WorldWideScience

Sample records for ladar based object

  1. Ground target detection based on discrete cosine transform and Rényi entropy for imaging ladar

    Science.gov (United States)

    Xu, Yuannan; Chen, Weili; Li, Junwei; Dong, Yanbing

    2016-01-01

    The discrete cosine transform (DCT) due to its excellent properties that the images can be represented in spatial/spatial-frequency domains, has been applied in sequence data analysis and image fusion. For intensity and range images of ladar, through the DCT using one dimension window, the statistical property of Rényi entropy for images is studied. We also analyzed the change of Rényi entropy's statistical property in the ladar intensity and range images when the man-made objects appear. From this foundation, a novel method for generating saliency map based on DCT and Rényi entropy is proposed. After that, ground target detection is completed when the saliency map is segmented using a simple and convenient threshold method. For the ladar intensity and range images, experimental results show the proposed method can effectively detect the military vehicles from complex earth background with low false alarm.

  2. Precision and Accuracy Testing of FMCW Ladar Based Length Metrology

    OpenAIRE

    Mateo, Ana Baselga; Barber, Zeb W.

    2015-01-01

    The calibration and traceability of high resolution frequency modulated continuous wave (FMCW) ladar sources is a requirement for their use in length and volume metrology. We report the calibration of a FMCW ladar length measurement system by use of spectroscopy of molecular frequency references HCN (C-band) or CO (L-band) to calibrate the chirp rate of the FMCW source. Propagating the stated uncertainties from the molecular calibrations provided by NIST and measurement errors provides an est...

  3. Imaging through obscurants with a heterodyne detection-based ladar system

    Science.gov (United States)

    Reibel, Randy R.; Roos, Peter A.; Kaylor, Brant M.; Berg, Trenton J.; Curry, James R.

    2014-06-01

    Bridger Photonics has been researching and developing a ladar system based on heterodyne detection for imaging through brownout and other DVEs. There are several advantages that an FMCW ladar system provides compared to direct detect pulsed time-of-flight systems including: 1) Higher average powers, 2) Single photon sensitive while remaining tolerant to strong return signals, 3) Doppler sensitivity for clutter removal, and 4) More flexible system for sensing during various stages of flight. In this paper, we provide a review of our sensor, discuss lessons learned during various DVE tests, and show our latest 3D imagery.

  4. Precision and Accuracy Testing of FMCW Ladar Based Length Metrology

    CERN Document Server

    Mateo, Ana Baselga

    2015-01-01

    The calibration and traceability of high resolution frequency modulated continuous wave (FMCW) ladar sources is a requirement for their use in length and volume metrology. We report the calibration of a FMCW ladar length measurement system by use of spectroscopy of molecular frequency references HCN (C-band) or CO (L-band) to calibrate the chirp rate of the FMCW source. Propagating the stated uncertainties from the molecular calibrations provided by NIST and measurement errors provides an estimated uncertainty of a few ppm for the FMCW system. As a test of this calibration, a displacement measurement interferometer with a laser wavelength close to that of our FMCW system was built to make comparisons of the relative precision and accuracy. The comparisons performed show ppm agreement which is within the combined estimated uncertainties of the FMCW system and interferometer.

  5. Advances in ground vehicle-based LADAR for standoff detection of road-side hazards

    Science.gov (United States)

    Hollinger, Jim; Vessey, Alyssa; Close, Ryan; Middleton, Seth; Williams, Kathryn; Rupp, Ronald; Nguyen, Son

    2016-05-01

    Commercial sensor technology has the potential to bring cost-effective sensors to a number of U.S. Army applications. By using sensors built for a widespread of commercial application, such as the automotive market, the Army can decrease costs of future systems while increasing overall capabilities. Additional sensors operating in alternate and orthogonal modalities can also be leveraged to gain a broader spectrum measurement of the environment. Leveraging multiple phenomenologies can reduce false alarms and make detection algorithms more robust to varied concealment materials. In this paper, this approach is applied to the detection of roadside hazards partially concealed by light-to-medium vegetation. This paper will present advances in detection algorithms using a ground vehicle-based commercial LADAR system. The benefits of augmenting a LADAR with millimeter-wave automotive radar and results from relevant data sets are also discussed.

  6. Optical imaging process based on two-dimensional Fourier transform for synthetic aperture imaging ladar

    Science.gov (United States)

    Sun, Zhiwei; Zhi, Ya'nan; Liu, Liren; Sun, Jianfeng; Zhou, Yu; Hou, Peipei

    2013-09-01

    The synthetic aperture imaging ladar (SAIL) systems typically generate large amounts of data difficult to compress with digital method. This paper presents an optical SAIL processor based on compensation of quadratic phase of echo in azimuth direction and two dimensional Fourier transform. The optical processor mainly consists of one phase-only liquid crystal spatial modulator(LCSLM) to load the phase data of target echo and one cylindrical lens to compensate the quadratic phase and one spherical lens to fulfill the task of two dimensional Fourier transform. We show the imaging processing result of practical target echo obtained by a synthetic aperture imaging ladar demonstrator. The optical processor is compact and lightweight and could provide inherent parallel and the speed-of-light computing capability, it has a promising application future especially in onboard and satellite borne SAIL systems.

  7. Spectral ladar: towards active 3D multispectral imaging

    Science.gov (United States)

    Powers, Michael A.; Davis, Christopher C.

    2010-04-01

    In this paper we present our Spectral LADAR concept, an augmented implementation of traditional LADAR. This sensor uses a polychromatic source to obtain range-resolved 3D spectral images which are used to identify objects based on combined spatial and spectral features, resolving positions in three dimensions and up to hundreds of meters in distance. We report on a proof-of-concept Spectral LADAR demonstrator that generates spectral point clouds from static scenes. The demonstrator transmits nanosecond supercontinuum pulses generated in a photonic crystal fiber. Currently we use a rapidly tuned receiver with a high-speed InGaAs APD for 25 spectral bands with the future expectation of implementing a linear APD array spectrograph. Each spectral band is independently range resolved with multiple return pulse recognition. This is a critical feature, enabling simultaneous spectral and spatial unmixing of partially obscured objects when not achievable using image fusion of monochromatic LADAR and passive spectral imagers. This enables higher identification confidence in highly cluttered environments such as forested or urban areas (e.g. vehicles behind camouflage or foliage). These environments present challenges for situational awareness and robotic perception which can benefit from the unique attributes of Spectral LADAR. Results from this demonstrator unit are presented for scenes typical of military operations and characterize the operation of the device. The results are discussed here in the context of autonomous vehicle navigation and target recognition.

  8. Pose recognition of articulated target based on ladar range image with elastic shape analysis

    Science.gov (United States)

    Liu, Zheng-Jun; Li, Qi; Wang, Qi

    2014-10-01

    Elastic shape analysis is introduced for pose recognition of articulated target which is based on small samples of ladar range images. Shape deformations caused by poses changes represented as closed elastic curves given by the square-root velocity function geodesics are used to quantify shape differences and the Karcher mean is used to build a model library. Three kinds of moments - Hu moment invariants, affine moment invariants, and Zernike moment invariants based on support vector machines (SVMs) - are applied to evaluate this approach. The experiment results show that no matter what the azimuth angles of the testing samples are, this approach is capable of achieving a high recognition rate using only 3 model samples with different carrier to noise ratios (CNR); the performance of this approach is much better than that of three kinds of moments based on SVM, especially under high noise conditions.

  9. MBE based HgCdTe APDs and 3D LADAR sensors

    Science.gov (United States)

    Jack, Michael; Asbrock, Jim; Bailey, Steven; Baley, Diane; Chapman, George; Crawford, Gina; Drafahl, Betsy; Herrin, Eileen; Kvaas, Robert; McKeag, William; Randall, Valerie; De Lyon, Terry; Hunter, Andy; Jensen, John; Roberts, Tom; Trotta, Patrick; Cook, T. Dean

    2007-04-01

    Raytheon is developing HgCdTe APD arrays and sensor chip assemblies (SCAs) for scanning and staring LADAR systems. The nonlinear characteristics of APDs operating in moderate gain mode place severe requirements on layer thickness and doping uniformity as well as defect density. MBE based HgCdTe APD arrays, engineered for high performance, meet the stringent requirements of low defects, excellent uniformity and reproducibility. In situ controls for alloy composition and substrate temperature have been implemented at HRL, LLC and Raytheon Vision Systems and enable consistent run to run results. The novel epitaxial designed using separate absorption-multiplication (SAM) architectures enables the realization of the unique advantages of HgCdTe including: tunable wavelength, low-noise, high-fill factor, low-crosstalk, and ambient operation. Focal planes built by integrating MBE detectors arrays processed in a 2 x 128 format have been integrated with 2 x 128 scanning ROIC designed. The ROIC reports both range and intensity and can detect multiple laser returns with each pixel autonomously reporting the return. FPAs show exceptionally good bias uniformity China Lake. Excellent spatial and range resolution has been achieved with 3D imagery demonstrated both at short range and long range. Ongoing development under an Air Force Sponsored MANTECH program of high performance HgCdTe MBE APDs grown on large silicon wafers promise significant FPA cost reduction both by increasing the number of arrays on a given wafer and enabling automated processing.

  10. EO Scanned Micro-LADAR Project

    Data.gov (United States)

    National Aeronautics and Space Administration — In this SBIR program we will develop, design and build new scanning based micro-ladar sensors with unprecedented small size, weight, and power (SWaP), thereby...

  11. EO Scanned Micro-LADAR Project

    Data.gov (United States)

    National Aeronautics and Space Administration — In this phase II SBIR we will design, build, test, and deliver new scanning based micro-ladar sensors with unprecedented small size, weight, and power (SWaP),...

  12. Research on key technologies of LADAR echo signal simulator

    Science.gov (United States)

    Xu, Rui; Shi, Rui; Ye, Jiansen; Wang, Xin; Li, Zhuo

    2015-10-01

    LADAR echo signal simulator is one of the most significant components of hardware-in-the-loop (HWIL) simulation systems for LADAR, which is designed to simulate the LADAR return signal in laboratory conditions. The device can provide the laser echo signal of target and background for imaging LADAR systems to test whether it is of good performance. Some key technologies are investigated in this paper. Firstly, the 3D model of typical target is built, and transformed to the data of the target echo signal based on ranging equation and targets reflection characteristics. Then, system model and time series model of LADAR echo signal simulator are established. Some influential factors which could induce fixed delay error and random delay error on the simulated return signals are analyzed. In the simulation system, the signal propagating delay of circuits and the response time of pulsed lasers are belong to fixed delay error. The counting error of digital delay generator, the jitter of system clock and the desynchronized between trigger signal and clock signal are a part of random delay error. Furthermore, these system insertion delays are analyzed quantitatively, and the noisy data are obtained. The target echo signals are got by superimposing of the noisy data and the pure target echo signal. In order to overcome these disadvantageous factors, a method of adjusting the timing diagram of the simulation system is proposed. Finally, the simulated echo signals are processed by using a detection algorithm to complete the 3D model reconstruction of object. The simulation results reveal that the range resolution can be better than 8 cm.

  13. Target recognition for ladar range image using slice image

    Science.gov (United States)

    Xia, Wenze; Han, Shaokun; Wang, Liang

    2015-12-01

    A shape descriptor and a complete shape-based recognition system using slice images as geometric feature descriptor for ladar range images are introduced. A slice image is a two-dimensional image generated by three-dimensional Hough transform and the corresponding mathematical transformation. The system consists of two processes, the model library construction and recognition. In the model library construction process, a series of range images are obtained after the model object is sampled at preset attitude angles. Then, all the range images are converted into slice images. The number of slice images is reduced by clustering analysis and finding a representation to reduce the size of the model library. In the recognition process, the slice image of the scene is compared with the slice image in the model library. The recognition results depend on the comparison. Simulated ladar range images are used to analyze the recognition and misjudgment rates, and comparison between the slice image representation method and moment invariants representation method is performed. The experimental results show that whether in conditions without noise or with ladar noise, the system has a high recognition rate and low misjudgment rate. The comparison experiment demonstrates that the slice image has better representation ability than moment invariants.

  14. Progress on MEMS-scanned ladar

    Science.gov (United States)

    Stann, Barry L.; Dammann, John F.; Giza, Mark M.

    2016-05-01

    The Army Research Laboratory (ARL) has continued to research a short-range ladar imager for use on small unmanned ground vehicles (UGV) and recently small unmanned air vehicles (UAV). The current ladar brassboard is based on a micro-electro-mechanical system (MEMS) mirror coupled to a low-cost pulsed erbium fiber laser. It has a 5-6 Hz frame rate, an image size of 256 (h) x 128 (v) pixels, a 42º x 21º field of regard, 35 m range, eyesafe operation, and 40 cm range resolution with provisions for super-resolution. Experience with driving experiments on small ground robots and efforts to extend the use of the ladar to UAV applications has encouraged work to improve the ladar's performance. The data acquisition system can now capture range data from the three return pulses in a pixel (that is first, last, and largest return), and information such as elapsed time, operating parameters, and data from an inertial navigation system. We will mention the addition and performance of subsystems to obtain eye-safety certification. To meet the enhanced range requirement for the UAV application, we describe a new receiver circuit that improves the signal-to-noise (SNR) several-fold over the existing design. Complementing this work, we discuss research to build a low-capacitance large area detector that may enable even further improvement in receiver SNR. Finally, we outline progress to build a breadboard ladar to demonstrate increased range to 160 m. If successful, this ladar will be integrated with a color camera and inertial navigation system to build a data collection package to determine imaging performance for a small UAV.

  15. Integration and demonstration of MEMS-scanned LADAR for robotic navigation

    Science.gov (United States)

    Stann, Barry L.; Dammann, John F.; Del Giorno, Mark; DiBerardino, Charles; Giza, Mark M.; Powers, Michael A.; Uzunovic, Nenad

    2014-06-01

    LADAR is among the pre-eminent sensor modalities for autonomous vehicle navigation. Size, weight, power and cost constraints impose significant practical limitations on perception systems intended for small ground robots. In recent years, the Army Research Laboratory (ARL) developed a LADAR architecture based on a MEMS mirror scanner that fundamentally improves the trade-offs between these limitations and sensor capability. We describe how the characteristics of a highly developed prototype correspond to and satisfy the requirements of autonomous navigation and the experimental scenarios of the ARL Robotics Collaborative Technology Alliance (RCTA) program. In particular, the long maximum and short minimum range capability of the ARL MEMS LADAR makes it remarkably suitable for a wide variety of scenarios from building mapping to the manipulation of objects at close range, including dexterous manipulation with robotic arms. A prototype system was applied to a small (approximately 50 kg) unmanned robotic vehicle as the primary mobility perception sensor. We present the results of a field test where the perception information supplied by the LADAR system successfully accomplished the experimental objectives of an Integrated Research Assessment (IRA).

  16. Miniature Ground Mapping LADAR Project

    Data.gov (United States)

    National Aeronautics and Space Administration — System & Processes Engineering Corporation (SPEC) proposes a miniature solid state surface imaging LADAR, for imaging the landing areas providing precision...

  17. Anomaly Detection in Clutter using Spectrally Enhanced Ladar

    CERN Document Server

    Chhabra, Puneet S; Hopgood, James R

    2016-01-01

    Discrete return (DR) Laser Detection and Ranging (Ladar) systems provide a series of echoes that reflect from objects in a scene. These can be first, last or multi-echo returns. In contrast, Full-Waveform (FW)-Ladar systems measure the intensity of light reflected from objects continuously over a period of time. In a camouflaged scenario, e.g., objects hidden behind dense foliage, a FW-Ladar penetrates such foliage and returns a sequence of echoes including buried faint echoes. The aim of this paper is to learn local-patterns of co-occurring echoes characterised by their measured spectra. A deviation from such patterns defines an abnormal event in a forest/tree depth profile. As far as the authors know, neither DR or FW-Ladar, along with several spectral measurements, has not been applied to anomaly detection. This work presents an algorithm that allows detection of spectral and temporal anomalies in FW-Multi Spectral Ladar (FW-MSL) data samples. An anomaly is defined as a full waveform temporal and spectral ...

  18. Ladar scene projector for a hardware-in-the-loop simulation system.

    Science.gov (United States)

    Xu, Rui; Wang, Xin; Tian, Yi; Li, Zhuo

    2016-07-20

    In order to test a direct-detection ladar in a hardware-in-the-loop simulation system, a ladar scene projector is proposed. A model based on the ladar range equation is developed to calculate the profile of the ladar return signal. The influences of both the atmosphere and the target's surface properties are considered. The insertion delays of different channels of the ladar scene projector are investigated and compensated for. A target range image with 108 pixels is generated. The simulation range is from 0 to 15 km, the range resolution is 1.04 m, the range error is 1.28 cm, and the peak-valley error for different channels is 15 cm. PMID:27463932

  19. Ultra-compact, High Resolution, LADAR system for 3D Imaging Project

    Data.gov (United States)

    National Aeronautics and Space Administration — SiWave proposes to develop an innovative, ultra-compact, high resolution, long range LADAR system to produce a 3D map of the exterior of any object in space such as...

  20. Doublet Pulse Coherent Laser Radar for Tracking of Resident Space Objects

    Science.gov (United States)

    Prasad, Narasimha S.; Rudd, Van; Shald, Scott; Sandford, Stephen; Dimarcantonio, Albert

    2014-01-01

    In this paper, the development of a long range ladar system known as ExoSPEAR at NASA Langley Research Center for tracking rapidly moving resident space objects is discussed. Based on 100 W, nanosecond class, near-IR laser, this ladar system with coherent detection technique is currently being investigated for short dwell time measurements of resident space objects (RSOs) in LEO and beyond for space surveillance applications. This unique ladar architecture is configured using a continuously agile doublet-pulse waveform scheme coupled to a closed-loop tracking and control loop approach to simultaneously achieve mm class range precision and mm/s velocity precision and hence obtain unprecedented track accuracies. Salient features of the design architecture followed by performance modeling and engagement simulations illustrating the dependence of range and velocity precision in LEO orbits on ladar parameters are presented. Estimated limits on detectable optical cross sections of RSOs in LEO orbits are discussed.

  1. Anti-ship missile tracking with a chirped AM ladar - Update: design, model predictions, and experimental results

    Science.gov (United States)

    Redman, Brian; Ruff, William; Stann, Barry; Giza, Mark; Lawler, William; Dammann, John; Potter, William

    2005-05-01

    Shipboard infrared search and track (IRST) systems can detect sea-skimming, anti-ship missiles at long ranges. Since IRST systems cannot measure range and line-of-sight (LOS) velocity, they have difficulty distinguishing missiles from false targets and clutter. In a joint Army-Navy program, the Army Research Laboratory (ARL) is developing a ladar based on the chirped amplitude modulation (AM) technique to provide range and velocity measurements of potential targets handed-over by the distributed aperture system - IRST (DAS-IRST) being developed by the Naval Research Laboratory (NRL) and sponsored by the Office of Naval Research (ONR). Using the ladar's range and velocity data, false alarms and clutter will be eliminated, and valid missile targets' tracks will be updated. By using an array receiver, ARL's ladar will also provide 3D imagery of potential threats for force protection/situational awareness. The concept of operation, the Phase I breadboard ladar design and performance model results, and the Phase I breadboard ladar development program were presented in paper 5413-16 at last year's symposium. This paper will present updated design and performance model results, as well as recent laboratory and field test results for the Phase I breadboard ladar. Implications of the Phase I program results on the design, development, and testing of the Phase II brassboard ladar will also be discussed.

  2. Object-Based Benefits without Object-Based Representations

    OpenAIRE

    Alvarez, George Angelo; Fougnie, Daryl; Cormiea, Sarah M

    2012-01-01

    The organization of visual information into objects strongly influences visual memory: Displays with objects defined by two features (e.g. color, orientation) are easier to remember than displays with twice as many objects defined by one feature (Olson & Jiang, 2002). Existing theories suggest that this ‘object-benefit’ is based on object-based limitations in working memory: because a limited number of objects can be stored, packaging features together so that fewer objects have to be remembe...

  3. Pulse laser imaging amplifier for advanced ladar systems

    Science.gov (United States)

    Khizhnyak, Anatoliy; Markov, Vladimir; Tomov, Ivan; Murrell, David

    2016-05-01

    Security measures sometimes require persistent surveillance of government, military and public areas Borders, bridges, sport arenas, airports and others are often surveilled with low-cost cameras. Their low-light performance can be enhanced with laser illuminators; however various operational scenarios may require a low-intensity laser illumination with the object-scattered light intensity lower than the sensitivity of the Ladar image detector. This paper discusses a novel type of high-gain optical image amplifier. The approach enables time-synchronization of the incoming and amplifying signals with accuracy <= 1 ns. The technique allows the incoming signal to be amplified without the need to match the input spectrum to the cavity modes. Instead, the incoming signal is accepted within the spectral band of the amplifier. We have gauged experimentally the performance of the amplifier with a 40 dB gain and an angle of view 20 mrad.

  4. A Comparative Study between Frequency-Modulated Continous Wave LADAR and Linear LiDAR

    Science.gov (United States)

    Massaro, R. D.; Anderson, J. E.; Nelson, J. D.; Edwards, J. D.

    2014-11-01

    Topographic Light Detection and Ranging (LiDAR) technology has advanced greatly in the past decade. Pulse repetition rates of terrestrial and airborne systems havemultiplied thus vastly increasing data acquisition rates. Geiger-mode and FLASH LiDAR have also become far more mature technologies. However, a new and relatively unknown technology is maturing rapidly: Frequency-Modulated Continuous Wave Laser Detection and Ranging (FMCW-LADAR). Possessing attributes more akin to modern radar systems, FMCWLADAR has the ability to more finely resolve objects separated by very small ranges. For tactical military applications (as described here), this can be a real advantage over single frequency, direct-detect systems. In fact, FMCW-LADAR can range resolve objects at 10-7 to 10-6 meter scales. FMCW-LADAR can also detect objects at greater range with less power. In this study, a FMCWLADAR instrument and traditional LiDAR instrument are compared. The co-located terrestrial scanning instruments were set up to perform simultaneous 3-D measurements of the given scene. Several targets were placed in the scene to expose the difference in the range resolution capabilities of the two instruments. The scans were performed at or nearly the same horizontal and vertical angular resolutions. It is demonstrated that the FMCW-LADAR surpasses the perfomance of the linear mode LiDAR scanner in terms of range resolution. Some results showing the maximum range acquisition are discussed but this was not studied in detail as the scanners' laser powers differed by a small amount. Applications and implications of this technology are also discussed.

  5. Multi-Dimensional, Non-Contact Metrology using Trilateration and High Resolution FMCW Ladar

    CERN Document Server

    Mateo, Ana Baselga

    2015-01-01

    Here we propose, describe, and provide experimental proof-of-concept demonstrations of a multi-dimensional, non-contact length metrology system design based on high resolution (millimeter to sub-100 micron) frequency modulated continuous wave (FMCW) ladar and trilateration based on length measurements from multiple, optical fiber-connected transmitters. With an accurate FMCW ladar source, the trilateration based design provides 3D resolution inherently independent of stand-off range and allows self-calibration to provide flexible setup of a field system. A proof-of-concept experimental demonstration was performed using a highly-stabilized, 2 THz bandwidth chirped laser source, two emitters, and one scanning emitter/receiver providing 1D surface profiles (2D metrology) of diffuse targets. The measured coordinate precision of < 200 microns was determined to be limited by laser speckle issues caused by diffuse scattering of the targets.

  6. Imaging of Airborne Synthetic Aperture Ladar under Platform Vibration Condition

    OpenAIRE

    Ma Meng; Li Dao-jing; Du Jian-bo

    2014-01-01

    This study examines the imaging problems in airborne synthetic aperture ladar with single detector and dual detectors along tracks under platform vibration condition. Because platform vibrations affect imaging processing for short intervals negligibly, a method uniting the subaperture imaging and phase gradient autofocus is considered for single-detector ladar. To obtain long stripmap images in azimuth, the stripmap phase gradient autofocus method and the subaperture image mosaic process usin...

  7. A low-power CMOS trans-impedance amplifier for FM/cw ladar imaging system

    Science.gov (United States)

    Hu, Kai; Zhao, Yi-qiang; Sheng, Yun; Zhao, Hong-liang; Yu, Hai-xia

    2013-09-01

    A scannerless ladar imaging system based on a unique frequency modulation/continuous wave (FM/cw) technique is able to entirely capture the target environment, using a focal plane array to construct a 3D picture of the target. This paper presents a low power trans-impedance amplifier (TIA) designed and implemented by 0.18 μm CMOS technology, which is used in the FM/cw imaging ladar with a 64×64 metal-semiconductor-metal(MSM) self-mixing detector array. The input stage of the operational amplifier (op amp) in TIA is realized with folded cascade structure to achieve large open loop gain and low offset. The simulation and test results of TIA with MSM detectors indicate that the single-end trans-impedance gain is beyond 100 kΩ, and the -3 dB bandwidth of Op Amp is beyond 60 MHz. The input common mode voltage ranges from 0.2 V to 1.5 V, and the power dissipation is reduced to 1.8 mW with a supply voltage of 3.3 V. The performance test results show that the TIA is a candidate for preamplifier of the read-out integrated circuit (ROIC) in the FM/cw scannerless ladar imaging system.

  8. Development of a 3D Flash LADAR Video Camera for Entry, Decent and Landing Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Advanced Scientific Concepts, Inc. (ASC) has developed a 128 x 128 frame, 3D Flash LADAR video camera capable of a 30 Hz frame rate. Because Flash LADAR captures an...

  9. Development of a 3D Flash LADAR Video Camera for Entry, Decent, and Landing Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Advanced Scientific Concepts, Inc. (ASC) has developed a 128 x 128 frame, 3D Flash LADAR video camera which produces 3-D point clouds at 30 Hz. Flash LADAR captures...

  10. Object-Based Image Compression

    Science.gov (United States)

    Schmalz, Mark S.

    2003-01-01

    Image compression frequently supports reduced storage requirement in a computer system, as well as enhancement of effective channel bandwidth in a communication system, by decreasing the source bit rate through reduction of source redundancy. The majority of image compression techniques emphasize pixel-level operations, such as matching rectangular or elliptical sampling blocks taken from the source data stream, with exemplars stored in a database (e.g., a codebook in vector quantization or VQ). Alternatively, one can represent a source block via transformation, coefficient quantization, and selection of coefficients deemed significant for source content approximation in the decompressed image. This approach, called transform coding (TC), has predominated for several decades in the signal and image processing communities. A further technique that has been employed is the deduction of affine relationships from source properties such as local self-similarity, which supports the construction of adaptive codebooks in a self-VQ paradigm that has been called iterated function systems (IFS). Although VQ, TC, and IFS based compression algorithms have enjoyed varying levels of success for different types of applications, bit rate requirements, and image quality constraints, few of these algorithms examine the higher-level spatial structure of an image, and fewer still exploit this structure to enhance compression ratio. In this paper, we discuss a fourth type of compression algorithm, called object-based compression, which is based on research in joint segmentaton and compression, as well as previous research in the extraction of sketch-like representations from digital imagery. Here, large image regions that correspond to contiguous recognizeable objects or parts of objects are segmented from the source, then represented compactly in the compressed image. Segmentation is facilitated by source properties such as size, shape, texture, statistical properties, and spectral

  11. Object-Based Attention Guided by An Invisible Object

    Directory of Open Access Journals (Sweden)

    Xilin Zhang

    2011-05-01

    Full Text Available Many studies have demonstrated that attention can be object based. One line of evidence supporting object-based attention showed that observers respond to a target faster when the target and cue are in the same object than when they are in different objects, which is called the same-object advantage. By adopting the double-rectangle cuing paradigm (Egly, Driver, & Rafal, 1994, we tested whether this advantage can occur with invisible rectangles. The original paradigm was slightly modified. Rectangles had a low luminance level against a dark background and were presented for only 10 ms, along with a cue or a target. These two characteristics rendered the rectangles invisible to subjects, as confirmed by a forced-choice test. We found a conventional object-based attention effect even when the rectangles were invisible. We also found that the object-based attention was dependent on the orientation of the rectangles presented along with the target, consistent with the finding by Ho and Yeh (2009. These results suggest that object based attention can be guided by an invisible object in an automatic way, with a minimal influence from the high level top-down control.

  12. Target-object integration, attention distribution, and object orientation interactively modulate object-based selection.

    Science.gov (United States)

    Al-Janabi, Shahd; Greenberg, Adam S

    2016-10-01

    The representational basis of attentional selection can be object-based. Various studies have suggested, however, that object-based selection is less robust than spatial selection across experimental paradigms. We sought to examine the manner by which the following factors might explain this variation: Target-Object Integration (targets 'on' vs. part 'of' an object), Attention Distribution (narrow vs. wide), and Object Orientation (horizontal vs. vertical). In Experiment 1, participants discriminated between two targets presented 'on' an object in one session, or presented as a change 'of' an object in another session. There was no spatial cue-thus, attention was initially focused widely-and the objects were horizontal or vertical. We found evidence of object-based selection only when targets constituted a change 'of' an object. Additionally, object orientation modulated the sign of object-based selection: We observed a same-object advantage for horizontal objects, but a same-object cost for vertical objects. In Experiment 2, an informative cue preceded a single target presented 'on' an object or as a change 'of' an object (thus, attention was initially focused narrowly). Unlike in Experiment 1, we found evidence of object-based selection independent of target-object integration. We again found that the sign of selection was modulated by the objects' orientation. This result may reflect a meridian effect, which emerged due to anisotropies in the cortical representations when attention is oriented endogenously. Experiment 3 revealed that object orientation did not modulate object-based selection when attention was oriented exogenously. Our findings suggest that target-object integration, attention distribution, and object orientation modulate object-based selection, but only in combination. PMID:27198915

  13. Simulation of a Geiger-Mode Imaging LADAR System for Performance Assessment

    Science.gov (United States)

    Kim, Seongjoon; Lee, Impyeong; Kwon, Yong Joon

    2013-01-01

    As LADAR systems applications gradually become more diverse, new types of systems are being developed. When developing new systems, simulation studies are an essential prerequisite. A simulator enables performance predictions and optimal system parameters at the design level, as well as providing sample data for developing and validating application algorithms. The purpose of the study is to propose a method for simulating a Geiger-mode imaging LADAR system. We develop simulation software to assess system performance and generate sample data for the applications. The simulation is based on three aspects of modeling—the geometry, radiometry and detection. The geometric model computes the ranges to the reflection points of the laser pulses. The radiometric model generates the return signals, including the noises. The detection model determines the flight times of the laser pulses based on the nature of the Geiger-mode detector. We generated sample data using the simulator with the system parameters and analyzed the detection performance by comparing the simulated points to the reference points. The proportion of the outliers in the simulated points reached 25.53%, indicating the need for efficient outlier elimination algorithms. In addition, the false alarm rate and dropout rate of the designed system were computed as 1.76% and 1.06%, respectively. PMID:23823970

  14. Range resolution improvement of eyesafe ladar testbed (ELT) measurements using sparse signal deconvolution

    Science.gov (United States)

    Budge, Scott E.; Gunther, Jacob H.

    2014-06-01

    The Eyesafe Ladar Test-bed (ELT) is an experimental ladar system with the capability of digitizing return laser pulse waveforms at 2 GHz. These waveforms can then be exploited off-line in the laboratory to develop signal processing techniques for noise reduction, range resolution improvement, and range discrimination between two surfaces of similar range interrogated by a single laser pulse. This paper presents the results of experiments with new deconvolution algorithms with the hoped-for gains of improving the range discrimination of the ladar system. The sparsity of ladar returns is exploited to solve the deconvolution problem in two steps. The first step is to estimate a point target response using a database of measured calibration data. This basic target response is used to construct a dictionary of target responses with different delays/ranges. Using this dictionary ladar returns from a wide variety of surface configurations can be synthesized by taking linear combinations. A sparse linear combination matches the physical reality that ladar returns consist of the overlapping of only a few pulses. The dictionary construction process is a pre-processing step that is performed only once. The deconvolution step is performed by minimizing the error between the measured ladar return and the dictionary model while constraining the coefficient vector to be sparse. Other constraints such as the non-negativity of the coefficients are also applied. The results of the proposed technique are presented in the paper and are shown to compare favorably with previously investigated deconvolution techniques.

  15. View-based 3-D object retrieval

    CERN Document Server

    Gao, Yue

    2014-01-01

    Content-based 3-D object retrieval has attracted extensive attention recently and has applications in a variety of fields, such as, computer-aided design, tele-medicine,mobile multimedia, virtual reality, and entertainment. The development of efficient and effective content-based 3-D object retrieval techniques has enabled the use of fast 3-D reconstruction and model design. Recent technical progress, such as the development of camera technologies, has made it possible to capture the views of 3-D objects. As a result, view-based 3-D object retrieval has become an essential but challenging res

  16. Speedy Object Detection Based on Shape

    Directory of Open Access Journals (Sweden)

    Y. Jayanta Singh

    2013-07-01

    Full Text Available This study is a part of design of an audio system for in-house object detection system for visually impaired,low vision personnel by birth or by an accident ordue to old age. The input of the system will be scene andoutput as audio. Alert facility is provided based on severity levels of the objects (snake, broke glass etc andalso during difficulties. The study proposed techniques to provide speedy detection of objects based onshapes and its scale. Features are extraction to have minimum spaces using dynamic scaling. From ascene, clusters of objects are formed based on thescale and shape. Searching is performed among theclusters initially based on the shape, scale, meancluster value and index of object(s. The minimumoperation to detect the possible shape of the object is performed. In case the object does not have alikelymatching shape, scale etc, then the several operations required for an object detection will not perform;instead, it will declared as a new object. In suchway, this study finds a speedy way of detecting objects.

  17. SPEEDY OBJECT DETECTION BASED ON SHAPE

    Directory of Open Access Journals (Sweden)

    Y. Jayanta Singh

    2013-06-01

    Full Text Available This study is a part of design of an audio system for in-house object detection system for visually impaired, low vision personnel by birth or by an accident or due to old age. The input of the system will be scene and output as audio. Alert facility is provided based on severity levels of the objects (snake, broke glass etc and also during difficulties. The study proposed techniques to provide speedy detection of objects based on shapes and its scale. Features are extraction to have minimum spaces using dynamic scaling. From a scene, clusters of objects are formed based on the scale and shape. Searching is performed among the clusters initially based on the shape, scale, mean cluster value and index of object(s. The minimum operation to detect the possible shape of the object is performed. In case the object does not have a likely matching shape, scale etc, then the several operations required for an object detection will not perform; instead, it will declared as a new object. In such way, this study finds a speedy way of detecting objects.

  18. Building a Knowledge Base from Learning Objects

    OpenAIRE

    Fredlund, Per Kristen

    2005-01-01

    The goal of this thesis has been to investigate if it is possible to develop a knowledge structure,knowledge base, based on learning objects. In this connection a learning object is a digital unitwhich should, as a minimum, contain a picture and some text. Most likely a learning objectwould function as a container with anchors for video, animations and links to html-pages.For every learning object there exists a textual description. If we consider the learning object asan overhead presented i...

  19. Advances in LADAR Components and Subsystems at Raytheon

    Science.gov (United States)

    Jack, Michael; Chapman, George; Edwards, John; McKeag, William; Veeder, Tricia; Wehner, Justin; Roberts, Tom; Robinson, Tom; Neisz, James; Andressen, Cliff; Rinker, Robert; Hall, Donald N. B.; Jacobson, Shane M.; Amzajerdian, Farzin; Cook, T. Dean

    2012-01-01

    Raytheon is developing NIR sensor chip assemblies (SCAs) for scanning and staring 3D LADAR systems. High sensitivity is obtained by integrating high performance detectors with gain, i.e., APDs with very low noise Readout Integrated Circuits (ROICs). Unique aspects of these designs include: independent acquisition (non-gated) of pulse returns, multiple pulse returns with both time and intensity reported to enable full 3D reconstruction of the image. Recent breakthrough in device design has resulted in HgCdTe APDs operating at 300K with essentially no excess noise to gains in excess of 100, low NEP <1nW and GHz bandwidths and have demonstrated linear mode photon counting. SCAs utilizing these high performance APDs have been integrated and demonstrated excellent spatial and range resolution enabling detailed 3D imagery both at short range and long ranges. In the following we will review progress in real-time 3D LADAR imaging receiver products in three areas: (1) scanning 256 x 4 configuration for the Multi-Mode Sensor Seeker (MMSS) program and (2) staring 256 x 256 configuration for the Autonomous Landing and Hazard Avoidance Technology (ALHAT) lunar landing mission and (3) Photon-Counting SCAs which have demonstrated a dramatic reduction in dark count rate due to improved design, operation and processing.

  20. Comb-calibrated frequency-modulated continuous-wave ladar for absolute distance measurements.

    Science.gov (United States)

    Baumann, Esther; Giorgetta, Fabrizio R; Coddington, Ian; Sinclair, Laura C; Knabe, Kevin; Swann, William C; Newbury, Nathan R

    2013-06-15

    We demonstrate a comb-calibrated frequency-modulated continuous-wave laser detection and ranging (FMCW ladar) system for absolute distance measurements. The FMCW ladar uses a compact external cavity laser that is swept quasi-sinusoidally over 1 THz at a 1 kHz rate. The system simultaneously records the heterodyne FMCW ladar signal and the instantaneous laser frequency at sweep rates up to 3400 THz/s, as measured against a free-running frequency comb (femtosecond fiber laser). Demodulation of the ladar signal against the instantaneous laser frequency yields the range to the target with 1 ms update rates, bandwidth-limited 130 μm resolution and a ~100 nm accuracy that is directly linked to the counted repetition rate of the comb. The precision is <100 nm at the 1 ms update rate and reaches ~6 nm for a 100 ms average. PMID:23938965

  1. Object based attention and visual area LO.

    OpenAIRE

    de-Wit, L.; Kentridge, R. W.; Milner, A D

    2009-01-01

    We investigated the neural basis of so-called “object-based attention” by examining patient D.F., who has visual form agnosia caused by bilateral damage to the lateral occipital (LO) area of the ventral visual stream. We tested D.F.’s object-based attention in two ways. In the first experiment, we used a spatial cueing procedure to compare the costs associated with shifting attention within versus between two separate outline figures. D.F. did not show the normal advantage of within-object ov...

  2. Coding Transparency in Object-Based Video

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Forchhammer, Søren

    2006-01-01

    A novel algorithm for coding gray level alpha planes in object-based video is presented. The scheme is based on segmentation in multiple layers. Different coders are specifically designed for each layer. In order to reduce the bit rate, cross-layer redundancies as well as temporal correlation...

  3. OBJECT ORIENTED SOFTWARE SYSTEM BASED ON AHP

    Directory of Open Access Journals (Sweden)

    Soumi Ghosh

    2012-11-01

    Full Text Available In modern days as because there are multiple number of object-oriented software systems, it is a real challenge for everyone to choose single one system among so many and variety of alternatives. This is obviously a challenging task to find out the most appropriate software system. In this particular study Analytical Hierarchy Process (AHP technique has been integrated with ISO 9126-1 and it has been applied for the purpose of selection of object oriented software system. In this process the basic features i.e. quality characteristics of ISO 9126-1 has to be identified and considered to formulate a set of rank for the object-oriented software system. To be specific the most appropriate object-oriented software systemmay be termed as number one rank based on its desirable features as against many other alternatives of the object-oriented software systems.

  4. Spatio-activity based object detection

    CERN Document Server

    Springett, Jarrad

    2008-01-01

    We present the SAMMI lightweight object detection method which has a high level of accuracy and robustness, and which is able to operate in an environment with a large number of cameras. Background modeling is based on DCT coefficients provided by cameras. Foreground detection uses similarity in temporal characteristics of adjacent blocks of pixels, which is a computationally inexpensive way to make use of object coherence. Scene model updating uses the approximated median method for improved performance. Evaluation at pixel level and application level shows that SAMMI object detection performs better and faster than the conventional Mixture of Gaussians method.

  5. Science objectives in the lunar base advocacy

    Science.gov (United States)

    Mendell, Wendell W.

    1988-01-01

    The author considers the potential function of astronomy in planning for a lunar base during the 21st century. He is one of the leading advocates for a permanent settlement on the Moon and has given considerable thought to the possible impact of such a station on science. He considers the rationale for a lunar base, research on the Moon, and the definition of science objectives.

  6. Invariant object recognition based on extended fragments.

    Science.gov (United States)

    Bart, Evgeniy; Hegdé, Jay

    2012-01-01

    Visual appearance of natural objects is profoundly affected by viewing conditions such as viewpoint and illumination. Human subjects can nevertheless compensate well for variations in these viewing conditions. The strategies that the visual system uses to accomplish this are largely unclear. Previous computational studies have suggested that in principle, certain types of object fragments (rather than whole objects) can be used for invariant recognition. However, whether the human visual system is actually capable of using this strategy remains unknown. Here, we show that human observers can achieve illumination invariance by using object fragments that carry the relevant information. To determine this, we have used novel, but naturalistic, 3-D visual objects called "digital embryos." Using novel instances of whole embryos, not fragments, we trained subjects to recognize individual embryos across illuminations. We then tested the illumination-invariant object recognition performance of subjects using fragments. We found that the performance was strongly correlated with the mutual information (MI) of the fragments, provided that MI value took variations in illumination into consideration. This correlation was not attributable to any systematic differences in task difficulty between different fragments. These results reveal two important principles of invariant object recognition. First, the subjects can achieve invariance at least in part by compensating for the changes in the appearance of small local features, rather than of whole objects. Second, the subjects do not always rely on generic or pre-existing invariance of features (i.e., features whose appearance remains largely unchanged by variations in illumination), and are capable of using learning to compensate for appearance changes when necessary. These psychophysical results closely fit the predictions of earlier computational studies of fragment-based invariant object recognition. PMID:22936910

  7. Invariant Object Recognition Based on Extended Fragments

    Directory of Open Access Journals (Sweden)

    Evgeniy eBart

    2012-08-01

    Full Text Available Visual appearance of natural objects is profoundly affected by viewing conditions such as viewpoint and illumination. Human subjects can nevertheless compensate well for variations in these viewing conditions. The strategies that the visual system uses to accomplish this are largely unclear. Previous computational studies have suggested that in principle, certain types of object fragments (rather than whole objects can be used for invariant recognition. However, whether the human visual system is actually capable of using this strategy remains unknown. Here, we show that human observers can achieve illumination invariance by using object fragments that carry the relevant information. To determine this, we have used novel, but naturalistic, 3-D visual objects called ‘digital embryos’. Using novel instances of whole embryos, not fragments, we trained subjects to recognize individual embryos across illuminations. We then tested the illumination-invariant object recognition performance of subjects using fragments. We found that the performance was strongly correlated with the mutual information (MI of the fragments, provided that MI value took variations in illumination into consideration. This correlation was not attributable to any systematic differences in task difficulty between different fragments. These results reveal two important principles of invariant object recognition. First, the subjects can achieve invariance at least in part by compensating for the changes in the appearance of small local features, rather than of whole objects. Second, the subjects do not always rely on generic or pre-existing invariance of features (i.e., features whose appearance remains largely unchanged by variations in illumination, and are capable of using learning to compensate for appearance changes when necessary. These psychophysical results closely fit the predictions of earlier computational studies of fragment-based invariant object recognition.

  8. Circular object recognition based on shape parameters

    Institute of Scientific and Technical Information of China (English)

    Chen Aijun; Li Jinzong; Zhu Bing

    2007-01-01

    To recognize circular objects rapidly in satellite remote sensing imagery, an approach using their geometry properties is presented.The original image is segmented to be a binary one by one dimension maximum entropy threshold algorithm and the binary image is labeled with an algorithm based on recursion technique.Then, shape parameters of all labeled regions are calculated and those regions with shape parameters satisfying certain conditions are recognized as circular objects.The algorithm is described in detail, and comparison experiments with the randomized Hough transformation (RHT) are also provided.The experimental results on synthetic images and real images show that the proposed method has the merits of fast recognition rate, high recognition efficiency and the ability of anti-noise and anti-jamming.In addition, the method performs well when some circular objects are little deformed and partly misshapen.

  9. GROUPING OBJECTS BASED ON THEIR APPEARANCE

    Directory of Open Access Journals (Sweden)

    Altamirano Robles Luis Carlos

    2013-07-01

    Full Text Available The use of clustering algorithms for partition to establish a hierarchical structure in a library of object models based on appearance is deployed. The main contribution corresponds to a novel and intuitive algorithm for clustering of models based on their appearance, closer to “human behavior”. This divides the complete set into subclasses. Immediately, divides each of these in a number of predefined groups to complete the levels of hierarchy that the user wants. Whose main purpose is to obtain a competitive classification compared to what a human would perform.

  10. Object Based Middleware for Grid Computing

    Directory of Open Access Journals (Sweden)

    S. Muruganantham

    2010-01-01

    Full Text Available Problem statement: “Grid” computing has emerged as an important new field, distinguished from conventional distributed computing by its focus on large-scale resource sharing, innovative applications and, in some cases, high-performance orientation. The role of middleware is to ease the task of designing, programming and managing distributed applications by providing a simple, consistent and integrated distributed programming environment. Essentially, middleware is a distributed software layer, which abstracts over the complexity and heterogeneity of the underlying distributed environment with its multitude of network technologies, machine architectures, operating systems and programming languages. Approach: This study brought out the development of supportive middleware to manage resources and distributed workload across multiple administrative boundaries is of central importance to Grid computing. Active middleware services that perform look-up, scheduling and staging are being developed that allow users to identify and utilize appropriate resources that provide sustainable system and user-level qualities of service. Results: Different middleware platforms support different programming models. Perhaps the most popular model is object-based middleware in which applications are structured into objects that interact via location transparent method invocation. Conclusion: The Object Management Group’s CORBA platform offer an Interface Definition Language (IDL which is used to abstract over the fact that objects can be implemented in any suitable programming language, an object request broker which is responsible for transparently directing method invocations to the appropriate target object and a set of services such as naming, time, transactions, replication which further enhance the programming environment.

  11. Robust feature-based object tracking

    Science.gov (United States)

    Han, Bing; Roberts, William; Wu, Dapeng; Li, Jian

    2007-04-01

    Object tracking is an important component of many computer vision systems. It is widely used in video surveillance, robotics, 3D image reconstruction, medical imaging, and human computer interface. In this paper, we focus on unsupervised object tracking, i.e., without prior knowledge about the object to be tracked. To address this problem, we take a feature-based approach, i.e., using feature points (or landmark points) to represent objects. Feature-based object tracking consists of feature extraction and feature correspondence. Feature correspondence is particularly challenging since a feature point in one image may have many similar points in another image, resulting in ambiguity in feature correspondence. To resolve the ambiguity, algorithms, which use exhaustive search and correlation over a large neighborhood, have been proposed. However, these algorithms incur high computational complexity, which is not suitable for real-time tracking. In contrast, Tomasi and Kanade's tracking algorithm only searches corresponding points in a small candidate set, which significantly reduces computational complexity; but the algorithm may lose track of feature points in a long image sequence. To mitigate the limitations of the aforementioned algorithms, this paper proposes an efficient and robust feature-based tracking algorithm. The key idea of our algorithm is as below. For a given target feature point in one frame, we first find a corresponding point in the next frame, which minimizes the sum-of-squared-difference (SSD) between the two points; then we test whether the corresponding point gives large value under the so-called Harris criterion. If not, we further identify a candidate set of feature points in a small neighborhood of the target point; then find a corresponding point from the candidate set, which minimizes the SSD between the two points. The algorithm may output no corresponding point due to disappearance of the target point. Our algorithm is capable of tracking

  12. Object Manipulation Facilitates Kind-Based Object Individuation of Shape-Similar Objects

    Science.gov (United States)

    Kingo, Osman S.; Krojgaard, Peter

    2011-01-01

    Five experiments investigated the importance of shape and object manipulation when 12-month-olds were given the task of individuating objects representing exemplars of kinds in an event-mapping design. In Experiments 1 and 2, results of the study from Xu, Carey, and Quint (2004, Experiment 4) were partially replicated, showing that infants were…

  13. [Electrophysiological bases of semantic processing of objects].

    Science.gov (United States)

    Kahlaoui, Karima; Baccino, Thierry; Joanette, Yves; Magnié, Marie-Noële

    2007-02-01

    How pictures and words are stored and processed in the human brain constitute a long-standing question in cognitive psychology. Behavioral studies have yielded a large amount of data addressing this issue. Generally speaking, these data show that there are some interactions between the semantic processing of pictures and words. However, behavioral methods can provide only limited insight into certain findings. Fortunately, Event-Related Potential (ERP) provides on-line cues about the temporal nature of cognitive processes and contributes to the exploration of their neural substrates. ERPs have been used in order to better understand semantic processing of words and pictures. The main objective of this article is to offer an overview of the electrophysiologic bases of semantic processing of words and pictures. Studies presented in this article showed that the processing of words is associated with an N 400 component, whereas pictures elicited both N 300 and N 400 components. Topographical analysis of the N 400 distribution over the scalp is compatible with the idea that both image-mediated concrete words and pictures access an amodal semantic system. However, given the distinctive N 300 patterns, observed only during picture processing, it appears that picture and word processing rely upon distinct neuronal networks, even if they end up activating more or less similar semantic representations. PMID:17291430

  14. Invariant object recognition based on extended fragments

    OpenAIRE

    Bart, Evgeniy; Hegdé, Jay

    2012-01-01

    Visual appearance of natural objects is profoundly affected by viewing conditions such as viewpoint and illumination. Human subjects can nevertheless compensate well for variations in these viewing conditions. The strategies that the visual system uses to accomplish this are largely unclear. Previous computational studies have suggested that in principle, certain types of object fragments (rather than whole objects) can be used for invariant recognition. However, whether the human visual syst...

  15. ROIC for gated 3D imaging LADAR receiver

    Science.gov (United States)

    Chen, Guoqiang; Zhang, Junling; Wang, Pan; Zhou, Jie; Gao, Lei; Ding, Ruijun

    2013-09-01

    Time of flight laser range finding, deep space communications and scanning video imaging are three applications requiring very low noise optical receivers to achieve detection of fast and weak optical signal. HgCdTe electrons initiated avalanche photodiodes (e-APDs) in linear multiplication mode is the detector of choice thanks to its high quantum efficiency, high gain at low bias, high bandwidth and low noise factor. In this project, a readout integrated circuit of hybrid e-APD focal plane array (FPA) with 100um pitch for 3D-LADAR was designed for gated optical receiver. The ROIC works at 77K, including unit cell circuit, column-level circuit, timing control, bias circuit and output driver. The unit cell circuit is a key component, which consists of preamplifier, correlated double Sampling (CDS), bias circuit and timing control module. Specially, the preamplifier used the capacitor feedback transimpedance amplifier (CTIA) structure which has two capacitors to offer switchable capacitance for passive/active dual mode imaging. The main circuit of column-level circuit is a precision Multiply-by-Two circuit which is implemented by switched-capacitor circuit. Switched-capacitor circuit is quite suitable for the signal processing of readout integrated circuit (ROIC) due to the working characteristics. The output driver uses a simply unity-gain buffer. Because the signal is amplified in column-level circuit, the amplifier in unity-gain buffer uses a rail-rail amplifier. In active imaging mode, the integration time is 80ns. Integrating current from 200nA to 4uA, this circuit shows the nonlinearity is less than 1%. In passive imaging mode, the integration time is 150ns. Integrating current from 1nA to 20nA shows the nonlinearity less than 1%.

  16. Line imaging ladar using a laser-diode transmitter and FM/cw radar principles for submunition applications

    Science.gov (United States)

    Stann, Barry L.; Abou-Auf, Ahmed; Ruff, William C.; Robinson, Dale; Liss, Brian; Potter, William; Sarama, Scott D.; Giza, Mark M.; Simon, Deborah R.; Frankel, Scott; Sztankay, Zoltan G.

    2000-09-01

    We describe the technical approach, component development, and test results of a line imager laser radar (ladar) being developed at the Army Research Laboratory (ARL) for smart munition applications. We obtain range information using a frequency modulation/continuous wave (FM/cw) technique implemented by directly amplitude modulating a near-IR diode laser transmitter with a radio frequency (rf) subcarrier that is linearly frequency modulated. The diode's output is collimated and projected to form a line illumination in the downrange image area. The returned signal is focused onto a line array of metal-semiconductor-metal (MSM) detectors where it is detected and mixed with a delayed replica of the laser modulation signal that modulates the responsivity of each detector. The output of each detector is an intermediate frequency (IF) signal (a product of the mixing process) whose frequency is proportional to the target range. This IF signal is continuously sampled over each period of the rf modulation. Following this, a N-channel signal processor based on field- programmable gate arrays (FPGA) calculates the discrete Fourier transform over the IF waveform in each pixel to establish the ranges to all the scatterers and their respective amplitudes. Over the past year, we constructed the fundamental building blocks of this ladar, which include a 3.5-W line illuminator, a wideband linear FM chirp modulator, a N-pixel MSM detector line array, and a N-channel FPGA signal processor. In this paper we report on the development and performance of each building block and the results of system tests conducted in the laboratory.

  17. Object Extraction Based on Evolutionary Morphological Processing

    Institute of Scientific and Technical Information of China (English)

    LI Bin; PAN Li

    2004-01-01

    This paper introduces a novel technique for object detection using genetic algorithms and morphological processing. The method employs a kind of object oriented structure element, which is derived by genetic algorithms. The population of morphological filters is iteratively evaluated according to a statistical performance index corresponding to object extraction ability, and evolves into an optimal structuring element using the evolution principles of genetic search. Experimental results of road extraction from high resolution satellite images are presented to illustrate the merit and feasibility of the proposed method.

  18. Action modulates object-based selection

    OpenAIRE

    Karina J Linnell; Humphreys, Glyn W; McIntyre, Dave B.; Laitinen, Sauli; Wing, Alan M.

    2005-01-01

    Cueing attention to one part of an object can facilitate discrimination in another part (Experiment 1 [Duncan, j. (1984). Selective attention and the organization of visual information. Journal of Experimental Psychology: General, 113, 501-517]; [Egly, R., Driver, J., and Rafal, R. D. (1994). Shifting visual attention between objects and locations: evidence from normal and parietal lesion divisions. Journal of Experimental Psychology: Human Perception and Performance, 123, 161-177]). We show ...

  19. University collections and object-based pedagogies

    OpenAIRE

    SIMPSON, Andrew; Hammond, Gina

    2012-01-01

    Engagement with objects, either directly or through digital media, has long been recognized as a viable, constructivist pedagogy, capable of mediating significant meaning and context. The increasing uptake of digital technologies in university learning and teaching programs provides a timely opportunity for integrating museum and collection data and metadata in these programs. This project looked at the use of university museum and collection objects in teaching programs through a controlled...

  20. Neurocomputational bases of object and face recognition.

    OpenAIRE

    Biederman, I; Kalocsai, P

    1997-01-01

    A number of behavioural phenomena distinguish the recognition of faces and objects, even when members of a set of objects are highly similar. Because faces have the same parts in approximately the same relations, individuation of faces typically requires specification of the metric variation in a holistic and integral representation of the facial surface. The direct mapping of a hypercolumn-like pattern of activation onto a representation layer that preserves relative spatial filter values in...

  1. Saliency-based object recognition in video

    OpenAIRE

    González-Díaz, Iván; Boujut, Hugo; Buso, Vincent; Benois-Pineau, Jenny; Domenger, Jean-Philippe

    2013-01-01

    10 pages In this paper we study the problem of object recognition in egocentric video recorded with cameras worn by persons. This task hasgained much attention during the last years, since it has turned tobe a main building block for action recognition systems in applications involving wearable cameras, such as tele-medicine or lifelogging. Under these scenarios, an action can be effectively definedas a sequence of manipulated or observed objects, so that recognition becomes a relevant stag...

  2. Contour-based object orientation estimation

    Science.gov (United States)

    Alpatov, Boris; Babayan, Pavel

    2016-04-01

    Real-time object orientation estimation is an actual problem of computer vision nowadays. In this paper we propose an approach to estimate an orientation of objects lacking axial symmetry. Proposed algorithm is intended to estimate orientation of a specific known 3D object, so 3D model is required for learning. The proposed orientation estimation algorithm consists of 2 stages: learning and estimation. Learning stage is devoted to the exploring of studied object. Using 3D model we can gather set of training images by capturing 3D model from viewpoints evenly distributed on a sphere. Sphere points distribution is made by the geosphere principle. It minimizes the training image set. Gathered training image set is used for calculating descriptors, which will be used in the estimation stage of the algorithm. The estimation stage is focusing on matching process between an observed image descriptor and the training image descriptors. The experimental research was performed using a set of images of Airbus A380. The proposed orientation estimation algorithm showed good accuracy (mean error value less than 6°) in all case studies. The real-time performance of the algorithm was also demonstrated.

  3. Interval-based Specification of Concurrent Objects

    DEFF Research Database (Denmark)

    Løvengreen, Hans Henrik; Sørensen, Morten U.

    1998-01-01

    We propose a logic for specifying the behaviour of concurrent objects, ie. concurrent entities that invoke operation of each other. The logic is an interval logic whith operation invocatins as primitive formulas. The strengths and deficiencies of the logic are illustrated by specifying a variety of...

  4. Object formation in visual working memory: Evidence from object-based attention.

    Science.gov (United States)

    Zhou, Jifan; Zhang, Haihang; Ding, Xiaowei; Shui, Rende; Shen, Mowei

    2016-09-01

    We report on how visual working memory (VWM) forms intact perceptual representations of visual objects using sub-object elements. Specifically, when objects were divided into fragments and sequentially encoded into VWM, the fragments were involuntarily integrated into objects in VWM, as evidenced by the occurrence of both positive and negative object-based attention effects: In Experiment 1, when subjects' attention was cued to a location occupied by the VWM object, the target presented at the location of that object was perceived as occurring earlier than that presented at the location of a different object. In Experiment 2, responses to a target were significantly slower when a distractor was presented at the same location as the cued object (Experiment 2). These results suggest that object fragments can be integrated into objects within VWM in a manner similar to that of visual perception. PMID:27253863

  5. Phase gradient algorithm method for three-dimensional holographic ladar imaging.

    Science.gov (United States)

    Stafford, Jason W; Duncan, Bradley D; Rabb, David J

    2016-06-10

    Three-dimensional (3D) holographic ladar uses digital holography with frequency diversity to add the ability to resolve targets in range. A key challenge is that since individual frequency samples are not recorded simultaneously, differential phase aberrations may exist between them, making it difficult to achieve range compression. We describe steps specific to this modality so that phase gradient algorithms (PGA) can be applied to 3D holographic ladar data for phase corrections across multiple temporal frequency samples. Substantial improvement of range compression is demonstrated with a laboratory experiment where our modified PGA technique is applied. Additionally, the PGA estimator is demonstrated to be efficient for this application, and the maximum entropy saturation behavior of the estimator is analytically described. PMID:27409018

  6. Bound on range precision for shot-noise limited ladar systems.

    Science.gov (United States)

    Johnson, Steven; Cain, Stephen

    2008-10-01

    The precision of ladar range measurements is limited by noise. The fundamental source of noise in a laser signal is the random time between photon arrivals. This phenomenon, called shot noise, is modeled as a Poisson random process. Other noise sources in the system are also modeled as Poisson processes. Under the Poisson-noise assumption, the Cramer-Rao lower bound (CRLB) on range measurements is derived. This bound on the variance of any unbiased range estimate is greater than the CRLB derived by assuming Gaussian noise of equal variance. Finally, it is shown that, for a ladar capable of dividing a fixed amount of energy into multiple laser pulses, the range precision is maximized when all energy is transmitted in a single pulse.

  7. Dimensionality reduction and information-theoretic divergence between sets of LADAR images

    Science.gov (United States)

    Gray, David M.; Príncipe, José C.

    2008-04-01

    This paper presents a preliminary study of information-theoretic divergence between sets of LADAR image data. This study has been motivated by the hypothesis that despite the huge dimensionality of raw image space, related images actually lie on embedded manifolds within this set of all possible images and can be represented in much lowerdimensional sub-spaces. If these low-dimensional representations can be found, information theoretic properties of the images can be exploited while circumventing many of the problems associated with the so-called "curse of dimensionality." In this study, PCA techniques are used to find a low-dimensional sub-space representation of LADAR image sets. A real LADAR image data set was collected using the AFSTAR sensor and a synthetic image data set was created using the Irma LADAR image modeling program. One unique aspect of this study is the use of an entirely synthetic data set to find a sub-space representation that is reasonably valid for both the synthetic data set and the real data set. After the sub-space representation is found, an information-theoretic density divergence measure (Cauchy- Schwarz divergence) is computed using Parzen window estimation methods to find the divergence between and among the sets of synthetic and real target classes. These divergence measures can then be used to make target classification decisions for sets of images. In practice, this technique could be used to make classification decisions on multiple images collected from a moving sensor platform or from a geographically distributed set of cooperating sensor platforms operating in a target region.

  8. A Comparative Study between Frequency-Modulated Continous Wave LADAR and Linear LiDAR

    OpenAIRE

    R. D. Massaro; Anderson, J E; Nelson, J. D.; Edwards, J D

    2014-01-01

    Topographic Light Detection and Ranging (LiDAR) technology has advanced greatly in the past decade. Pulse repetition rates of terrestrial and airborne systems havemultiplied thus vastly increasing data acquisition rates. Geiger-mode and FLASH LiDAR have also become far more mature technologies. However, a new and relatively unknown technology is maturing rapidly: Frequency-Modulated Continuous Wave Laser Detection and Ranging (FMCW-LADAR). Possessing attributes more akin to modern ra...

  9. Object Conveyance Algorithm for Multiple Mobile Robots based on Object Shape and Size

    Directory of Open Access Journals (Sweden)

    Purnomo Sejati

    2016-05-01

    Full Text Available This paper describes a determination method of a number of a team for multiple mobile robot object conveyance. The number of robot on multiple mobile robot systems is the factor of complexity on robots formation and motion control. In our previous research, we verified the use of the complex-valued neural network for controlling multiple mobile robots in object conveyance problem. Though it is a significant issue to develop effective determination team member for multiple mobile robot object conveyance, few studies have been done on it. Therefore, we propose an algorithm for determining the number of the team member on multiple mobile robot object conveyance with grasping push. The team member is determined based on object weight to obtain appropriate formation. First, the object shape and size measurement is carried out by a surveyor robot that approaches and surrounds the object. During surrounding the object, the surveyor robot measures its distance to the object and records for estimating the object shape and size. Since the object shape and size are estimated, the surveyor robot makes initial push position on the estimated push point and calls additional robots for cooperative push. The algorithm is validated in several computer simulations with varying object shape and size. As a result, the proposed algorithm is promising for minimizing the number of the robot on multiple mobile robot object conveyance.

  10. THE ADMINISTRATOR OBJECT PATTERN FOR ROLE-BASED ACCESS CONTROL

    OpenAIRE

    S. R. KODITUWAKKU

    2010-01-01

    The Object-Oriented paradigm approaches the software development by representing real world entities into classes of software objects. Object oriented design patterns facilitate small scale and large scale design reuse. This paper presents an object oriented design pattern, Administrator Object, to address the User-Role assignment problem in Role Based Access Control (RBAC). Two alternative solutions are proposed. The pattern is presented according to the Gang of Four template.

  11. THE ADMINISTRATOR OBJECT PATTERN FOR ROLE-BASED ACCESS CONTROL

    Directory of Open Access Journals (Sweden)

    S. R. KODITUWAKKU

    2010-12-01

    Full Text Available The Object-Oriented paradigm approaches the software development by representing real world entities into classes of software objects. Object oriented design patterns facilitate small scale and large scale design reuse. This paper presents an object oriented design pattern, Administrator Object, to address the User-Role assignment problem in Role Based Access Control (RBAC. Two alternative solutions are proposed. The pattern is presented according to the Gang of Four template.

  12. Tracking target objects orbiting earth using satellite-based telescopes

    Science.gov (United States)

    De Vries, Willem H; Olivier, Scot S; Pertica, Alexander J

    2014-10-14

    A system for tracking objects that are in earth orbit via a constellation or network of satellites having imaging devices is provided. An object tracking system includes a ground controller and, for each satellite in the constellation, an onboard controller. The ground controller receives ephemeris information for a target object and directs that ephemeris information be transmitted to the satellites. Each onboard controller receives ephemeris information for a target object, collects images of the target object based on the expected location of the target object at an expected time, identifies actual locations of the target object from the collected images, and identifies a next expected location at a next expected time based on the identified actual locations of the target object. The onboard controller processes the collected image to identify the actual location of the target object and transmits the actual location information to the ground controller.

  13. Surveillance Video Retrieval Based on Moving Objects Detection

    OpenAIRE

    Xuan Huang; Fernando Croquer; Wenhua Zeng

    2013-01-01

    In this article, we proposed a surveillance video retrieval method based on detection of moving objects and researched on key problems in surveillance video, such as moving objects detection, video segmentation, selection and description of key frames, and measurement of feature similarities. We detected moving objects via movement detection algorithm based on codebook, and realized automatic segmentation of surveillance video via calculating present Frame Movement Amount based on the foregro...

  14. Laser Calibration Experiment for Small Objects in Space

    Science.gov (United States)

    Campbell, Jonathan; Ayers, K.; Carreras, R.; Carruth, R.; Freestone, T.; Sharp, J.; Rawleigh, A.; Brewer, J.; Schrock, K.; Bell, L.; Howell, Joe (Technical Monitor)

    2001-01-01

    The Air Force Research Laboratory/Directed Energy Directorate (AFRL/DE) and NASA/Marshall Space Flight Center (MSFC) are looking at a series of joint laser space calibration experiments using the 12J 15Hz CO2 High Performance CO2 Ladar Surveillance Sensor (FU-CLASS) system on the 3.67 meter aperture Advanced Electro-Optics System (AEOS). The objectives of these experiments are to provide accurate range and signature measurements of calibration spheres, demonstrate high resolution tracking capability of small objects, and support NASA in technology development and tracking projects. Ancillary benefits include calibrating radar and optical sites, completing satellite conjunction analyses, supporting orbital perturbations analyses, and comparing radar and optical signatures. In the first experiment, a Global Positioning System (GPS)/laser beacon instrumented microsatellite about 25 cm in diameter will be deployed from a Space Shuttle Hitchhiker canister or other suitable launch means. Orbiting in low earth orbit, the microsatellite will pass over AEOS on the average of two times per 24-hour period. An onboard orbit propagator will activate the GPS unit and a visible laser beacon at the appropriate times. The HI-CLASS/AEOS system will detect the microsatellite as it rises above the horizon, using GPS-generated acquisition vectors. The visible laser beacon will be used to fine-tune the tracking parameters for continuous ladar data measurements throughout the pass. This operational approach should maximize visibility to the ground-based laser while allowing battery life to be conserved, thus extending the lifetime of the satellite. GPS data will be transmitted to the ground providing independent location information for the microsatellite down to sub-meter accuracies.

  15. BACKGROUND RECONSTRUCTION AND OBJECT EXTRACTION BASED ON COLOR AND OBJECT TRACKING

    Institute of Scientific and Technical Information of China (English)

    XIANG Guishan; WANG Xuanyin; LIANG Dongtai

    2006-01-01

    In YCbCr colorspace, a method is proposed to reconstruct the background and extract moving objects based on the Gaussian model of chroma components. Background model is updated according to changes of chroma components. In order to eliminate the disturbance of shadow, a shadow detecting principle is proposed in YCbCr colorspace. A Kalman filter is introduced to estimate objects' positions in the image and then the pedestrian is tracked according to its information of shape. Experiments show that the background reconstruction and updating are successful, object extraction and shadow suppression are satisfactory, and real-time and reliable tracking is realized.

  16. Perceptual Object Extraction Based on Saliency and Clustering

    Directory of Open Access Journals (Sweden)

    Qiaorong Zhang

    2010-08-01

    Full Text Available Object-based visual attention has received an increasing interest in recent years. Perceptual object is the basic attention unit of object-based visual attention. The definition and extraction of perceptual objects is one of the key technologies in object-based visual attention computation model. A novel perceptual object definition and extraction method is proposed in this paper. Based on Gestalt theory and visual feature integration theory, perceptual object is defined using homogeneity region, salient region and edges. An improved saliency map generating algorithm is employed first. Based on the saliency map, salient edges are extracted. Then graph-based clustering algorithm is introduced to get homogeneity regions in the image. Finally an integration strategy is adopted to combine salient edges and homogeneity regions to extract perceptual objects. The proposed perceptual object extraction method has been tested on lots of natural images. Experiment results and analysis are presented in this paper also. Experiment results show that the proposed method is reasonable and valid.

  17. Context based Coding of Quantized Alpha Planes for Video Objects

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Forchhammer, Søren

    2002-01-01

    In object based video, each frame is a composition of objects that are coded separately. The composition is performed through the alpha plane that represents the transparency of the object. We present an alternative to MPEG-4 for coding of alpha planes that considers their specific properties....... Comparisons in terms of rate and distortion are provided, showing that the proposed coding scheme for still alpha planes is better than the algorithms for I-frames used in MPEG-4....

  18. Extracting Moving Objects Based on Morphological Motion Filter

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    This paper presents a new approach to the extraction of a moving object from video sequence. The method is based on mor phological motion filter using connected operator and a proposed new filtering criterion. The morphological motion filter aims to detect motion which is distinct from that of the background, and thereby locates independently moving physical objects in the scenes. Experi ments show that the algorithm can extract object from moving backgrounds efficiently.

  19. A proto-object-based computational model for visual saliency.

    Science.gov (United States)

    Yanulevskaya, Victoria; Uijlings, Jasper; Geusebroek, Jan-Mark; Sebe, Nicu; Smeulders, Arnold

    2013-01-01

    State-of-the-art bottom-up saliency models often assign high saliency values at or near high-contrast edges, whereas people tend to look within the regions delineated by those edges, namely the objects. To resolve this inconsistency, in this work we estimate saliency at the level of coherent image regions. According to object-based attention theory, the human brain groups similar pixels into coherent regions, which are called proto-objects. The saliency of these proto-objects is estimated and incorporated together. As usual, attention is given to the most salient image regions. In this paper we employ state-of-the-art computer vision techniques to implement a proto-object-based model for visual attention. Particularly, a hierarchical image segmentation algorithm is used to extract proto-objects. The two most powerful ways to estimate saliency, rarity-based and contrast-based saliency, are generalized to assess the saliency at the proto-object level. The rarity-based saliency assesses if the proto-object contains rare or outstanding details. The contrast-based saliency estimates how much the proto-object differs from the surroundings. However, not all image regions with high contrast to the surroundings attract human attention. We take this into account by distinguishing between external and internal contrast-based saliency. Where the external contrast-based saliency estimates the difference between the proto-object and the rest of the image, the internal contrast-based saliency estimates the complexity of the proto-object itself. We evaluate the performance of the proposed method and its components on two challenging eye-fixation datasets (Judd, Ehinger, Durand, & Torralba, 2009; Subramanian, Katti, Sebe, Kankanhalli, & Chua, 2010). The results show the importance of rarity-based and both external and internal contrast-based saliency in fixation prediction. Moreover, the comparison with state-of-the-art computational models for visual saliency demonstrates the

  20. Content-Based Object Movie Retrieval and Relevance Feedbacks

    Directory of Open Access Journals (Sweden)

    Lee Greg C

    2007-01-01

    Full Text Available Object movie refers to a set of images captured from different perspectives around a 3D object. Object movie provides a good representation of a physical object because it can provide 3D interactive viewing effect, but does not require 3D model reconstruction. In this paper, we propose an efficient approach for content-based object movie retrieval. In order to retrieve the desired object movie from the database, we first map an object movie into the sampling of a manifold in the feature space. Two different layers of feature descriptors, dense and condensed, are designed to sample the manifold for representing object movies. Based on these descriptors, we define the dissimilarity measure between the query and the target in the object movie database. The query we considered can be either an entire object movie or simply a subset of views. We further design a relevance feedback approach to improving retrieved results. Finally, some experimental results are presented to show the efficacy of our approach.

  1. Ellipse Fitting Based Approach for Extended Object Tracking

    Directory of Open Access Journals (Sweden)

    Borui Li

    2014-01-01

    Full Text Available With the increase of sensors’ resolution, traditional object tracking technology, which ignores object’s physical extension, gradually becomes inappropriate. Extended object tracking (EOT technology is able to obtain more information about the object through jointly estimating both centroid’s dynamic state and physical extension of the object. Random matrix based approach is a promising method for EOT. It uses ellipse/ellipsoid to describe the physical extension of the object. In order to reduce the physical extension estimation error when object maneuvers, the relationship between ellipse/ellipsoid and symmetrical positive definite matrix is analyzed at first. On this basis, ellipse/ellipsoid fitting based approach (EFA for EOT is proposed based on the measurement model and centroid’s dynamic model of random matrix based EOT approach. Simulation results show that EFA is effective. The physical extension estimation error of EFA is lower than those of random matrix based approaches when object maneuvers. Besides, the estimation error of centroid’s dynamic state of EFA is also lower.

  2. A Method of Object-based De-duplication

    Directory of Open Access Journals (Sweden)

    Fang Yan

    2011-12-01

    Full Text Available Today, the world is increasingly awash in more and more unstructured data, not only because of the Internet, but also because data that used to be collected on paper or media such as film, DVDs and compact discs has moved online [1]. Most of this data is unstructured and in diverse formats such as e-mail, documents, graphics, images, and videos. In managing unstructured data complexity and scalability, object storage has a clear advantage. Object-based data de-duplication is the current most advanced method and is the effective solution for detecting duplicate data. It can detect common embedded data for the first backup across completely unrelated files and even when physical block layout changes. However, almost all of the current researches on data de-duplication do not consider the content of different file types, and they do not have any knowledge of the backup data format. It has been proven that such method cannot achieve optimal performance for compound files.In our proposed system, we will first extract objects from files, Object_IDs are then obtained by applying hash function to the objects. The resulted Object_IDs are used to build as indexing keys in B+ tree like index structure, thus, we avoid the need for a full object index, the searching time for the duplicate objects reduces to O(log n.We introduce a new concept of a duplicate object resolver. The object resolver mediates access to all the objects and is a central point for managing all the metadata and indexes for all the objects. All objects are addressable by their IDs which is unique in the universe. The resolver stores metadata with triple format. This improved metadata management strategy allows us to set, add and resolve object properties with high flexibility, and allows the repeated use of the same metadata among duplicate object.

  3. Category vs. Object Knowledge in Category-based Induction

    OpenAIRE

    Murphy, Gregory L.; Ross, Brian H.

    2010-01-01

    In one form of category-based induction, people make predictions about unknown properties of objects. There is a tension between predictions made based on the object’s specific features (e.g., objects above a certain size tend not to fly) and those made by reference to category-level knowledge (e.g., birds fly). Seven experiments with artificial categories investigated these two sources of induction by looking at whether people used information about correlated features within categories, sug...

  4. Monocular model-based 3D tracking of rigid objects

    CERN Document Server

    Lepetit, Vincent

    2014-01-01

    Many applications require tracking complex 3D objects. These include visual serving of robotic arms on specific target objects, Augmented Reality systems that require real time registration of the object to be augmented, and head tracking systems that sophisticated interfaces can use. Computer vision offers solutions that are cheap, practical and non-invasive. ""Monocular Model-Based 3D Tracking of Rigid Objects"" reviews the different techniques and approaches that have been developed by industry and research. First, important mathematical tools are introduced: camera representation, robust e

  5. A Secure and Robust Object-Based Video Authentication System

    Directory of Open Access Journals (Sweden)

    He Dajun

    2004-01-01

    Full Text Available An object-based video authentication system, which combines watermarking, error correction coding (ECC, and digital signature techniques, is presented for protecting the authenticity between video objects and their associated backgrounds. In this system, a set of angular radial transformation (ART coefficients is selected as the feature to represent the video object and the background, respectively. ECC and cryptographic hashing are applied to those selected coefficients to generate the robust authentication watermark. This content-based, semifragile watermark is then embedded into the objects frame by frame before MPEG4 coding. In watermark embedding and extraction, groups of discrete Fourier transform (DFT coefficients are randomly selected, and their energy relationships are employed to hide and extract the watermark. The experimental results demonstrate that our system is robust to MPEG4 compression, object segmentation errors, and some common object-based video processing such as object translation, rotation, and scaling while securely preventing malicious object modifications. The proposed solution can be further incorporated into public key infrastructure (PKI.

  6. A Secure and Robust Object-Based Video Authentication System

    Science.gov (United States)

    He, Dajun; Sun, Qibin; Tian, Qi

    2004-12-01

    An object-based video authentication system, which combines watermarking, error correction coding (ECC), and digital signature techniques, is presented for protecting the authenticity between video objects and their associated backgrounds. In this system, a set of angular radial transformation (ART) coefficients is selected as the feature to represent the video object and the background, respectively. ECC and cryptographic hashing are applied to those selected coefficients to generate the robust authentication watermark. This content-based, semifragile watermark is then embedded into the objects frame by frame before MPEG4 coding. In watermark embedding and extraction, groups of discrete Fourier transform (DFT) coefficients are randomly selected, and their energy relationships are employed to hide and extract the watermark. The experimental results demonstrate that our system is robust to MPEG4 compression, object segmentation errors, and some common object-based video processing such as object translation, rotation, and scaling while securely preventing malicious object modifications. The proposed solution can be further incorporated into public key infrastructure (PKI).

  7. Object-based indexing of MPEG-4 compressed video

    Science.gov (United States)

    Ferman, Ahmet M.; Gunsel, Bilge; Tekalp, A. Murat

    1997-01-01

    The MPEG-4 object-based coding standard, designed as a common platform for all multimedia applications, is inherently well-suited for video indexing applications. To fully exploit the advantages offered by MPEG-4, however, a reconsideration of existing indexing strategies is required. This paper proposes a new object-based framework for video indexing and retrieval that treats as the basic indexing unit the object itself, where changes in content are detected through observations made on the objects in the video sequence. We present a temporal segmentation algorithm that is designed to automatically extract key frames for each video object in an MPEG-4 compressed sequence based on the prediction model chosen by the encoder for individual macroblocks. An extension to the existing MPEG-4 syntax is presented for conducting and facilitating vast database searches. The data presented in the proposed 'indexing field' are: the birth and death frames of individual objects, global motion characteristics/camera operations observed in the scene, representative key frames that capture the major transformations each object undergoes, and the dominant motion characteristics of each object throughout its lifetime. We present the validity of the proposed scheme by results obtained on several MPEG-4 test sequences.

  8. Stereovision-Based Object Segmentation for Automotive Applications

    Directory of Open Access Journals (Sweden)

    Fu Shan

    2005-01-01

    Full Text Available Obstacle detection and classification in a complex urban area are highly demanding, but desirable for pedestrian protection, stop & go, and enhanced parking aids. The most difficult task for the system is to segment objects from varied and complicated background. In this paper, a novel position-based object segmentation method has been proposed to solve this problem. According to the method proposed, object segmentation is performed in two steps: in depth map ( - plane and in layered images ( - planes. The stereovision technique is used to reconstruct image points and generate the depth map. Objects are detected in the depth map. Afterwards, the original edge image is separated into different layers based on the distance of detected objects. Segmentation performed in these layered images can be easier and more reliable. It has been proved that the proposed method offers robust detection of potential obstacles and accurate measurement of their location and size.

  9. Possibility of object recognition using Altera's model based design approach

    International Nuclear Information System (INIS)

    Object recognition is an image processing task of finding a given object in a selected image or video sequence. Object recognition can be divided into two areas: one of these is decision-theoretic and deals with patterns described by quantitative descriptors, for example such as length, area, shape and texture. With this Graphical User Interface Circuitry (GUIC) methodology employed here being relatively new for object recognition systems, the aim of this work is to identify if the developed circuitry can detect certain shapes or strings within the target image. A much smaller reference image feeds the preset data for identification, tests are conducted for both binary and greyscale and the additional mathematical morphology to highlight the area within the target image with the object(s) are located is also presented. This then provides proof that basic recognition methods are valid and would allow the progression to developing decision-theoretical and learning based approaches using GUICs for use in multidisciplinary tasks.

  10. An objective prior that unifies objective Bayes and information-based inference

    CERN Document Server

    LaMont, Colin H

    2015-01-01

    There are three principle paradigms of statistical inference: (i) Bayesian, (ii) information-based and (iii) frequentist inference. We describe an objective prior (the weighting or $w$-prior) which unifies objective Bayes and information-based inference. The $w$-prior is chosen to make the marginal probability an unbiased estimator of the predictive performance of the model. This definition has several other natural interpretations. From the perspective of the information content of the prior, the $w$-prior is both uniformly and maximally uninformative. The $w$-prior can also be understood to result in a uniform density of distinguishable models in parameter space. Finally we demonstrate the the $w$-prior is equivalent to the Akaike Information Criterion (AIC) for regular models in the asymptotic limit. The $w$-prior appears to be generically applicable to statistical inference and is free of {\\it ad hoc} regularization. The mechanism for suppressing complexity is analogous to AIC: model complexity reduces mo...

  11. A new approach toward object-based change detection

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Object-based change detection has been the hotspot in remote sensing image processing.A new approach toward object-based change detection is proposed.The two different temporal images are unitedly segmented using the mean shift procedure to obtain corresponding objects.Then change detection is implemented based on the integration of corresponding objects’ intensity and texture differences.Experiments are conducted on both panchromatic images and multispectral images and the results show that the integrated measure is robust with respect to illumination changes and noise.Supplementary color detection is conducted to determine whether the color of the unchanged objects changes or not when dealing with multispectral images.Some verification work is carried out to show the accuracy of the proposed approach.

  12. Research on moving object detection based on frog's eyes

    Science.gov (United States)

    Fu, Hongwei; Li, Dongguang; Zhang, Xinyuan

    2008-12-01

    On the basis of object's information processing mechanism with frog's eyes, this paper discussed a bionic detection technology which suitable for object's information processing based on frog's vision. First, the bionics detection theory by imitating frog vision is established, it is an parallel processing mechanism which including pick-up and pretreatment of object's information, parallel separating of digital image, parallel processing, and information synthesis. The computer vision detection system is described to detect moving objects which has special color, special shape, the experiment indicates that it can scheme out the detecting result in the certain interfered background can be detected. A moving objects detection electro-model by imitating biologic vision based on frog's eyes is established, the video simulative signal is digital firstly in this system, then the digital signal is parallel separated by FPGA. IN the parallel processing, the video information can be caught, processed and displayed in the same time, the information fusion is taken by DSP HPI ports, in order to transmit the data which processed by DSP. This system can watch the bigger visual field and get higher image resolution than ordinary monitor systems. In summary, simulative experiments for edge detection of moving object with canny algorithm based on this system indicate that this system can detect the edge of moving objects in real time, the feasibility of bionic model was fully demonstrated in the engineering system, and it laid a solid foundation for the future study of detection technology by imitating biologic vision.

  13. Spanish Tourist Behaviour: A Specific Objective-base Segmantation

    OpenAIRE

    González, Pablo Rodríguez; Molina, Oscar

    2009-01-01

    This work uses data from the Spanish Tourism Demand Segments Survey (N=6900) conducted by the IESA-CSIC for Turismo Andaluz, SA. The objective of the paper is to develop a statistical segmentation or typology of Spanish tourists based on objective aspects of tourist behaviour measured in the survey including destinations visited, theme of the trip, lodging, transportation and travel group. Initial categorical data are reduced using multiple correspondence analysis and grouped through cluster ...

  14. A New RWA Algorithm Based on Multi-Objective

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    In this article, we studied the associated research problems and challenges on routing and wavelength assignment (RWA) in WDM (wavelength division multiplexing) networks. Various RWA approaches are examined and compared. We proposed a new RWA algorithm based on multi-objective. In this new algorithm, we consider multiple network optimizing objectives to setup a lightpath with maximize profit and shortest path under the limited resources. By comparing and analyzing, the proposed algorithm is much better ...

  15. Geophysics-based method of locating a stationary earth object

    Energy Technology Data Exchange (ETDEWEB)

    Daily, Michael R. (Albuquerque, NM); Rohde, Steven B. (Corrales, NM); Novak, James L. (Albuquerque, NM)

    2008-05-20

    A geophysics-based method for determining the position of a stationary earth object uses the periodic changes in the gravity vector of the earth caused by the sun- and moon-orbits. Because the local gravity field is highly irregular over a global scale, a model of local tidal accelerations can be compared to actual accelerometer measurements to determine the latitude and longitude of the stationary object.

  16. Dynamic Object Identification with SOM-based neural networks

    Directory of Open Access Journals (Sweden)

    Aleksey Averkin

    2014-03-01

    Full Text Available In this article a number of neural networks based on self-organizing maps, that can be successfully used for dynamic object identification, is described. Unique SOM-based modular neural networks with vector quantized associative memory and recurrent self-organizing maps as modules are presented. The structured algorithms of learning and operation of such SOM-based neural networks are described in details, also some experimental results and comparison with some other neural networks are given.

  17. Using Morphlet-Based Image Representation for Object Detection

    Science.gov (United States)

    Gorbatsevich, V. S.; Vizilter, Yu. V.

    2016-06-01

    In this paper, we propose an original method for objects detection based on a special tree-structured image representation - the trees of morphlets. The method provides robust detection of various types of objects in an image without employing a machine learning procedure. Along with a bounding box creation on a detection step, the method makes pre-segmentation, which can be further used for recognition purposes. Another important feature of the proposed approach is that there are no needs to use a running window as well as a features pyramid in order to detect the objects of different sizes.

  18. A General Polygon-based Deformable Model for Object Recognition

    DEFF Research Database (Denmark)

    Jensen, Rune Fisker; Carstensen, Jens Michael

    1999-01-01

    We propose a general scheme for object localization and recognition based on a deformable model. The model combines shape and image properties by warping a arbitrary prototype intensity template according to the deformation in shape. The shape deformations are constrained by a probabilistic...... distribution, which combined with a match of the warped intensity template and the image form the final criteria used for localization and recognition of a given object. The chosen representation gives the model an ability to model an almost arbitrary object. Beside the actual model a full general scheme for...

  19. A New RWA Algorithm Based on Multi-Objective

    Institute of Scientific and Technical Information of China (English)

    Qu Hua; Zhao Jihong; Li Zengzhi

    2003-01-01

    In this article , we studied the associated research problems and challenges on routing and wavelength assignment (RWA) in WDM (wavelength division multiplexing) networks. Various RWA approaches are examined and compared.We proposed a new RWA algorithm based on multi-objective. In this new algorithm, we consider multiple network optimizing objectives to setup a lightpath with maximize profit and shortest path under the limited resources. By comparing and analyzing, the pro posed algorithm is much better than the algorithms, which only consider one optimizing objective.

  20. USING MORPHLET-BASED IMAGE REPRESENTATION FOR OBJECT DETECTION

    Directory of Open Access Journals (Sweden)

    V. S. Gorbatsevich

    2016-06-01

    Full Text Available In this paper, we propose an original method for objects detection based on a special tree-structured image representation – the trees of morphlets. The method provides robust detection of various types of objects in an image without employing a machine learning procedure. Along with a bounding box creation on a detection step, the method makes pre-segmentation, which can be further used for recognition purposes. Another important feature of the proposed approach is that there are no needs to use a running window as well as a features pyramid in order to detect the objects of different sizes.

  1. A framework for Internet service evolution based on active object

    Institute of Scientific and Technical Information of China (English)

    HU Hua; ZHANG Yang

    2006-01-01

    The wide use of Internet Service in distributed computing and e-business has made the evolution of Internet Service to be one of the most prevalent research fields in software development domain. Traditional methods for software development cannot adapt to the challenge of Internet Service oriented software development. In this paper, we propose a new paradigm for the evolution of Internet Service with active objects from the characteristics of Internet Service and principles of active objects. The paradigm uses an automatic monitoring mechanism of active object to detect and process evolution requirement in system based on Internet Service.

  2. OBJECT-BASED SUPER RESOLUTION FOR INTELLIGENT VISUAL SURVEILLANCE VIDEO

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    Construction of high resolution images from low resolution sequences is often important in surveillance applications. In this letter, an affine based multi-scale block-matching image registration algorithm is first proposed. The images to be registered are divided into overlapped blocks of different size according to its motions. The Least Square (LS) image registration algorithm is extended to match the blocks. Then an object based Super Resolution (SR) scheme is designed, the Maximum A Priori (MAP) super resolution algorithm is extended to enhance the resolution of the interest objects. Experimental results show that the proposed multi-scale registration method provides more accurate registration between frames. Further more, the object based super resolution scheme shows an enhanced performance compared with the traditional MAP method.

  3. Video Based Moving Object Tracking by Particle Filter

    Directory of Open Access Journals (Sweden)

    Md. Zahidul Islam

    2009-03-01

    Full Text Available Usually, the video based object tracking deal with non-stationary image stream that changes over time. Robust and Real time moving object tracking is a problematic issue in computer vision research area. Most of the existing algorithms are able to track only inpredefined and well controlled environment. Some cases, they don’t consider non-linearity problem. In our paper, we develop such a system which considers color information, distance transform (DT based shape information and also nonlinearity. Particle filtering has been proven very successful for non-gaussian and non-linear estimation problems. We examine the difficulties of video based tracking and step by step we analyze these issues. In our firstapproach, we develop the color based particle filter tracker that relies on the deterministic search of window, whose color content matches a reference histogram model. A simple HSV histogram-based color model is used to develop this observation system. Secondly, wedescribe a new approach for moving object tracking with particle filter by shape information. The shape similarity between a template and estimated regions in the video scene is measured by their normalized cross-correlation of distance transformed images. Our observation system of particle filter is based on shape from distance transformed edge features. Template is created instantly by selecting any object from the video scene by a rectangle. Finally, inthis paper we illustrate how our system is improved by using both these two cues with non linearity.

  4. Object-based Storage Integration within the ATLAS DDM system

    CERN Document Server

    Garonne, Vincent; The ATLAS collaboration

    2016-01-01

    In this paper, we'll talk about our experiences with different data storage technologies within the ATLAS Distributed Data Management system, and in particular about object-based storage. Object-based storage differs in many points from traditional file system storage and offers a highly scalable, simple and most common storage solution for the cloud. First, we describe the needed changes in the Rucio software to integrate this technology, then we present for which use cases we have evaluated them. Finally, we conclude by reporting the results, performances and the potential future by exploiting more of their specificities and features, like metadata support.

  5. Object-based Landslide Mapping: Examples, Challenges and Opportunities

    Science.gov (United States)

    Hölbling, Daniel; Eisank, Clemens; Friedl, Barbara; Chang, Kang-Tsung; Tsai, Tsai-Tsung; Birkefeldt Møller Pedersen, Gro; Betts, Harley; Cigna, Francesca; Chiang, Shou-Hao; Aubrey Robson, Benjamin; Bianchini, Silvia; Füreder, Petra; Albrecht, Florian; Spiekermann, Raphael; Weinke, Elisabeth; Blaschke, Thomas; Phillips, Chris

    2016-04-01

    Over the last decade, object-based image analysis (OBIA) has been increasingly used for mapping landslides that occur after triggering events such as heavy rainfall. The increasing availability and quality of Earth Observation (EO) data in terms of temporal, spatial and spectral resolution allows for comprehensive mapping of landslides at multiple scales. Most often very high resolution (VHR) or high resolution (HR) optical satellite images are used in combination with a digital elevation model (DEM) and its products such as slope and curvature. Semi-automated object-based mapping makes use of various characteristics of image objects that are derived through segmentation. OBIA enables numerous spectral, spatial, contextual and textural image object properties to be applied during an analysis. This is especially useful when mapping complex natural features such as landslides and constitutes an advantage over pixel-based image analysis. However, several drawbacks in the process of object-based landslide mapping have not been overcome yet. The developed classification routines are often rather complex and limited regarding their transferability across areas and sensors. There is still more research needed to further improve present approaches and to fully exploit the capabilities of OBIA for landslide mapping. In this study several examples of object-based landslide mapping from various geographical regions with different characteristics are presented. Examples from the Austrian and Italian Alps are shown, whereby one challenge lies in the detection of small-scale landslides on steep slopes while preventing the classification of false positives with similar spectral properties (construction areas, utilized land, etc.). Further examples feature landslides mapped in Iceland, where the differentiation of landslides from other landscape-altering processes in a highly dynamic volcanic landscape poses a very distinct challenge, and in Norway, which is exposed to multiple

  6. Reactor Network Synthesis Based on Instantaneous Objective Function Characteristic Curves

    Institute of Scientific and Technical Information of China (English)

    张治山; 赵文; 王艳丽; 周传光; 袁希钢

    2003-01-01

    It is believed that whether the instantaneous objective function curves of plug-flow-reactor (PFR) and continuous-stirred-tank-reactor (CSTR) overlap or not, they have a consistent changing trend for complex reactions(steady state, isothermal and constant volume). As a result of the relation of the objective functions (selectivity or yield) to the instantaneous objective functions (instantaneous selectivity or instantaneous reaction rate), the optimal reactor network configuration can be determined according to the changing trend of the instantaneous objective function curves. Further, a recent partition strategy for the reactor network synthesis based on the instantaneous objective function characteristic curves is proposed by extending the attainable region partition strategy from the concentration space to the instantaneous objective function-unreacted fraction of key reactant space. In this paper,the instantaneous objective function is closed to be the instantaneous selectivity and several samples axe examined to illustrate the proposed method. The comparison with the previous work indicates it is a very convenient and practical systematic tool of the reactor network synthesis and seems also promising for overcoming the dimension limit of the attainable region partition strategy in the concentration space.

  7. Modeling of Heterogeneous Objects: An Approach Based on Implicit Functions

    Directory of Open Access Journals (Sweden)

    Miller Gómez-Mora

    2016-02-01

    Full Text Available Modeling objects, their properties and relations is an important topic in computer science. In this sense, this research contributes to the framework of heterogeneous solid modeling, as well as the popular and intricate study of implicit solid representation. The approach presented here is broad and generic, but this article will focus on bio-CAD models, alluding to the existing extension and implementation in other fields. The overall aim of this work is to demonstrate that solid models of heterogeneous object can be built implicitly. This is shown to have promise in practical applications from biomedical computing to computer animation and engineering. The approach adopted here is based on the observation that current solid models cannot intrinsically represent multiphase geometric information along with the attribute information. This makes necessary to explore new modeling techniques in order to represent real-world objects. The availability of such modeling techniques remains central to the design, analysis, and fabrication of heterogeneous objects

  8. Concurrent Object-Oriented Programming Based on MPI

    Institute of Scientific and Technical Information of China (English)

    鲁宏伟; 汪厚祥; 裴晓黎; 肖永玲

    2004-01-01

    Object-oriented model possesses inherent concurrency. Integration of concurrency and object-orientation is a promising new field. MPI is a message-passing standard and has been adopted by more and more systems. This paper proposes a novel approach to realize concurrent object-oriented programming based on Message-passing interface(MPI) in which future method communication is adopted between concurrent objects. A state behavior set is proposed to solve inheritance anomaly, and a bounded buffer is taken as an example to illustrate this proposal. The definition of ParaMPI class, which is the most important class in the concurrent class library,and implementation issues are briefly described.

  9. Research on Virtual Object Tele-operation Based on Gesture

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    A tele-operation method of virtual environment based on gesture is presented.Firstly,the design block diagram and the information flow of the virtual environment tele-operation simulation system are given.Secondly,the coordination transformation between virtual gesture and the tele-operated aircraft is presented.Finally,a tele-operation simulation system based on gesture is developed.And the simulation results demonstrate that there is more consistency between the virtual gesture and the moving object.

  10. A Learning Object Approach To Evidence based learning

    OpenAIRE

    Zabin Visram; Bruce Elson; Patricia Reynolds

    2005-01-01

    This paper describes the philosophy, development and framework of the body of elements formulated to provide an approach to evidence-based learning sustained by Learning Objects and web based technology Due to the demands for continuous improvement in the delivery of healthcare and in the continuous endeavour to improve the quality of life, there is a continuous need for practitioner's to update their knowledge by accomplishing accredited courses. The rapid advances in medical science has mea...

  11. Archive Design Based on Planets Inspired Logical Object Model

    DEFF Research Database (Denmark)

    Zierau, Eld; Johansen, Anders

    2008-01-01

    We describe a proposal for a logical data model based on preliminary work the Planets project In OAIS terms the main areas discussed are related to the introduction of a logical data model for representing the past, present and future versions of the digital object associated with the Archival...

  12. Vision-based autonomous grasping of unknown piled objects

    International Nuclear Information System (INIS)

    Computer vision techniques have been used to develop a vision-based grasping capability for autonomously picking and placing unknown piled objects. This work is currently being applied to the problem of hazardous waste sorting in support of the Department of Energy's Mixed Waste Operations Program

  13. Object-oriented vision for a behavior-based robot

    Science.gov (United States)

    Bischoff, Rainer; Graefe, Volker; Wershofen, Klaus P.

    1996-10-01

    As one realization out of the class of behavior-based robot architectures a specific concept of situation-oriented behavior-based navigation has been proposed. Its main characteristic is that the selection of the behaviors to be executed in each moment is based on a continuous recognition and evaluation of the dynamically changing situation in which the robot is finding itself. An important prerequisite for such as approach is a timely and comprehensive perception of the robot's dynamically changing environment. Object-oriented vision as proposed and successfully applied, e.g., in freeway traffic scenes is a particularly well suited sensing modality for robot control. Our work concentrated on modeling the physical objects which are relevant for indoor navigation, i.e. walls, intersections of corridors, and landmarks. In the interest of efficiency these models include only those necessary features for allowing the robot to reliably recognize different situations in real time. According to the concept of object- oriented vision recognizing such objects is largely reduced to a knowledge-based verification of objects or features that may be expected to be visible in the current situation. The following results have been achieved: 1) By using its vision system and a knowledge base in the form of an attributed topological map the robot could orient itself and navigate autonomously in a known environment. 2) In an unknown environment the robot was able to build, by means of supervised learning, an attributed topological map as a basis for subsequent autonomous navigation. 3) The experiments could be performed both under unmodified artificial light and under natural light shining through the glass walls of the building.

  14. Observed bodies generate object-based spatial codes.

    Science.gov (United States)

    Taylor, Alison; Flynn, Maria; Edmonds, Caroline J; Gardner, Mark R

    2016-09-01

    Contemporary studies of spatial and social cognition frequently use human figures as stimuli. The interpretation of such studies may be complicated by spatial compatibility effects that emerge when researchers employ spatial responses, and participants spontaneously code spatial relationships about an observed body. Yet, the nature of these spatial codes - whether they are location- or object-based, and coded from the perspective of the observer or the figure - has not been determined. Here, we investigated this issue by exploring spatial compatibility effects arising for objects held by a visually presented whole-bodied schematic human figure. In three experiments, participants responded to the colour of the object held in the figure's left or right hand, using left or right key presses. Left-right compatibility effects were found relative to the participant's egocentric perspective, rather than the figure's. These effects occurred even when the figure was rotated by 90° to the left or to the right, and the coloured objects were aligned with the participant's midline. These findings are consistent with spontaneous spatial coding from the participant's perspective and relative to the normal upright orientation of the body. This evidence for object-based spatial coding implies that the domain general cognitive mechanisms that result in spatial compatibility effects may contribute to certain spatial perspective-taking and social cognition phenomena. PMID:27235754

  15. Fuzzy Distance-Based Range Queries over Uncertain Moving Objects

    Institute of Scientific and Technical Information of China (English)

    Yi-Fei Chen; Xiao-Lin Qin; Liang Liu; Bo-Han Li

    2012-01-01

    Data obtained from real world are imprecise or uncertain due to the accuracy of positioning devices,updating protocols or characteristics of applications.On the other hand,users sometimes prefer to qualitatively express their requests with vague conditions and different parts of search region are in-equally important in some applications.We address the problem of efficiently processing the fuzzy range queries for uncertain moving objects whose whereabouts in time are not known exactly,for which the basic syntax is find objects always/sometimes near to the query issuer with the qualifying guarantees no less than a given threshold during a given temporal interval.We model the location uncertainty of moving objects on the utilization of probability density functions and describe the indeterminate boundary of query range with fuzzy set.We present the qualifying guarantee evaluation of objects,and propose pruning techniques based on the α-cut of fuzzy set to shrink the search space efficiently.We also design rules to reject non-qualifying objects and validate qualifying objects in order to avoid unnecessary costly numeric integrations in the refinement step.An extensive empirical study has been conducted to demonstrate the efficiency and effectiveness of algorithms under various experimental settings.

  16. Object-Based Classification and Change Detection of Hokkaido, Japan

    Science.gov (United States)

    Park, J. G.; Harada, I.; Kwak, Y.

    2016-06-01

    Topography and geology are factors to characterize the distribution of natural vegetation. Topographic contour is particularly influential on the living conditions of plants such as soil moisture, sunlight, and windiness. Vegetation associations having similar characteristics are present in locations having similar topographic conditions unless natural disturbances such as landslides and forest fires or artificial disturbances such as deforestation and man-made plantation bring about changes in such conditions. We developed a vegetation map of Japan using an object-based segmentation approach with topographic information (elevation, slope, slope direction) that is closely related to the distribution of vegetation. The results found that the object-based classification is more effective to produce a vegetation map than the pixel-based classification.

  17. Reconstructed key frame and object motion based video retrieval

    Science.gov (United States)

    Hu, Shuangyan; Li, Junshan; Li, Kun; Wang, Rui; Yang, Weijun

    2007-11-01

    This paper proposes a video retrieval scheme which can retrieve desired video clips from video databases using color and object motion. The retrieval method includes two steps. In the first step, get the Intra picture frames (I-frames) set from the query MPEG video and reconstruct the key frame of the video based on the set. Then, the video retrieval equals to the retrieval of the reconstructed key frame(R-key frame) and can be easily performed according the methods of content based image retrieval. The second step, the local object motion information that is local motion vector field, is extracted from the video clips set which is the result of the first step, and the final similarity of videos is measured based on the constructed directional histogram. Experimental results show that the proposed two-step retrieval method performed excellently for video retrieval.

  18. Knowledge-Based Object Detection in Laser Scanning Point Clouds

    Science.gov (United States)

    Boochs, F.; Karmacharya, A.; Marbs, A.

    2012-07-01

    Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human expert knowledge about the scene, the objects inside, and their representation by the data and the behavior of algorithms to the machine. This "understanding" enables the machine to assist human interpretation of the scene inside the point cloud. Furthermore, it allows the machine to understand possibilities and limitations of algorithms and to take this into account within the processing chain. This not only assists the researchers in defining optimal processing steps, but also provides suggestions when certain changes or new details emerge from the point cloud. Our approach benefits from the advancement in knowledge technologies within the Semantic Web framework. This advancement has provided a strong base for applications based on knowledge management. In the article we will present and describe the knowledge technologies used for our approach such as Web Ontology Language (OWL), used for formulating the knowledge base and the Semantic Web Rule Language (SWRL) with 3D processing and topologic built-ins, aiming to combine geometrical analysis of 3D point clouds, and specialists' knowledge of the scene and algorithmic processing.

  19. Agent-based Algorithm for Spatial Distribution of Objects

    KAUST Repository

    Collier, Nathan

    2012-06-02

    In this paper we present an agent-based algorithm for the spatial distribution of objects. The algorithm is a generalization of the bubble mesh algorithm, initially created for the point insertion stage of the meshing process of the finite element method. The bubble mesh algorithm treats objects in space as bubbles, which repel and attract each other. The dynamics of each bubble are approximated by solving a series of ordinary differential equations. We present numerical results for a meshing application as well as a graph visualization application.

  20. A Method of Object-based De-duplication

    OpenAIRE

    Fang Yan; YuAn Tan

    2011-01-01

    Today, the world is increasingly awash in more and more unstructured data, not only because of the Internet, but also because data that used to be collected on paper or media such as film, DVDs and compact discs has moved online [1]. Most of this data is unstructured and in diverse formats such as e-mail, documents, graphics, images, and videos. In managing unstructured data complexity and scalability, object storage has a clear advantage. Object-based data de-duplication is the current most ...

  1. Rules-based object-relational databases ontology construction

    Institute of Scientific and Technical Information of China (English)

    Chen Jia; Wu Yue

    2009-01-01

    To solve the problems of sharing and reusing information in the information system, a rules-based ontology constructing approach from object-relational databases is proposed. A 3-tuple ontology constructing model is proposed first. Then, four types of ontology constructing rules including class, property, property characteristics, and property restrictions axe formalized affording to the model. Experiment results described in Web ontology language prove that our proposed approach is feasible for applying in the semantic objects project of semantic computing laboratory in UC Irvine. Our approach reduces about twenty percent constructing time compared with the ontology construction from relational databases.

  2. Features Extraction for Object Detection Based on Interest Point

    Directory of Open Access Journals (Sweden)

    Amin Mohamed Ahsan

    2013-05-01

    Full Text Available In computer vision, object detection is an essential process for further processes such as object tracking, analyzing and so on. In the same context, extraction features play important role to detect the object correctly. In this paper we present a method to extract local features based on interest point which is used to detect key-points within an image, then, compute histogram of gradient (HOG for the region surround that point. Proposed method used speed-up robust feature (SURF method as interest point detector and exclude the descriptor. The new descriptor is computed by using HOG method. The proposed method got advantages of both mentioned methods. To evaluate the proposed method, we used well-known dataset which is Caltech101. The initial result is encouraging in spite of using a small data for training.

  3. Performance Evaluation of Java Based Object Relational Mapping Tools

    Directory of Open Access Journals (Sweden)

    Shoaib Mahmood Bhatti

    2013-04-01

    Full Text Available Object persistency is the hot issue in the form of ORM (Object Relational Mapping tools in industry as developers use these tools during software development. This paper presents the performance evaluation of Java based ORM tools. For this purpose, Hibernate, Ebean and TopLinkhave been selected as the ORM tools which are popular and open source. Their performance has been measured from execution point of view. The results show that ORM tools are the good option for the developers considering the system throughput in shorter setbacks and they can be used efficiently and effectively for performing mapping of the objects into the relational dominated world of database, thus creating a hope for a better and well dominated future of this technology.

  4. Nanoscale synthesis and characterization of graphene-based objects

    Directory of Open Access Journals (Sweden)

    Daisuke Fujita

    2011-01-01

    Full Text Available Graphene-based nano-objects such as nanotrenches, nanowires, nanobelts and nanoscale superstructures have been grown by surface segregation and precipitation on carbon-doped mono- and polycrystalline nickel substrates in ultrahigh vacuum. The dominant morphologies of the nano-objects were nanowire and nanosheet. Nucleation of graphene sheets occurred at surface defects such as step edges and resulted in the directional growth of nanowires. Surface analysis by scanning tunneling microscopy (STM has clarified the structure and functionality of the novel nano-objects at atomic resolution. Nanobelts were detected consisting of bilayer graphene sheets with a nanoscale width and a length of several microns. Moiré patterns and one-dimensional reconstruction were observed on multilayer graphite terraces. As a useful functionality, application to repairable high-resolution STM probes is demonstrated.

  5. Likelihood-based CT reconstruction of objects containing known components

    Energy Technology Data Exchange (ETDEWEB)

    Stayman, J. Webster [Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Biomedical Engineering; Otake, Yoshito; Uneri, Ali; Prince, Jerry L.; Siewerdsen, Jeffrey H.

    2011-07-01

    There are many situations in medical imaging where there are known components within the imaging volume. Such is the case in diagnostic X-ray CT imaging of patients with implants, in intraoperative CT imaging where there may be surgical tools in the field, or in situations where the patient support (table or frame) or other devices are outside the (truncated) reconstruction FOV. In such scenarios it is often of great interest to image the relation between the known component and the surrounding anatomy, or to provide high-quality images at the boundary of these objects, or simply to minimize artifacts arising from such components. We propose a framework for simultaneously estimating the position and orientation of a known component and the surrounding volume. Toward this end, we adopt a likelihood-based objective function with an image volume jointly parameterized by a known object, or objects, with unknown registration parameters and an unknown background attenuation volume. The objective is solved iteratively using an alternating minimization approach between the two parameter types. Because this model integrates a substantial amount of prior knowledge about the overall volume, we expect a number of advantages including the reduction of metal artifacts, potential for more sparse data acquisition (decreased time and dose), and/or improved image quality. We illustrate this approach using simulated spine CT data that contains pedicle screws placed in a vertebra, and demonstrate improved performance over traditional filtered-backprojection and penalized-likelihood reconstruction techniques. (orig.)

  6. Density-based clustering method in the moving object database

    Institute of Scientific and Technical Information of China (English)

    ZHOU Xing; XIANG Shu; GE Jun-wei; LIU Zhao-hong; BAE Hae-young

    2004-01-01

    With the rapid advance of wireless communication, tracking the positions of the moving objects is becoming increasingly feasible and necessary. Because a large number of people use mobile phones, we must handle a large moving object database as well as the following problems. How can we provide the customers with high quality service, that means, how can we deal with so many enquiries within as less time as possible? Because of the large number of data, the gap between CPU speed and the size of main memory has increasing considerably. One way to reduce the time to handle enquiries is to reduce the I/O number between the buffer and the secondary storage. An effective clustering of the objects can minimize the I/O-cost between them. In this paper, according to the characteristic of the moving object database, we analyze the objects in buffer, according to their mappings in the two-dimension coordinate, and then develop a density-based clustering method to effectively reorganize the clusters. This new mechanism leads to the less cost of the I/O operation and the more efficient response to enquiries.

  7. A Learning Object Approach To Evidence based learning

    Directory of Open Access Journals (Sweden)

    Zabin Visram

    2005-06-01

    Full Text Available This paper describes the philosophy, development and framework of the body of elements formulated to provide an approach to evidence-based learning sustained by Learning Objects and web based technology Due to the demands for continuous improvement in the delivery of healthcare and in the continuous endeavour to improve the quality of life, there is a continuous need for practitioner's to update their knowledge by accomplishing accredited courses. The rapid advances in medical science has meant increasingly, there is a desperate need to adopt wireless schemes, whereby bespoke courses can be developed to help practitioners keep up with expanding knowledge base. Evidently, without current best evidence, practice risks becoming rapidly out of date, to the detriment of the patient. There is a need to provide a tactical, operational and effective environment, which allows professional to update their education, and complete specialised training, just-in-time, in their own time and location. Following this demand in the marketplace the information engineering group, in combination with several medical and dental schools, set out to develop and design a conceptual framework which form the basis of pioneering research, which at last, enables practitioner's to adopt a philosophy of life long learning. The body and structure of this framework is subsumed under the term Object oriented approach to Evidence Based learning, Just-in-time, via Internet sustained by Reusable Learning Objects (The OEBJIRLO Progression. The technical pillars which permit this concept of life long learning are pivoted by the foundations of object oriented technology, Learning objects, Just-in-time education, Data Mining, intelligent Agent technology, Flash interconnectivity and remote wireless technology, which allow practitioners to update their professional skills, complete specialised training which leads to accredited qualifications. This paper sets out to develop and

  8. Moving object detection in aerial video based on spatiotemporal saliency

    Institute of Scientific and Technical Information of China (English)

    Shen Hao; Li Shuxiao; Zhu Chengfei; Chang Hongxing; Zhang Jinglan

    2013-01-01

    In this paper, the problem of moving object detection in aerial video is addressed. While motion cues have been extensively exploited in the literature, how to use spatial information is still an open problem. To deal with this issue, we propose a novel hierarchical moving target detection method based on spatiotemporal saliency. Temporal saliency is used to get a coarse segmentation, and spatial saliency is extracted to obtain the object’s appearance details in candidate motion regions. Finally, by combining temporal and spatial saliency information, we can get refined detec-tion results. Additionally, in order to give a full description of the object distribution, spatial sal-iency is detected in both pixel and region levels based on local contrast. Experiments conducted on the VIVID dataset show that the proposed method is efficient and accurate.

  9. Data Warehouse Requirements Analysis Framework: Business-Object Based Approach

    Directory of Open Access Journals (Sweden)

    Anirban Sarkar

    2012-01-01

    Full Text Available Detailed requirements analysis plays a key role towards the design of successful Data Warehouse (DW system. The requirements analysis specifications are used as the prime input for the construction of conceptual level multidimensional data model. This paper has proposed a Business Object based requirements analysis framework for DW system which is supported with abstraction mechanism and reuse capability. It also facilitate the stepwise mapping of requirements descriptions into high level design components of graph semantic based conceptual level object oriented multidimensional data model. The proposed framework starts with the identification of the analytical requirements using business process driven approach and finally refine the requirements in further detail to map into the conceptual level DW design model using either Demand-driven of Mixed-driven approach for DW requirements analysi

  10. Depth-Based Object Tracking Using a Robust Gaussian Filter

    OpenAIRE

    Issac, Jan; Wüthrich, Manuel; Cifuentes, Cristina Garcia; Bohg, Jeannette; Trimpe, Sebastian; Schaal, Stefan

    2016-01-01

    We consider the problem of model-based 3D-tracking of objects given dense depth images as input. Two difficulties preclude the application of a standard Gaussian filter to this problem. First of all, depth sensors are characterized by fat-tailed measurement noise. To address this issue, we show how a recently published robustification method for Gaussian filters can be applied to the problem at hand. Thereby, we avoid using heuristic outlier detection methods that simply reject measurements i...

  11. Logical Object as a Basis of Knowledge Based Systems

    Institute of Scientific and Technical Information of China (English)

    徐殿祥; 郑国梁

    1995-01-01

    This paper presents a framework called logical knowledge object (LKO),which is taken as a basis of the dependable development of knowledge based systems(KBSs).LKO combines logic programming and object-oriented programming paradigms,where objects are viewed as abstractions with states,constraints,behaviors and inheritance.The operational semantics defined in the style of natural semantics is simple and clear.A hybrid knowledge representation amalgamating rule,frame,semantic network and blackboard is available for both most structured and flat knowledge.The management of knowledge bases has been formally specified.Accordingly,LKO is well suited for the formal representation of knowledge and requirements of KBSs.Based on the framework,verification techniques are also explored to enhance the analysis of requirement specifications and the validation of KBSs.In addition,LKO provides a methodology for the development of KBSs,applying the concepts of rapid prototyping and top-down design to deal with changing and incomplete requirements,and to provide multiple abstract models of the domain,where formal methods might be used at each abstract level.

  12. WOMBAT: sWift Objects for Mhd BAsed on Tvd

    Science.gov (United States)

    Mendygral, Peter; Porter, David; Edmon, Paul; Delgado, Jennifer

    2012-04-01

    WOMBAT (sWift Objects for Mhd BAsed on Tvd) is an astrophysical fluid code that is an implementation of a non-relativistic MHD TVD scheme; an extension for relativistic MHD has been added. The code operates on 1, 2, and 3D Eulerian meshes (cartesian and cylindrical coordinates) with magnetic field divergence restriction controlled by a constrained transport (CT) scheme. The user can tune code performance to a given processor based on chip cache sizes. Proper settings yield significant speed-ups due to efficient cache reuse.

  13. Multi-objective community detection based on memetic algorithm.

    Directory of Open Access Journals (Sweden)

    Peng Wu

    Full Text Available Community detection has drawn a lot of attention as it can provide invaluable help in understanding the function and visualizing the structure of networks. Since single objective optimization methods have intrinsic drawbacks to identifying multiple significant community structures, some methods formulate the community detection as multi-objective problems and adopt population-based evolutionary algorithms to obtain multiple community structures. Evolutionary algorithms have strong global search ability, but have difficulty in locating local optima efficiently. In this study, in order to identify multiple significant community structures more effectively, a multi-objective memetic algorithm for community detection is proposed by combining multi-objective evolutionary algorithm with a local search procedure. The local search procedure is designed by addressing three issues. Firstly, nondominated solutions generated by evolutionary operations and solutions in dominant population are set as initial individuals for local search procedure. Then, a new direction vector named as pseudonormal vector is proposed to integrate two objective functions together to form a fitness function. Finally, a network specific local search strategy based on label propagation rule is expanded to search the local optimal solutions efficiently. The extensive experiments on both artificial and real-world networks evaluate the proposed method from three aspects. Firstly, experiments on influence of local search procedure demonstrate that the local search procedure can speed up the convergence to better partitions and make the algorithm more stable. Secondly, comparisons with a set of classic community detection methods illustrate the proposed method can find single partitions effectively. Finally, the method is applied to identify hierarchical structures of networks which are beneficial for analyzing networks in multi-resolution levels.

  14. Multiple-input multiple-output synthetic aperture ladar system for wide-range swath with high azimuth resolution.

    Science.gov (United States)

    Tang, Yu; Qin, Bao; Yan, Yun; Xing, Mengdao

    2016-02-20

    For the trade-off between the high azimuth resolution and the wide-range swath in the single-input single-output synthetic aperture ladar (SAL) system, the range swath of the SAL system is restricted to a narrow range, this paper proposes a multiple-input multiple-output (MIMO) synthetic aperture ladar system. The MIMO system adopts a low pulse repetition frequency (PRF) to avoid a range ambiguity for the wide-range swath and in azimuth adopts the multi-channel method to achieve azimuth high resolution from the unambiguous azimuth wide-spectrum signal, processed through adaptive digital beam-forming technology. Simulations and analytical results are presented. PMID:26906593

  15. Multiple-input multiple-output synthetic aperture ladar system for wide-range swath with high azimuth resolution.

    Science.gov (United States)

    Tang, Yu; Qin, Bao; Yan, Yun; Xing, Mengdao

    2016-02-20

    For the trade-off between the high azimuth resolution and the wide-range swath in the single-input single-output synthetic aperture ladar (SAL) system, the range swath of the SAL system is restricted to a narrow range, this paper proposes a multiple-input multiple-output (MIMO) synthetic aperture ladar system. The MIMO system adopts a low pulse repetition frequency (PRF) to avoid a range ambiguity for the wide-range swath and in azimuth adopts the multi-channel method to achieve azimuth high resolution from the unambiguous azimuth wide-spectrum signal, processed through adaptive digital beam-forming technology. Simulations and analytical results are presented.

  16. Corner Sort for Pareto-Based Many-Objective Optimization.

    Science.gov (United States)

    Wang, Handing; Yao, Xin

    2014-01-01

    Nondominated sorting plays an important role in Pareto-based multiobjective evolutionary algorithms (MOEAs). When faced with many-objective optimization problems multiobjective optimization problems (MOPs) with more than three objectives, the number of comparisons needed in nondominated sorting becomes very large. In view of this, a new corner sort is proposed in this paper. Corner sort first adopts a fast and simple method to obtain a nondominated solution from the corner solutions, and then uses the nondominated solution to ignore the solutions dominated by it to save comparisons. Obtaining the nondominated solutions requires much fewer objective comparisons in corner sort. In order to evaluate its performance, several state-of-the-art nondominated sorts are compared with our corner sort on three kinds of artificial solution sets of MOPs and the solution sets generated from MOEAs on benchmark problems. On one hand, the experiments on artificial solution sets show the performance on the solution sets with different distributions. On the other hand, the experiments on the solution sets generated from MOEAs show the influence that different sorts bring to MOEAs. The results show that corner sort performs well, especially on many-objective optimization problems. Corner sort uses fewer comparisons than others.

  17. Low-power portable scanning imaging ladar system

    Science.gov (United States)

    Pyburn, Dana; Leon, Roberto; Haji-Saeed, B.; Sengupta, Sandip K.; Testorf, Markus; Kierstead, John; Khoury, Jehad; Woods, Charles L.; Lorenzo, Joseph

    2003-08-01

    We propose and are in the process of progressively implementing an improved architecture for a laser based system to acquire intensity and range images of hard targets in real-time. The system design emphasizes the use of low power laser sources in conjunction with optical preamplification of target return signals to maintain eye safety without incurring the associated performance penalty. The design leverages advanced fiber optic component technology developed for the commercial market to achieve compactness and low power consumption without the high costs and long lead times associated with custom military devices. All important system parameters are designed to be configured in the field, by the user, in software, allowing for adaptive reconfiguration for different missions and targets. Recently we have started our transition from the initial test bed, using a laser in the visible wavelength, into the final system with a 1550nm diode laser. Currently we are able to acquire and display 3-D false-color and gray-scale images, in the laboratory, at moderate frame rates in real-time. Commercial off-the-shelf data acquisition and signal processing software on a desktop computer equipped with commercial acquisition hardware is utilized. Significant improvements in both range and spatial resolution are expected in the near future.

  18. AN OBJECT-BASED METHOD FOR CHINESE LANDFORM TYPES CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    H. Ding

    2016-06-01

    Full Text Available Landform classification is a necessary task for various fields of landscape and regional planning, for example for landscape evaluation, erosion studies, hazard prediction, et al. This study proposes an improved object-based classification for Chinese landform types using the factor importance analysis of random forest and the gray-level co-occurrence matrix (GLCM. In this research, based on 1km DEM of China, the combination of the terrain factors extracted from DEM are selected by correlation analysis and Sheffield's entropy method. Random forest classification tree is applied to evaluate the importance of the terrain factors, which are used as multi-scale segmentation thresholds. Then the GLCM is conducted for the knowledge base of classification. The classification result was checked by using the 1:4,000,000 Chinese Geomorphological Map as reference. And the overall classification accuracy of the proposed method is 5.7% higher than ISODATA unsupervised classification, and 15.7% higher than the traditional object-based classification method.

  19. An Object-Based Method for Chinese Landform Types Classification

    Science.gov (United States)

    Ding, Hu; Tao, Fei; Zhao, Wufan; Na, Jiaming; Tang, Guo'an

    2016-06-01

    Landform classification is a necessary task for various fields of landscape and regional planning, for example for landscape evaluation, erosion studies, hazard prediction, et al. This study proposes an improved object-based classification for Chinese landform types using the factor importance analysis of random forest and the gray-level co-occurrence matrix (GLCM). In this research, based on 1km DEM of China, the combination of the terrain factors extracted from DEM are selected by correlation analysis and Sheffield's entropy method. Random forest classification tree is applied to evaluate the importance of the terrain factors, which are used as multi-scale segmentation thresholds. Then the GLCM is conducted for the knowledge base of classification. The classification result was checked by using the 1:4,000,000 Chinese Geomorphological Map as reference. And the overall classification accuracy of the proposed method is 5.7% higher than ISODATA unsupervised classification, and 15.7% higher than the traditional object-based classification method.

  20. Code Based Analysis for Object-Oriented Systems

    Institute of Scientific and Technical Information of China (English)

    Swapan Bhattacharya; Ananya Kanjilal

    2006-01-01

    The basic features of object-oriented software makes it difficult to apply traditional testing methods in objectoriented systems. Control Flow Graph (CFG) is a well-known model used for identification of independent paths in procedural software. This paper highlights the problem of constructing CFG in object-oriented systems and proposes a new model named Extended Control Flow Graph (ECFG) for code based analysis of Object-Oriented (OO) software. ECFG is a layered CFG where nodes refer to methods rather than statements. A new metrics - Extended Cyclomatic Complexity (E-CC) is developed which is analogous to McCabe's Cyclomatic Complexity (CC) and refers to the number of independent execution paths within the OO software. The different ways in which CFG's of individual methods are connected in an ECFG are presented and formulas for E-CC for these different cases are proposed. Finally we have considered an example in Java and based on its ECFG, applied these cases to arrive at the E-CC of the total system as well as proposed a methodology for calculating the basis set, i.e., the set of independent paths for the OO system that will help in creation of test cases for code testing.

  1. Object Recognition using Feature- and Color-Based Methods

    Science.gov (United States)

    Duong, Tuan; Duong, Vu; Stubberud, Allen

    2008-01-01

    An improved adaptive method of processing image data in an artificial neural network has been developed to enable automated, real-time recognition of possibly moving objects under changing (including suddenly changing) conditions of illumination and perspective. The method involves a combination of two prior object-recognition methods one based on adaptive detection of shape features and one based on adaptive color segmentation to enable recognition in situations in which either prior method by itself may be inadequate. The chosen prior feature-based method is known as adaptive principal-component analysis (APCA); the chosen prior color-based method is known as adaptive color segmentation (ACOSE). These methods are made to interact with each other in a closed-loop system to obtain an optimal solution of the object-recognition problem in a dynamic environment. One of the results of the interaction is to increase, beyond what would otherwise be possible, the accuracy of the determination of a region of interest (containing an object that one seeks to recognize) within an image. Another result is to provide a minimized adaptive step that can be used to update the results obtained by the two component methods when changes of color and apparent shape occur. The net effect is to enable the neural network to update its recognition output and improve its recognition capability via an adaptive learning sequence. In principle, the improved method could readily be implemented in integrated circuitry to make a compact, low-power, real-time object-recognition system. It has been proposed to demonstrate the feasibility of such a system by integrating a 256-by-256 active-pixel sensor with APCA, ACOSE, and neural processing circuitry on a single chip. It has been estimated that such a system on a chip would have a volume no larger than a few cubic centimeters, could operate at a rate as high as 1,000 frames per second, and would consume in the order of milliwatts of power.

  2. R2-Based Multi/Many-Objective Particle Swarm Optimization

    Science.gov (United States)

    Toscano, Gregorio; Barron-Zambrano, Jose Hugo; Tello-Leal, Edgar

    2016-01-01

    We propose to couple the R2 performance measure and Particle Swarm Optimization in order to handle multi/many-objective problems. Our proposal shows that through a well-designed interaction process we could maintain the metaheuristic almost inalterable and through the R2 performance measure we did not use neither an external archive nor Pareto dominance to guide the search. The proposed approach is validated using several test problems and performance measures commonly adopted in the specialized literature. Results indicate that the proposed algorithm produces results that are competitive with respect to those obtained by four well-known MOEAs. Additionally, we validate our proposal in many-objective optimization problems. In these problems, our approach showed its main strength, since it could outperform another well-known indicator-based MOEA. PMID:27656200

  3. R2-Based Multi/Many-Objective Particle Swarm Optimization

    Science.gov (United States)

    Toscano, Gregorio; Barron-Zambrano, Jose Hugo; Tello-Leal, Edgar

    2016-01-01

    We propose to couple the R2 performance measure and Particle Swarm Optimization in order to handle multi/many-objective problems. Our proposal shows that through a well-designed interaction process we could maintain the metaheuristic almost inalterable and through the R2 performance measure we did not use neither an external archive nor Pareto dominance to guide the search. The proposed approach is validated using several test problems and performance measures commonly adopted in the specialized literature. Results indicate that the proposed algorithm produces results that are competitive with respect to those obtained by four well-known MOEAs. Additionally, we validate our proposal in many-objective optimization problems. In these problems, our approach showed its main strength, since it could outperform another well-known indicator-based MOEA.

  4. Multiview-Based Cooperative Tracking of Multiple Human Objects

    Directory of Open Access Journals (Sweden)

    Lien Kuo-Chin

    2008-01-01

    Full Text Available Abstract Human tracking is a popular research topic in computer vision. However, occlusion problem often complicates the tracking process. This paper presents the so-called multiview-based cooperative tracking of multiple human objects based on the homographic relation between different views. This cooperative tracking applies two hidden Markov processes (tracking and occlusion processes for each target in each view. The tracking process locates the moving target in each view, whereas the occlusion process represents the possible visibility of the specific target in that designated view. Based on the occlusion process, the cooperative tracking process may reallocate tracking resources for different trackers in different views. Experimental results show the efficiency of the proposed method.

  5. Multiview-Based Cooperative Tracking of Multiple Human Objects

    Directory of Open Access Journals (Sweden)

    Kuo-Chin Lien

    2008-03-01

    Full Text Available Human tracking is a popular research topic in computer vision. However, occlusion problem often complicates the tracking process. This paper presents the so-called multiview-based cooperative tracking of multiple human objects based on the homographic relation between different views. This cooperative tracking applies two hidden Markov processes (tracking and occlusion processes for each target in each view. The tracking process locates the moving target in each view, whereas the occlusion process represents the possible visibility of the specific target in that designated view. Based on the occlusion process, the cooperative tracking process may reallocate tracking resources for different trackers in different views. Experimental results show the efficiency of the proposed method.

  6. Analysis of manufacturing based on object oriented discrete event simulation

    Directory of Open Access Journals (Sweden)

    Eirik Borgen

    1990-01-01

    Full Text Available This paper describes SIMMEK, a computer-based tool for performing analysis of manufacturing systems, developed at the Production Engineering Laboratory, NTH-SINTEF. Its main use will be in analysis of job shop type of manufacturing. But certain facilities make it suitable for FMS as well as a production line manufacturing. This type of simulation is very useful in analysis of any types of changes that occur in a manufacturing system. These changes may be investments in new machines or equipment, a change in layout, a change in product mix, use of late shifts, etc. The effects these changes have on for instance the throughput, the amount of VIP, the costs or the net profit, can be analysed. And this can be done before the changes are made, and without disturbing the real system. Simulation takes into consideration, unlike other tools for analysis of manufacturing systems, uncertainty in arrival rates, process and operation times, and machine availability. It also shows the interaction effects a job which is late in one machine, has on the remaining machines in its route through the layout. It is these effects that cause every production plan not to be fulfilled completely. SIMMEK is based on discrete event simulation, and the modeling environment is object oriented. The object oriented models are transformed by an object linker into data structures executable by the simulation kernel. The processes of the entity objects, i.e. the products, are broken down to events and put into an event list. The user friendly graphical modeling environment makes it possible for end users to build models in a quick and reliable way, using terms from manufacturing. Various tests and a check of model logic are helpful functions when testing validity of the models. Integration with software packages, with business graphics and statistical functions, is convenient in the result presentation phase.

  7. Measurement of spatial object's exterior attitude based on linear CCD

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    It is difficult to realize real-time measurement of exterior attitude by the traditional systems based on the area image sensor which have conflict between speed and accuracy.The subsystem for three-dimensional (3D) coordinate rcconstruction of point target (S3DCRPT) which is composed of three one-dimensional (1D) cameras based on linear charge-coupled device (CCD) can determine the distant light spots' spatial position. The attitude angle of the measured object is determined by the spatial solution while the coordinate reconstruction is separately carried on by the S3DCRPT with some point cooperation targets (PCTs) on the measured object. A new optical system is designed to solve the interference problem with one-to-one relationship between the PCTs and the S3DCRPT optical subsystems,which improves the measurement accuracy and saves space. The mathematical model of the attitude measurement is established,and partial and global calibrations are realized for the multi-camera attitude measurement system.The test results show the feasibility of the exterior attitude measurement based on linear CCD.

  8. Options-Based Multi-Objective Evaluation of Product Platforms

    OpenAIRE

    Gonzalez-Zugasti, Javier P.; Otto, Kevin N.; Whitcomb, Clifford A.

    2007-01-01

    The article of record as published may be located at http://dx.doi.org/10.1111/j.1559-3584.2007.00070.x A platform is the set of elements and interfaces that are common to a family of products. Design teams must choose among feasible platform concepts upon which a product family could be based, often involving new technologies. Multiple performance objectives need to be considered. A standard approach is to convert the performance outcomes into financial figures, which can then ...

  9. Cloud Aggregation and Bursting for Object Based Sharable Environment

    Directory of Open Access Journals (Sweden)

    Mr. Pradeep Kumar Tripathi

    2011-09-01

    Full Text Available Cloud computing promises innate scalability and high availability at low cost. So far cloud storage deployments were subject to big companies but an increasing amount of available open-source systems allow also smaller private cloud installations. In this paper we discuss cloud aggregation and cloud bursting with their empirical review. Based on the review we map class and object in the sharable small clouds for making clouds more efficient. We also consider some of the security concern for the cloud computing for authorized data sharing between clouds.

  10. Introducing shape constraints into object-based traveltime tomography

    Science.gov (United States)

    Gaullier, G.; Charbonnier, P.; Heitz, F.; Côte, P.

    2016-09-01

    Traveltime tomography is a difficult, ill-posed reconstruction problem due to the nonlinearity of the forward model and the limited number of measurements usually available. In such an adverse situation, pixel-based regularization methods are generally unable to provide satisfactory reconstructions. In this paper we propose a novel object-based reconstruction method that introduces prior information about the shape of the structures to be reconstructed, which yields high quality geoacoustic inversion. The proposed method approaches the forward model by a series of linear problems, leading to a sequence of minimizations during which the shape prior is introduced. The method is demonstrated on synthetic and real data, collected on a specific bench dedicated to non-destructive testing of civil engineering structures.

  11. Object-based Analysis for Extraction of Dominant Tree Species

    Institute of Scientific and Technical Information of China (English)

    Meiyun; SHAO; Xia; JING; Lu; WANG

    2015-01-01

    As forest is of great significance for our whole development and the sustainable plan is so focus on it. It is very urgent for us to have the whole distribution,stock volume and other related information about that. So the forest inventory program is on our schedule. Aiming at dealing with the problem in extraction of dominant tree species,we tested the highly hot method-object-based analysis. Based on the ALOS image data,we combined multi-resolution in e Cognition software and fuzzy classification algorithm. Through analyzing the segmentation results,we basically extract the spruce,the pine,the birch and the oak of the study area. Both the spectral and spatial characteristics were derived from those objects,and with the help of GLCM,we got the differences of each species. We use confusion matrix to do the Classification accuracy assessment compared with the actual ground data and this method showed a comparatively good precision as 87% with the kappa coefficient 0. 837.

  12. Reactive underwater object inspection based on artificial electric sense.

    Science.gov (United States)

    Lebastard, Vincent; Boyer, Frédéric; Lanneau, Sylvain

    2016-07-26

    Weakly electric fish can perform complex cognitive tasks based on extracting information from blurry electric images projected from their immediate environment onto their electro-sensitive skin. In particular they can be trained to recognize the intrinsic properties of objects such as their shape, size and electric nature. They do this by means of novel perceptual strategies that exploit the relations between the physics of a self-generated electric field, their body morphology and the ability to perform specific movement termed probing motor acts (PMAs). In this article we artificially reproduce and combine these PMAs to build an autonomous control strategy that allows an artificial electric sensor to find electrically contrasted objects, and to orbit around them based on a minimum set of measurements and simple reactive feedback control laws of the probe's motion. The approach does not require any simulation models and could be implemented on an autonomous underwater vehicle (AUV) equipped with artificial electric sense. The AUV has only to satisfy certain simple geometric properties, such as bi-laterally (left/right) symmetrical electrodes and possess a reasonably high aspect (length/width) ratio.

  13. Reactive underwater object inspection based on artificial electric sense.

    Science.gov (United States)

    Lebastard, Vincent; Boyer, Frédéric; Lanneau, Sylvain

    2016-01-01

    Weakly electric fish can perform complex cognitive tasks based on extracting information from blurry electric images projected from their immediate environment onto their electro-sensitive skin. In particular they can be trained to recognize the intrinsic properties of objects such as their shape, size and electric nature. They do this by means of novel perceptual strategies that exploit the relations between the physics of a self-generated electric field, their body morphology and the ability to perform specific movement termed probing motor acts (PMAs). In this article we artificially reproduce and combine these PMAs to build an autonomous control strategy that allows an artificial electric sensor to find electrically contrasted objects, and to orbit around them based on a minimum set of measurements and simple reactive feedback control laws of the probe's motion. The approach does not require any simulation models and could be implemented on an autonomous underwater vehicle (AUV) equipped with artificial electric sense. The AUV has only to satisfy certain simple geometric properties, such as bi-laterally (left/right) symmetrical electrodes and possess a reasonably high aspect (length/width) ratio. PMID:27458187

  14. Strength of object representation: its key role in object-based attention for determining the competition result between Gestalt and top-down objects.

    Science.gov (United States)

    Zhao, Jingjing; Wang, Yonghui; Liu, Donglai; Zhao, Liang; Liu, Peng

    2015-10-01

    It was found in previous studies that two types of objects (rectangles formed according to the Gestalt principle and Chinese words formed in a top-down fashion) can both induce an object-based effect. The aim of the present study was to investigate how the strength of an object representation affects the result of the competition between these two types of objects based on research carried out by Liu, Wang and Zhou [(2011) Acta Psychologica, 138(3), 397-404]. In Experiment 1, the rectangles were filled with two different colors to increase the strength of Gestalt object representation, and we found that the object effect changed significantly for the different stimulus types. Experiment 2 used Chinese words with various familiarities to manipulate the strength of the top-down object representation. As a result, the object-based effect induced by rectangles was observed only when the Chinese word familiarity was low. These results suggest that the strength of object representation determines the result of competition between different types of objects.

  15. RFID and IP Based Object Identification in Ubiquitous Networking

    OpenAIRE

    Nisha Vaghela; Parikshit Mahalle

    2012-01-01

    Ubiquitous networking is an integrated part of future networking technology that can provide capabilities for connecting all of objects (computers, human, PDAs, cell phones etc.) in future network. It has to meet the challenge of seamless connection for communication between human and objects in internet infrastructure. Unique object identification is very much important to make the communication between objects possible. RFID tag can be used as unique identifier to identify a physical object...

  16. Noise Based Detection and Segmentation of Nebulous Objects

    CERN Document Server

    Akhlaghi, Mohammad

    2015-01-01

    A noise based non parametric technique to detect nebulous objects, for example irregular or clumpy galaxies, and their structure in noise is introduced. Noise based and non parametric imply that it imposes negligible constraints on the properties of the targets and that it employs no regression analysis or fittings. The sub-sky detection threshold is defined, and initial detections are found, independent of the sky value. False detections are then estimated and removed using the ambient noise as a reference. This results in a purity level of 0.86 for the final detections as compared to 0.27 for SExtractor when a completeness of 1 is desired for a sample extremely faint and diffuse identical mock galaxy profiles. The dispersion in their measured magnitudes is less by one magnitude, allowing much more accurate photometry. Defining the accuracy of detection as the difference of the measured sky with the known background of mock images, an order of magnitude less biased sky measurement is achieved. A non parametr...

  17. Poka Yoke system based on image analysis and object recognition

    Science.gov (United States)

    Belu, N.; Ionescu, L. M.; Misztal, A.; Mazăre, A.

    2015-11-01

    Poka Yoke is a method of quality management which is related to prevent faults from arising during production processes. It deals with “fail-sating” or “mistake-proofing”. The Poka-yoke concept was generated and developed by Shigeo Shingo for the Toyota Production System. Poka Yoke is used in many fields, especially in monitoring production processes. In many cases, identifying faults in a production process involves a higher cost than necessary cost of disposal. Usually, poke yoke solutions are based on multiple sensors that identify some nonconformities. This means the presence of different equipment (mechanical, electronic) on production line. As a consequence, coupled with the fact that the method itself is an invasive, affecting the production process, would increase its price diagnostics. The bulky machines are the means by which a Poka Yoke system can be implemented become more sophisticated. In this paper we propose a solution for the Poka Yoke system based on image analysis and identification of faults. The solution consists of a module for image acquisition, mid-level processing and an object recognition module using associative memory (Hopfield network type). All are integrated into an embedded system with AD (Analog to Digital) converter and Zync 7000 (22 nm technology).

  18. Adaptive Multi-Objective Optimization Based on Feedback Design

    Institute of Scientific and Technical Information of China (English)

    窦立谦; 宗群; 吉月辉; 曾凡琳

    2010-01-01

    The problem of adaptive multi-objective optimization(AMOO) has received extensive attention due to its practical significance.An important issue in optimizing a multi-objective system is adjusting the weighting coefficients of multiple objectives so as to keep track of various conditions.In this paper,a feedback structure for AMOO is designed.Moreover,the reinforcement learning combined with hidden biasing information is applied to online tuning weighting coefficients of objective functions.Finally,the prop...

  19. Model-Based Multi-Objective Reinforcement Learning

    NARCIS (Netherlands)

    Wiering, Marco; Withagen, Maikel; Drugan, Madalina

    2014-01-01

    This paper describes a novel multi-objective reinforcement learning algorithm. The proposed algorithm first learns a model of the multi-objective sequential decision making problem, after which this learned model is used by a multi-objective dynamic programming method to compute Pareto op-timal poli

  20. Resampling technique in the orthogonal direction for down-looking Synthetic Aperture Imaging Ladar

    Science.gov (United States)

    Li, Guangyuan; Sun, Jianfeng; Lu, Zhiyong; Zhang, Ning; Cai, Guangyu; Sun, Zhiwei; Liu, Liren

    2015-09-01

    The implementation of down-looking Synthetic Aperture Imaging Ladar(SAIL) uses quadratic phase history reconstruction in the travel direction and linear phase modulation reconstruction in the orthogonal direction. And the linear phase modulation in the orthogonal direction is generated by the shift of two cylindrical lenses in the two polarization-orthogonal beams. Therefore, the fast-moving of two cylindrical lenses is necessary for airborne down-looking SAIL to match the aircraft flight speed and to realize the compression of the orthogonal direction, but the quick start and the quick stop of the cylindrical lenses must greatly damage the motor and make the motion trail non-uniform. To reduce the damage and get relatively well trajectory, we make the motor move like a sinusoidal curve to make it more realistic movement, and through a resampling interpolation imaging algorithm, we can transform the nonlinear phase to linear phase, and get good reconstruction results of point target and area target in laboratory. The influences on imaging quality in different sampling positions when the motor make a sinusoidal motion and the necessity of the algorithm are analyzed. At last, we perform a comparison of the results of two cases in resolution.

  1. OBJECT-BASED CHANGE DETECTION USING GEOREFERENCED UAV IMAGES

    Directory of Open Access Journals (Sweden)

    J. Shi

    2012-09-01

    Full Text Available Unmanned aerial vehicles (UAV have been widely used to capture and down-link real-time videos/images. However, their role as a low-cost airborne platform for capturing high-resolution, geo-referenced still imagery has not been fully utilized. The images obtained from UAV are advantageous over remote sensing images as they can be obtained at a low cost and potentially no risk to human life. However, these images are distorted due to the noise generated by the rotary wings which limits the usefulness of such images. One potential application of such images is to detect changes between the images of the same area which are collected over time. Change detection is of widespread interest due to a large number of applications, including surveillance and civil infrastructure. Although UAVs can provide images with high resolution in a portable and easy way, such images only cover small parts of the entire field of interest and are often with high deformation. Until now, there is not much application of change detection for UAV images. Also the traditional pixel-based change detection method does not give satisfactory results for such images. In this paper, we have proposed a novel object-based method for change detection using UAV images which can overcome the effect of deformation and can fully utilize the high resolution capability of UAV images. The developed method can be divided into five main blocks: pre-processing, image matching, image segmentation and feature extraction, change detection and accuracy evaluation. The pre-processing step is further divided into two sub-steps: the first sub-step is to geometrically correct the bi-temporal image based on the geo-reference information (GPS/INS installed on the UAV system, and the second sub-step is the radiometric normalization using a histogram method. The image matching block uses the well-known scale-invariant feature transform (SIFT algorithm to match the same areas in the images and then

  2. Object Recognition Algorithm Utilizing Graph Cuts Based Image Segmentation

    Directory of Open Access Journals (Sweden)

    Zhaofeng Li

    2014-02-01

    Full Text Available This paper concentrates on designing an object recognition algorithm utilizing image segmentation. The main innovations of this paper lie in that we convert the image segmentation problem into graph cut problem, and then the graph cut results can be obtained by calculating the probability of intensity for a given pixel which is belonged to the object and the background intensity. After the graph cut process, the pixels in a same component are similar, and the pixels in different components are dissimilar. To detect the objects in the test image, the visual similarity between the segments of the testing images and the object types deduced from the training images is estimated. Finally, a series of experiments are conducted to make performance evaluation. Experimental results illustrate that compared with existing methods, the proposed scheme can effectively detect the salient objects. Particularly, we testify that, in our scheme, the precision of object recognition is proportional to image segmentation accuracy

  3. KNOWLEDGE-BASED OBJECT DETECTION IN LASER SCANNING POINT CLOUDS

    OpenAIRE

    F. Boochs; Karmacharya, A.; Marbs, A.

    2012-01-01

    Object identification and object processing in 3D point clouds have always posed challenges in terms of effectiveness and efficiency. In practice, this process is highly dependent on human interpretation of the scene represented by the point cloud data, as well as the set of modeling tools available for use. Such modeling algorithms are data-driven and concentrate on specific features of the objects, being accessible to numerical models. We present an approach that brings the human e...

  4. OBJECT DETECTION SCHEME FOR DYNAMIC VIDEOS BASED ON LOCAL ILLUMINATION BASED TECHNIQUES

    OpenAIRE

    T. SOWRYA PRATAP; V. SURENDRA BABU

    2014-01-01

    The paper presents the object detection for dynamic texture scenes using illumination based techniques. They are two types of illumination technique. First one is illumination based background subtraction (ILBS) and second one is illumination based frame difference (ILFS). Illumination frame difference is identifying the objects accurately in dynamic texture scene compare to illumination background subtraction. It has less computation complexity, less computation cost and less spa...

  5. Feature based recognition of submerged objects in holographic imagery

    Science.gov (United States)

    Ratto, Christopher R.; Beagley, Nathaniel; Baldwin, Kevin C.; Shipley, Kara R.; Sternberger, Wayne I.

    2014-05-01

    The ability to autonomously sense and characterize underwater objects in situ is desirable in applications of unmanned underwater vehicles (UUVs). In this work, underwater object recognition was explored using a digital holographic system. Two experiments were performed in which several objects of varying size, shape, and material were submerged in a 43,000 gallon test tank. Holograms were collected from each object at multiple distances and orientations, with the imager located either outside the tank (looking through a porthole) or submerged (looking downward). The resultant imagery from these holograms was preprocessed to improve dynamic range, mitigate speckle, and segment out the image of the object. A collection of feature descriptors were then extracted from the imagery to characterize various object properties (e.g., shape, reflectivity, texture). The features extracted from images of multiple objects, collected at different imaging geometries, were then used to train statistical models for object recognition tasks. The resulting classification models were used to perform object classification as well as estimation of various parameters of the imaging geometry. This information can then be used to inform the design of autonomous sensing algorithms for UUVs employing holographic imagers.

  6. Multimedia Learning Systems Based on IEEE Learning Object Metadata (LOM).

    Science.gov (United States)

    Holzinger, Andreas; Kleinberger, Thomas; Muller, Paul

    One of the "hottest" topics in recent information systems and computer science is metadata. Learning Object Metadata (LOM) appears to be a very powerful mechanism for representing metadata, because of the great variety of LOM Objects. This is on of the reasons why the LOM standard is repeatedly cited in projects in the field of eLearning Systems.…

  7. Rule set transferability for object-based feature extraction

    NARCIS (Netherlands)

    Anders, N.S.; Seijmonsbergen, Arie C.; Bouten, Willem

    2015-01-01

    Cirques are complex landforms resulting from glacial erosion and can be used to estimate Equilibrium Line Altitudes and infer climate history. Automated extraction of cirques may help research on glacial geomorphology and climate change. Our objective was to test the transferability of an object-

  8. DEGAS : a temporal active data model based on object autonomy

    NARCIS (Netherlands)

    Akker, J.F.P. van den; Siebes, A.P.J.M.

    1996-01-01

    This report defines DEGAS, an advanced active data model that is novel in two ways. The first innovation is object autonomy, an extreme form of distributed control. In comparison to more traditional approaches, autonomous objects also encapsulate rule definitions to make them active. The second inno

  9. Orbit determination of space objects based on sparse optical data

    CERN Document Server

    Milani, A; Farnocchia, D; Rossi, A; Schildknecht, T; Jehn, R

    2010-01-01

    While building up a catalog of Earth orbiting objects, if the available optical observations are sparse, not deliberate follow ups of specific objects, no orbit determination is possible without previous correlation of observations obtained at different times. This correlation step is the most computationally intensive, and becomes more and more difficult as the number of objects to be discovered increases. In this paper we tested two different algorithms (and the related prototype software) recently developed to solve the correlation problem for objects in geostationary orbit (GEO), including the accurate orbit determination by full least squares solutions with all six orbital elements. Because of the presence in the GEO region of a significant subpopulation of high area to mass objects, strongly affected by non-gravitational perturbations, it was actually necessary to solve also for dynamical parameters describing these effects, that is to fit between 6 and 8 free parameters for each orbit. The validation w...

  10. Partial Evaluation for Class-Based Object-Oriented Languages

    DEFF Research Database (Denmark)

    Schultz, Ulrik Pagh

    2001-01-01

    Object-oriented programming facilitates the development of generic software, but at a significant cost in terms of performance. We apply partial evaluation to object-oriented programs, to automatically map generic software into specific implementations. In this paper we give a concise, formal des...... description of a simple partial evaluator for a minimal object-oriented language, and give directions for extending this partial evaluator to handle realistic programs.......Object-oriented programming facilitates the development of generic software, but at a significant cost in terms of performance. We apply partial evaluation to object-oriented programs, to automatically map generic software into specific implementations. In this paper we give a concise, formal...

  11. A biological hierarchical model based underwater moving object detection.

    Science.gov (United States)

    Shen, Jie; Fan, Tanghuai; Tang, Min; Zhang, Qian; Sun, Zhen; Huang, Fengchen

    2014-01-01

    Underwater moving object detection is the key for many underwater computer vision tasks, such as object recognizing, locating, and tracking. Considering the super ability in visual sensing of the underwater habitats, the visual mechanism of aquatic animals is generally regarded as the cue for establishing bionic models which are more adaptive to the underwater environments. However, the low accuracy rate and the absence of the prior knowledge learning limit their adaptation in underwater applications. Aiming to solve the problems originated from the inhomogeneous lumination and the unstable background, the mechanism of the visual information sensing and processing pattern from the eye of frogs are imitated to produce a hierarchical background model for detecting underwater objects. Firstly, the image is segmented into several subblocks. The intensity information is extracted for establishing background model which could roughly identify the object and the background regions. The texture feature of each pixel in the rough object region is further analyzed to generate the object contour precisely. Experimental results demonstrate that the proposed method gives a better performance. Compared to the traditional Gaussian background model, the completeness of the object detection is 97.92% with only 0.94% of the background region that is included in the detection results. PMID:25140194

  12. A Biological Hierarchical Model Based Underwater Moving Object Detection

    Directory of Open Access Journals (Sweden)

    Jie Shen

    2014-01-01

    Full Text Available Underwater moving object detection is the key for many underwater computer vision tasks, such as object recognizing, locating, and tracking. Considering the super ability in visual sensing of the underwater habitats, the visual mechanism of aquatic animals is generally regarded as the cue for establishing bionic models which are more adaptive to the underwater environments. However, the low accuracy rate and the absence of the prior knowledge learning limit their adaptation in underwater applications. Aiming to solve the problems originated from the inhomogeneous lumination and the unstable background, the mechanism of the visual information sensing and processing pattern from the eye of frogs are imitated to produce a hierarchical background model for detecting underwater objects. Firstly, the image is segmented into several subblocks. The intensity information is extracted for establishing background model which could roughly identify the object and the background regions. The texture feature of each pixel in the rough object region is further analyzed to generate the object contour precisely. Experimental results demonstrate that the proposed method gives a better performance. Compared to the traditional Gaussian background model, the completeness of the object detection is 97.92% with only 0.94% of the background region that is included in the detection results.

  13. Space Object Tracking Method Based on a Snake Model

    Science.gov (United States)

    Zhan-wei, Xu; Xin, Wang

    2016-04-01

    In this paper, aiming at the problem of unstable tracking of low-orbit variable and bright space objects, adopting an active contour model, a kind of improved GVF (Gradient Vector Flow) - Snake algorithm is proposed to realize the real-time search of the real object contour on the CCD image. Combined with the Kalman filter for prediction, a new adaptive tracking method is proposed for space objects. Experiments show that this method can overcome the tracking error caused by the fixed window, and improve the tracking robustness.

  14. Exploiting database technology for object based event storage and retrieval

    International Nuclear Information System (INIS)

    This paper discusses the storage and retrieval of experimental data on relational databases. Physics experiments carried out using reactors and particle accelerators, generate huge amount of data. Also, most of the data analysis and simulation programs are developed using object oriented programming concepts. Hence, one of the most important design features of an experiment related software framework is the way object persistency is handled. We intend to discuss these issues in the light of the module developed by us for storing C++ objects in relational databases like Oracle. This module was developed under the POOL persistency framework being developed for LHC, CERN grid. (author)

  15. Flattop beam illumination for 3D imaging ladar with simple optical devices in the wide distance range

    Science.gov (United States)

    Tsuji, Hidenobu; Nakano, Takayuki; Matsumoto, Yoshihiro; Kameyama, Shumpei

    2016-04-01

    We have developed an illumination optical system for 3D imaging ladar (laser detection and ranging) which forms flattop beam shape by transformation of the Gaussian beam in the wide distance range. The illumination is achieved by beam division and recombination using a prism and a negative powered lens. The optimum condition of the transformation by the optical system is derived. It is confirmed that the flattop distribution can be formed in the wide range of the propagation distance from 1 to 1000 m. The experimental result with the prototype is in good agreement with the calculation result.

  16. Remote sensing clustering analysis based on object-based interval modeling

    Science.gov (United States)

    He, Hui; Liang, Tianheng; Hu, Dan; Yu, Xianchuan

    2016-09-01

    In object-based clustering, image data are segmented into objects (groups of pixels) and then clustered based on the objects' features. This method can be used to automatically classify high-resolution, remote sensing images, but requires accurate descriptions of object features. In this paper, we ascertain that interval-valued data model is appropriate for describing clustering prototype features. With this in mind, we developed an object-based interval modeling method for high-resolution, multiband, remote sensing data. We also designed an adaptive interval-valued fuzzy clustering method. We ran experiments utilizing images from the SPOT-5 satellite sensor, for the Pearl River Delta region and Beijing. The results indicate that the proposed algorithm considers both the anisotropy of the remote sensing data and the ambiguity of objects. Additionally, we present a new dissimilarity measure for interval vectors, which better separates the interval vectors generated by features of the segmentation units (objects). This approach effectively limits classification errors caused by spectral mixing between classes. Compared with the object-based unsupervised classification method proposed earlier, the proposed algorithm improves the classification accuracy without increasing computational complexity.

  17. Object Tracking Approach based on Mean Shift Algorithm

    Directory of Open Access Journals (Sweden)

    Xiaojing Zhang

    2013-06-01

    Full Text Available Object tracking has always been a hotspot in the field of computer vision, which has a range of applications in real world. The object tracking is a critical task in many vision applications. The main steps in video analysis are: detection of interesting moving objects and tracking of such objects from frame to frame. Most of tracking algorithms use pre-defined methods to process. In this paper, we introduce the Mean shift tracking algorithm, which is a kind of important no parameters estimation method, then we evaluate the tracking performance of Mean shift algorithm on different video sequences. Experimental results show that the Mean shift tracker is effective and robust tracking method.

  18. Adaptive Multi-Objective Optimization Based on Feedback Design

    Institute of Scientific and Technical Information of China (English)

    DOU Liqian; ZONG Qun; JI Yuehui; ZENG Fanlin

    2010-01-01

    The problem of adaptive multi-objective optimization(AMOO)has received extensive attention due to its practical significance.An important issue in optimizing a multi-objective system is adjusting the weighting coefficients of multiple objectives so as to keep track of various conditions.In this paper,a feedback structure for AMOO is designed.Moreover,the reinforcement learning combined with hidden biasing information is applied to online tuning weighting coefficients of objective functions.Finally,the proposed approach is applied to the optimization design problem of an elevator group control system.Simulation results show that AMOO has the best average performance at up-peak traffic profile,and its average waiting time reaches 22 s.AMOO is suitable for various traffic patterns,and it is also superior to the majority of algorithms at down-peak traffic profile.

  19. Dominant object detection for autonomous vision-based surveillance

    NARCIS (Netherlands)

    Celik, H.

    2010-01-01

    The deployment of visual surveillance and monitoring systems has reached massive proportions. Consequently, a need to automate the processes involved in retrieving useful information from surveillance videos, such as detecting and counting objects, and interpreting their individual and joint behavio

  20. Tailoring Green Infrastructure Implementation Scenarios based on Stormwater Management Objectives

    Science.gov (United States)

    Green infrastructure (GI) refers to stormwater management practices that mimic nature by soaking up, storing, and controlling onsite. GI practices can contribute reckonable benefits towards meeting stormwater management objectives, such as runoff peak shaving, volume reduction, f...

  1. Drifting Recovery Base Concept for GEO Derelict Object Capture

    Science.gov (United States)

    Bacon, John B.

    2009-01-01

    Over 250 objects hover within 6 m/sec of perfect geostationary orbit. Over half of these objects lie within 0.1 m/sec of the GEO velocity. Such items have 62% of the total velocity required to achieve Earth gravitational escape. A conceptual architecture is proposed to clean this orbit area of derelict objects while providing a demonstration mission for many facets of future asteroid mining operations. These near-GEO objects average nearly 2000kg each, consisting of (typically functioning) power systems, batteries, and large quantities of components and raw aerospace-grade refined materials. Such a demonstration collection system could capture, collect and remove all GEO derelict objects in an international effort to create a depot of components and of aerospace-grade raw materials--with a total mass greater than that of the International Space Station--as a space scrap depot ready for transfer to lunar or Mars orbit, using only two heavy-lift launches and 2-3 years of on-orbit operations.

  2. Topic Modelling for Object-Based Classification of Vhr Satellite Images Based on Multiscale Segmentations

    Science.gov (United States)

    Shen, Li; Wu, Linmei; Li, Zhipeng

    2016-06-01

    Multiscale segmentation is a key prerequisite step for object-based classification methods. However, it is often not possible to determine a sole optimal scale for the image to be classified because in many cases different geo-objects and even an identical geo-object may appear at different scales in one image. In this paper, an object-based classification method based on mutliscale segmentation results in the framework of topic modelling is proposed to classify VHR satellite images in an entirely unsupervised fashion. In the stage of topic modelling, grayscale histogram distributions for each geo-object class and each segment are learned in an unsupervised manner from multiscale segments. In the stage of classification, each segment is allocated a geo-object class label by the similarity comparison between the grayscale histogram distributions of each segment and each geo-object class. Experimental results show that the proposed method can perform better than the traditional methods based on topic modelling.

  3. Dynamic Cell Formation based on Multi-objective Optimization Model

    Directory of Open Access Journals (Sweden)

    Guozhu Jia

    2013-08-01

    Full Text Available In this paper, a multi-objective model is proposed to address the dynamic cellular manufacturing (DCM formation problem. This model considers four conflicting objectives: relocation cost, machine utilization, material handling cost and maintenance cost. The model also considers the situation that some machines could be shared by more than one cell at the same period. A genetic algorithm is applied to get the solution of this mathematical model. Three numerical examples are simulated to evaluate the validity of this model.  

  4. JBOOM: Java Based Object Oriented Model of Software Configuration Management

    Directory of Open Access Journals (Sweden)

    Bhavya Mehta

    2006-01-01

    Full Text Available Most of the present Software Configuration Management systems deal with version and configurations in the form of files and directories, the need today is to have a Software Configuration Management system that handles versions and configurations directly in terms of functions (program module. A major objective of this research is the use of Java in the Software Configuration Management systems. An object-oriented language provides both design and implementation in an integrated manner. We have proposed a model that expresses change evolution in terms of class hierarchies. As the changes evolve so does the class hierarchy, it can be further extended and existing classes can be extended.

  5. Objective, Way and Method of Faculty Management Based on Ergonomics

    Science.gov (United States)

    WANG, Hong-bin; Liu, Yu-hua

    2008-01-01

    The core problem that influences educational quality of talents in colleges and universities is the faculty management. Without advanced faculty, it is difficult to cultivate excellent talents. With regard to some problems in present faculty construction of colleges and universities, this paper puts forward the new objectives, ways and methods of…

  6. CONTENT BASED INDEXING OF MUSIC OBJECTS USING APPROXIMATE SEQUENTIAL PATTERNS

    Directory of Open Access Journals (Sweden)

    Dr.M.Shashi

    2015-03-01

    Full Text Available The music objects are classified into Monophonic and Polyphonic. In Monophonic there is only one track which is the main melody that leads the song. In Polyphonic objects, there are several tracks that accompany the main melody. Each track is a sequence of notes played simultaneously with other tracks. But, the main melody captures the essence of the music and plays vital role in MIR. The MIR involves representation of main melody as a sequence of notes played, extraction of repeating patterns from it and matching of query sequence with frequent repeating sequential patterns constituting the music object. Repeating patterns are subsequences of notes played time and again in a main melody with possible variations in the notes to a tolerable extent. Similarly, the query sequence meant for retrieving a music object may not contain the repeating patterns of the main melody in its exact form. Hence, extraction of approximate patterns is essential for a MIR system. This paper proposes a novel method of finding approximate repeating patterns for the purpose of MIR. The effectiveness of methodology is tested and found satisfactory on real world data namely ‘Raga Surabhi’ an Indian Carnatic Music portal.

  7. Ontology-Based Annotation of Learning Object Content

    Science.gov (United States)

    Gasevic, Dragan; Jovanovic, Jelena; Devedzic, Vladan

    2007-01-01

    The paper proposes a framework for building ontology-aware learning object (LO) content. Previously ontologies were exclusively employed for enriching LOs' metadata. Although such an approach is useful, as it improves retrieval of relevant LOs from LO repositories, it does not enable one to reuse components of a LO, nor to incorporate an explicit…

  8. ICT Competence-Based Learning Object Recommendations for Teachers

    Science.gov (United States)

    Sergis, Stylianos; Zervas, Panagiotis; Sampson, Demetrios G.

    2014-01-01

    Recommender Systems (RS) have been applied in the Technology enhanced Learning (TeL) field for facilitating, among others, Learning Object (LO) selection and retrieval. Most of the existing approaches, however, aim at accommodating the needs of learners and teacher-oriented RS are still an under-investigated field. Moreover, the systems that focus…

  9. Bandwidth trading under misaligned objectives: decentralized measurement-based control

    NARCIS (Netherlands)

    Mandjes, M.R.H.; Ramakrishnan, M.

    2006-01-01

    This paper studies the interplay between a profit-maximizing network and a number of users competing for the finite bandwidth on each link. In our setting, the objectives of the network and the users are ‘misaligned’, in that the prices that optimize the network’s profit do not maximize the aggregat

  10. Application of Object-Based Industrial Controls for Cryogenics

    CERN Document Server

    Casas-Cubillos, J; Gomes, P; Pezzetti, M; Sicard, Claude Henri; Varas, F J

    2002-01-01

    The first application of the CERN Unified Industrial Control system (UNICOS) has been developed for the 1.8 K refrigerator at point 1.8 in mid-2001. This paper presents the engineering methods used for application development, in order to reach the objectives of maintainability and reusability, in the context of a development done by an external consortium of engineering firms. It will also review the lessons learned during this first development and the improvements planned for the next applications.

  11. Development of learning object from IP-based television programme

    OpenAIRE

    Fallahkhair, Sanaz

    2013-01-01

    The TAMALLE+[1, 2] is a prototype system that supports learners in their television viewing, enhancing informal language learning via interactive television and mobile phones. In this paper we describe a learner-centred study designed to elicit criteria for selection of those language learning object whose annotation or explanation through TAMALLE+ system could best enhance the advanced learner’s understanding of popular broadcast television programmes in English. We identified two main areas...

  12. Software-Based Extraction of Objective Parameters from Music Performances

    OpenAIRE

    Lerch, Alexander

    2008-01-01

    Different music performances of the same score may significantly differ from each other. It is obvious that not only the composer’s work, the score, defines the listener’s music experience, but that the music performance itself is an integral part of this experience. Music performers use the information contained in the score, but interpret, transform or add to this information.Four parameter classes can be used to describe a performance objectively: tempo and timing, loudness, timbre and pit...

  13. Integration of an object knowledge base into a medical workstation.

    OpenAIRE

    Timmers, T.; van Mulligen, E. M.; van den Heuvel, F.

    1991-01-01

    A simple, yet powerful, knowledge base and its development environment is described that can act as a "knowledge server", integrated into a medical workstation. In many areas, such an integration of a knowledge base with other modules and systems is required, but difficult or impossible to achieve with existing commercial development shells. Three applications of the knowledge base are described: a controlled vocabulary for the classification of Congenital Heart Diseases, an extended data mod...

  14. Segmentation of object-based video of gaze communication

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Stegmann, Mikkel Bille; Forchhammer, Søren;

    2005-01-01

    Aspects of video communication based on gaze interaction are considered. The overall idea is to use gaze interaction to control video, e.g. for video conferencing. Towards this goal, animation of a facial mask is demonstrated. The animation is based on images using Active Appearance Models (AAM...

  15. A Framework for Geographic Object-Based Image Analysis (GEOBIA) based on geographic ontology

    Science.gov (United States)

    Gu, H. Y.; Li, H. T.; Yan, L.; Lu, X. J.

    2015-06-01

    GEOBIA (Geographic Object-Based Image Analysis) is not only a hot topic of current remote sensing and geographical research. It is believed to be a paradigm in remote sensing and GIScience. The lack of a systematic approach designed to conceptualize and formalize the class definitions makes GEOBIA a highly subjective and difficult method to reproduce. This paper aims to put forward a framework for GEOBIA based on geographic ontology theory, which could implement "Geographic entities - Image objects - Geographic objects" true reappearance. It consists of three steps, first, geographical entities are described by geographic ontology, second, semantic network model is built based on OWL(ontology web language), at last, geographical objects are classified with decision rule or other classifiers. A case study of farmland ontology was conducted for describing the framework. The strength of this framework is that it provides interpretation strategies and global framework for GEOBIA with the property of objective, overall, universal, universality, etc., which avoids inconsistencies caused by different experts' experience and provides an objective model for mage analysis.

  16. Evaluation of satellite-based precipitation estimates in winter season using an object-based approach

    Science.gov (United States)

    Li, J.; Hsu, K.; AghaKouchak, A.; Sorooshian, S.

    2012-12-01

    Verification has become an integral component of satellite precipitation algorithms and products. A number of object-based verification methods have been proposed to provide diagnostic information regarding the precipitation products' ability to capture the spatial pattern, intensity, and placement of precipitation. However, most object-based methods are not capable of investigating precipitation objects at the storm-scale. In this study, an image processing approach known as watershed segmentation was adopted to detect the storm-scale rainfall objects. Then, a fuzzy logic-based technique was utilized to diagnose and analyze storm-scale object attributes, including centroid distance, area ratio, intersection area ratio and orientation angle difference. Three verification metrics (i.e., false alarm ratio, missing ratio and overall membership score) were generated for validation and verification. Three satellite-based precipitation products, including PERSIANN, CMORPH, 3B42RT, were evaluated against NOAA stage IV MPE multi-sensor composite rain analysis at 0.25° by 0.25° on a daily scale in the winter season of 2010 over the contiguous United States. Winter season is dominated by frontal systems which usually have larger area coverage. All three products and the stage IV observation tend to find large size storm objects. With respect to the evaluation attributes, PERSIANN tends to obtain larger area ratio and consequently has larger centroid distance to the stage IV observations, while 3B42RT are found to be closer to the stage IV for the object size. All evaluation products give small orientation angle differences but vary significantly for the missing ratio and false alarm ratio. This implies that satellite estimates can fail to detect storms in winter. The overall membership scores are close for all three different products which indicate that all three satellite-based precipitation products perform well for capturing the spatial and geometric characteristics of

  17. Model-based beam control for illumination of remote objects

    Science.gov (United States)

    Chandler, Susan M.; Lukesh, Gordon W.; Voelz, David; Basu, Santasri; Sjogren, Jon A.

    2004-11-01

    On September 1, 2003, Nukove Scientific Consulting, together with partner New Mexico State University, began work on a Phase 1 Small Business Technology TRansfer (STTR) grant from the United States Air Force Office of Scientific Research (AFOSR). The purpose of the grant was to show the feasibility of taking Nukove's pointing estimation technique from a post-processing tool for estimation of laser system characteristics to a real-time tool usable in the field. Nukove's techniques for pointing, shape, and OCS estimation do not require an imaging sensor nor a target board, thus estimates may be made very quickly. To prove feasibility, Nukove developed an analysis tool RHINO (Real-time Histogram Interpretation of Numerical Observations) and successfully demonstrated the emulation of real-time, frame-by-frame estimation of laser system characteristics, with data streamed into the tool and the estimates displayed as they are made. The eventual objective will be to use the frame-by-frame estimates to allow for feedback to a fielded system. Closely associated with this, NMSU developed a laboratory testbed to illuminate test objects, collect the received photons, and stream the data into RHINO. The two coupled efforts clearly demonstrate the feasibility of real-time pointing control of a laser system.

  18. Semantic Map Building Based on Object Detection for Indoor Navigation

    Directory of Open Access Journals (Sweden)

    Jinfu Yang

    2015-12-01

    Full Text Available Building a map of the environment is a prerequisite for mobile robot navigation. In this paper, we present a semantic map building method for indoor navigation of a robot using only the image sequence acquired by a monocular camera installed on the robot. First, a topological map of the environment is created, where each key frame forms a node of the map represented as visual words (VWs. The edges between two adjacent nodes are built from relative poses obtained by performing a novel pose estimation approach, called one point RANSAC camera pose estimation (ORPE. Then, taking advantage of an improved deformable part model (iDPM for object detection, the topological map is extended by assigning semantic attributes to the nodes. Extensive experimental evaluations demonstrate the effectiveness of the proposed monocular SLAM method.

  19. Automated Detection of Objects Based on Sérsic Profiles

    Science.gov (United States)

    Cabrera, Guillermo; Miller, C.; Harrison, C.; Vera, E.; Asahi, T.

    2011-01-01

    We present the results of a new astronomical object detection and deblending algorithm when applied to Sloan Digital Sky Survey data. Our algorithm fits PSF-convolved Sérsic profiles to elliptical isophotes of source candidates. The main advantage of our method is that it minimizes the amount and complexity of real-time user input relative to many commonly used source detection algorithms. Our results are compared with 1D radial profile Sérsic fits. Our long-term goal is to use these techniques in a mixture-model environment to leverage the speed and advantages of machine learning. This approach will have a great impact when re-processing large data-sets and data-streams from next generation telescopes, such as the LSST and the E-ELT.

  20. Digital Microdroplet Ejection Technology-Based Heterogeneous Objects Prototyping

    Directory of Open Access Journals (Sweden)

    Na Li

    2016-01-01

    Full Text Available An integrate fabrication framework is presented to build heterogeneous objects (HEO using digital microdroplets injecting technology and rapid prototyping. The heterogeneous materials part design and manufacturing method in structure and material was used to change the traditional process. The net node method was used for digital modeling that can configure multimaterials in time. The relationship of material, color, and jetting nozzle was built. The main important contributions are to combine the structure, material, and visualization in one process and give the digital model for manufacture. From the given model, it is concluded that the method is effective for HEO. Using microdroplet rapid prototyping and the model given in the paper HEO could be gotten basically. The model could be used in 3D biomanufacturing.

  1. Buried object location based on frequency-domain UWB measurements

    International Nuclear Information System (INIS)

    In this paper, a wideband ground penetrating radar (GPR) system and a proposed frequency-domain data analysis technique are presented for the detection of shallow buried objects such as anti-personnel landmines. The GPR system uses one transmitting antenna and an array of six monopole receiving antenna elements and operates from 1 GHz to 20 GHz. This system is able to acquire, save and analyse data in the frequency domain. A common source or wide-angle reflection and refraction technique has been used for acquiring and processing the data. This technique is effective for the rejection of ground surface clutter. By applying the C-scan scheme, metallic and plastic mine-like targets buried in dry soil will be located

  2. Video object's behavior analyzing based on motion history image and hidden markov model

    Institute of Scientific and Technical Information of China (English)

    Meng Fanfeng; Qu Zhenshen; Zeng Qingshuang; Li li

    2009-01-01

    A novel method was proposed, which extracted video object's track and analyzed video object's behavior. Firstly, this method tracked the video object based on motion history image, and obtained the coordinate-based track sequence and orientation-based track sequence of the video object. Then the proposed hidden markov model (HMM) based algorithm was used to analyze the behavior of video object with the track sequence as input. Experimental results on traffic object show that this method can achieve the statistics of a mass of traffic objects' behavior efficiently, can acquire the reasonable velocity behavior curve of traffic object, and can recognize traffic object's various behaviors accurately. It provides a base for further research on video object behavior.

  3. Identifying Objective EEG Based Markers of Linear Vection in Depth

    Science.gov (United States)

    Palmisano, Stephen; Barry, Robert J.; De Blasio, Frances M.; Fogarty, Jack S.

    2016-01-01

    This proof-of-concept study investigated whether a time-frequency EEG approach could be used to examine vection (i.e., illusions of self-motion). In the main experiment, we compared the event-related spectral perturbation (ERSP) data of 10 observers during and directly after repeated exposures to two different types of optic flow display (each was 35° wide by 29° high and provided 20 s of motion stimulation). Displays consisted of either a vection display (which simulated constant velocity forward self-motion in depth) or a control display (a spatially scrambled version of the vection display). ERSP data were decomposed using time-frequency Principal Components Analysis (t–f PCA). We found an increase in 10 Hz alpha activity, peaking some 14 s after display motion commenced, which was positively associated with stronger vection ratings. This followed decreases in beta activity, and was also followed by a decrease in delta activity; these decreases in EEG amplitudes were negatively related to the intensity of the vection experience. After display motion ceased, a series of increases in the alpha band also correlated with vection intensity, and appear to reflect vection- and/or motion-aftereffects, as well as later cognitive preparation for reporting the strength of the vection experience. Overall, these findings provide support for the notion that EEG can be used to provide objective markers of changes in both vection status (i.e., “vection/no vection”) and vection strength. PMID:27559328

  4. Feature-based and object-based attention orientation during short-term memory maintenance.

    Science.gov (United States)

    Ku, Yixuan

    2015-12-01

    Top-down attention biases the short-term memory (STM) processing at multiple stages. Orienting attention during the maintenance period of STM by a retrospective cue (retro-cue) strengthens the representation of the cued item and improves the subsequent STM performance. In a recent article, Backer et al. (Backer KC, Binns MA, Alain C. J Neurosci 35: 1307-1318, 2015) extended these findings from the visual to the auditory domain and combined electroencephalography to dissociate neural mechanisms underlying feature-based and object-based attention orientation. Both event-related potentials and neural oscillations explained the behavioral benefits of retro-cues and favored the theory that feature-based and object-based attention orientation were independent. PMID:26084908

  5. Relational and Object-Oriented Methodology in Data Bases Systems

    Directory of Open Access Journals (Sweden)

    Marian Pompiliu CRISTESCU

    2006-01-01

    Full Text Available Database programming languages integrate concepts of databases and programming languages to provide both implementation tools for data-intensive applications and high-level user interfaces to databases. Frequently, database programs contain a large amount of application knowledge which is hidden in the procedural code and thus difficult to maintain with changing data and user views. This paper presents a first attempt to improve the situation by supporting the integrated definition and management of data and rules based on a setoriented and predicative approach. The use of database technology for integrated fact and rule base management is shown to have some important advantages in terms of fact and rule integrity, question-answering, and explanation of results.

  6. Design of Objects Tracking System Based on ARM Embedded Platform

    Institute of Scientific and Technical Information of China (English)

    XU Mei; SONG Yong-duan; LV Shao-dong; LIU Zhi-long; HUANG Cong-ying

    2014-01-01

    In recent years, according to the need of intelligent video surveillance system increasing rapidly in metropolitan cities ,a design based on S3C2440 microprocessor and embedded Linux operating system is adopted for real-time video target tracking. However, it is very challenging as embedded systems usually afford limited processing power and limited resources. Therefore, to address this problem, a real-time tracking algorithm using multi-features based on compressive sensing is proposed and implemented. The algorithm uses multiple matrix as the projection matrix of the compressive sensing and the compressed date as the multiple features to extract useful information needed by tracking process. Functions and libraries in OpenCV which were developed by Intel Corporation are utilized for building the tracking algorithms. It is tested with variant video sequences and the results show that the algorithm achieves stable tracking for the target moved of the light changed.

  7. Robust B+ -Tree-Based Indexing of Moving Objects

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Tiesyte, Dalia; Tradisauskas, Nerius

    2006-01-01

    that is needed to guarantee perfect recall, thus significantly improving robustness. The new technique is empirically evaluated and compared with four other approaches and with the TPR-tree, a competitor that is based on the R*-tree. The results indicate that the new index is indeed more robust than its...... predecessor?it significantly reduces the number of I/O operations per query for the workloads considered. In many settings, the TPR-tree is outperformed as well....

  8. Hierarchical Object-Based Visual Attention for Machine Vision

    OpenAIRE

    Sun, Yaoru

    2003-01-01

    Human vision uses mechanisms of covert attention to selectively process interesting information and overt eye movements to extend this selectivity ability. Thus, visual tasks can be effectively dealt with by limited processing resources. Modelling visual attention for machine vision systems is not only critical but also challenging. In the machine vision literature there have been many conventional attention models developed but they are all space-based only and cannot perform ...

  9. Rule Based Selection of 2D Urban Area Map Objects

    OpenAIRE

    Jagdish Lal Raheja; Umesh Kumar

    2010-01-01

    The purpose of cartographic generalization is to represent a particular situation adapted to the needs of its users, with adequate legibility of the representation and perceptional congruity with the real situation. In this paper, a simple approach is presented for the selection process of building ground plans that are represented as 2D line, square and polygon segments. It is based on simple selection process from the field of computer graphics. It is important to preserve the overall chara...

  10. Web-based visualization of spatial objects in 3DGIS

    Institute of Scientific and Technical Information of China (English)

    ZHANG LiQiang; GUO ZhiFeng; KANG ZhiZhong; ZHANG LiXin; ZHANG XingMing; YANG Ling

    2009-01-01

    Adaptive rendering large and complex spatial data has become an important research issue In a 3DGIS application.In order to transmit the data to the client efficiently,this paper proposes a node-layer data model to manage the 3D scene.Because the large spatial data and limited network bandwidth are the main bottlenecks of web-based 3DGIS,a client/server architecture including progressive transmission methods and multiresolution representations,together with the spatial index,are developed to improve the performance.All this makes the application quite scalable.Experimental results reveal that the application works appropriately.

  11. Design of Object-based Information System Prototype

    Directory of Open Access Journals (Sweden)

    Suhyeon Yoo

    2014-06-01

    Full Text Available Researchers who use science and technology information were found to ask an information service in which they can excerpt the contents they needed, rather than using the information at article level. In this study, we micronized the contents of scholarly articles into text, image, and table and then constructed a micro-content DB to design a new information system prototype based on this micro-content. After designing the prototype, we performed usability test for this prototype so as to confirm the usefulness of the system prototype. We expect that the outcome of this study will fulfill the segmented and diversified information need of researchers.

  12. From neural-based object recognition toward microelectronic eyes

    Science.gov (United States)

    Sheu, Bing J.; Bang, Sa Hyun

    1994-01-01

    Engineering neural network systems are best known for their abilities to adapt to the changing characteristics of the surrounding environment by adjusting system parameter values during the learning process. Rapid advances in analog current-mode design techniques have made possible the implementation of major neural network functions in custom VLSI chips. An electrically programmable analog synapse cell with large dynamic range can be realized in a compact silicon area. New designs of the synapse cells, neurons, and analog processor are presented. A synapse cell based on Gilbert multiplier structure can perform the linear multiplication for back-propagation networks. A double differential-pair synapse cell can perform the Gaussian function for radial-basis network. The synapse cells can be biased in the strong inversion region for high-speed operation or biased in the subthreshold region for low-power operation. The voltage gain of the sigmoid-function neurons is externally adjustable which greatly facilitates the search of optimal solutions in certain networks. Various building blocks can be intelligently connected to form useful industrial applications. Efficient data communication is a key system-level design issue for large-scale networks. We also present analog neural processors based on perceptron architecture and Hopfield network for communication applications. Biologically inspired neural networks have played an important role towards the creation of powerful intelligent machines. Accuracy, limitations, and prospects of analog current-mode design of the biologically inspired vision processing chips and cellular neural network chips are key design issues.

  13. Mass Measurements of Isolated Objects from Space-based Microlensing

    Science.gov (United States)

    Zhu, Wei; Calchi Novati, S.; Gould, A.; Udalski, A.; Han, C.; Shvartzvald, Y.; Ranc, C.; Jørgensen, U. G.; Poleski, R.; Bozza, V.; Beichman, C.; Bryden, G.; Carey, S.; Gaudi, B. S.; Henderson, C. B.; Pogge, R. W.; Porritt, I.; Wibking, B.; Yee, J. C.; SPITZER Team; Pawlak, M.; Szymański, M. K.; Skowron, J.; Mróz, P.; Kozłowski, S.; Wyrzykowski, Ł.; Pietrukowicz, P.; Pietrzyński, G.; Soszyński, I.; Ulaczyk, K.; OGLE Group; Choi, J.-Y.; Park, H.; Jung, Y. K.; Shin, I.-G.; Albrow, M. D.; Park, B.-G.; Kim, S.-L.; Lee, C.-U.; Cha, S.-M.; Kim, D.-J.; Lee, Y.; KMTNET Group; Friedmann, M.; Kaspi, S.; Maoz, D.; WISE Group; Hundertmark, M.; Street, R. A.; Tsapras, Y.; Bramich, D. M.; Cassan, A.; Dominik, M.; Bachelet, E.; Dong, Subo; Figuera Jaimes, R.; Horne, K.; Mao, S.; Menzies, J.; Schmidt, R.; Snodgrass, C.; Steele, I. A.; Wambsganss, J.; RoboNeT Team; Skottfelt, J.; Andersen, M. I.; Burgdorf, M. J.; Ciceri, S.; D'Ago, G.; Evans, D. F.; Gu, S.-H.; Hinse, T. C.; Kerins, E.; Korhonen, H.; Kuffmeier, M.; Mancini, L.; Peixinho, N.; Popovas, A.; Rabus, M.; Rahvar, S.; Tronsgaard, R.; Scarpetta, G.; Southworth, J.; Surdej, J.; von Essen, C.; Wang, Y.-B.; Wertz, O.; MiNDSTEP Group

    2016-07-01

    We report on the mass and distance measurements of two single-lens events from the 2015 Spitzer microlensing campaign. With both finite-source effect and microlens parallax measurements, we find that the lens of OGLE-2015-BLG-1268 is very likely a brown dwarf (BD). Assuming that the source star lies behind the same amount of dust as the Bulge red clump, we find the lens is a 45 ± 7 {M}{{J}} BD at 5.9 ± 1.0 kpc. The lens of of the second event, OGLE-2015-BLG-0763, is a 0.50 ± 0.04 {M}ȯ star at 6.9 ± 1.0 kpc. We show that the probability to definitively measure the mass of isolated microlenses is dramatically increased once simultaneous ground- and space-based observations are conducted.

  14. Mass Measurements of Isolated Objects from Space-based Microlensing

    CERN Document Server

    Zhu, Wei; Gould, A; Udalski, A; Han, C; Shvartzvald, Y; Ranc, C; Jorgensen, U G; Poleski, R; Bozza, V; Beichman, C; Bryden, G; Carey, S; Gaudi, B S; Henderson, C B; Pogge, R W; Porritt, I; Wibking, B; Yee, J C; Pawlak, M; Szymanski, M K; Skowron, J; Mroz, P; Kozlowski, S; Wyrzykowski, L; Pietrukowicz, P; Pietrzynski, G; Soszynski, I; Ulaczyk, K; Choi, J Y; Park, H; Jung, Y K; Shin, I -G; Albrow, M D; Park, B -G; Kim, S -L; Lee, C -U; Kim, D -J; Lee, Y; Friedmann, M; Kaspi, S; Maoz, D; Hundertmark, M; Street, R A; Tsapras, Y; Bramich, D M; Cassan, A; Dominik, M; Bachelet, E; Dong, Subo; Jaimes, R Figuera; Horne, K; Mao, S; Menzies, J; Schmidt, R; Snodgrass, C; Steele, I A; Wambsganss, J; Skottfelt, J; Andersen, M I; Burgdorf, M J; Ciceri, S; D'Ago, G; Evans, D F; Gu, S -H; Hinse, T C; Kerins, E; Korhonen, H; Kuffmeier, M; Mancini, L; Peixinho, N; popovas, A; Rabus, M; Rahvar, S; Rasmussen, R T; Scarpetta, G; Southworth, J; Surdej, J; von Essen, C; Wang, Y -B; Wertz, O

    2015-01-01

    We report on the mass and distance measurements of two single-lens events from the 2015 \\emph{Spitzer} microlensing campaign. With both finite-source effect and microlens parallax measurements, we find that the lens of OGLE-2015-BLG-1268 is a $47\\pm7$ $M_{\\rm J}$ brown dwarf at $5.4\\pm1.0$ kpc, and that the lens of OGLE-2015-BLG-0763 is a $0.50\\pm0.04$ $M_\\odot$ star at $6.9\\pm1.0$ kpc. We show that the probability to definitively measure the mass of isolated microlenses, including isolated stellar mass black holes and free floating planets, is dramatically increased once simultaneous ground- and space-based observations are conducted.

  15. Multi-objective optimization of process based on resource capability

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    To improve the practicability, suitability and accuracy of the trade-off among time, cost and quality of a process, a method based on resource capability is introduced. Through analyzing the relationship between an activity and its' supporting resource, the model trades off the time, cost and quality by changing intensity of labor or changing the types of supporting resource or units of labor of resource in a certain time respectively according to the different types of its' supporting resources. Through contrasting this method with the model of unit time cost corresponding to different quality levels and inter-related linear programming model of time, cost and quality for process optimizing, it is shown that this model does not only cover the above two models but also can describe some conditions the above two models can not express. The method supports to select different function to optimize a process according to different types of its supporting resource.

  16. Proto-object based rate control for JPEG2000: an approach to content-based scalability.

    Science.gov (United States)

    Xue, Jianru; Li, Ce; Zheng, Nanning

    2011-04-01

    The JPEG2000 system provides scalability with respect to quality, resolution and color component in the transfer of images. However, scalability with respect to semantic content is still lacking. We propose a biologically plausible salient region based bit allocation mechanism within the JPEG2000 codec for the purpose of augmenting scalability with respect to semantic content. First, an input image is segmented into several salient proto-objects (a region that possibly contains a semantically meaningful physical object) and background regions (a region that contains no object of interest) by modeling visual focus of attention on salient proto-objects. Then, a novel rate control scheme distributes a target bit rate to each individual region according to its saliency, and constructs quality layers of proto-objects for the purpose of more precise truncation comparable to original quality layers in the standard. Empirical results show that the suggested approach adds to the JPEG2000 system scalability with respect to content as well as the functionality of selectively encoding, decoding, and manipulation of each individual proto-object in the image, with only some slightly trivial modifications to the JPEG2000 standard. Furthermore, the proposed rate control approach efficiently reduces the computational complexity and memory usage, as well as maintains the high quality of the image to a level comparable to the conventional post-compression rate distortion (PCRD) optimum truncation algorithm for JPEG2000.

  17. Object Structure from Manipulation via Particle Filter and Robot-based Active Learning

    OpenAIRE

    LI, Kun; Meng, Max Q.-H.

    2014-01-01

    To learn object models for robotic manipulation, unsupervised methods cannot provide accurate object structural information and supervised methods require a large amount of manually labeled training samples, thus interactive object segmentation is developed to automate object modeling. In this article, we formulate a novel dynamic process for interactive object segmentation, and develop a solution based on particle filter and active learning so that a robot can manipulate and learn object str...

  18. Optical MEMS-based arrays

    Science.gov (United States)

    Ruffin, Paul B.

    2003-07-01

    Industrial Micro Electro Mechanical Systems (MEMS) developers are rapidly bringing to demonstration inertial radio frequency, and optical MEMS devices and components. The Army has a requirement for compact, highly reliable, and inexpensive laser beam steering components for missile seekers and unmanned aerial vehicles remote sensing components to provide a fast scanning capability for pointing, acquisition, tracking, and data communication. The coupling of this requirement with recent developments in the micro-optics area, has led scientists and engineers at the Army Aviation and Missile Command (AMCOM) to consider optical MEMS-based phased arrays, which have potential applications in the commercial industry as well as in the military, as a replacement for gimbals. Laser beam steering in commercial applications such as free space communicataion, scanning display, bar-code reading, and gimbaled seekers; require relatively large monolithic micro-mirrors to accomplish the required optical resolution. The Army will benefit from phased arrays composed of relatively small micro-mirrors that can be actuated through large deflection angles with substantially reduced volume times. The AMCOM Aviation and Missile Research, Development, and Engineering Center (AMRDEC) has initiated a research project to develop MEMS-based phased arrays for use in a small volume, inexpensive Laser Detection and Ranging (LADAR) seeker that is particularly attractive because of its ability to provide large field-of-regard and autonomous target acquisition for reconnaissance mission applications. The primary objective of the collaborative project with the Defence Advanced Research Projects Agency (DARPA) is to develop a rugged, MEMS-based phased arrays for incorporation into the 2-D scanner of a LADAR seeker. Design challenges and approach to achieving performance requirements will be discussed.

  19. Rule Based Selection of 2D Urban Area Map Objects

    Directory of Open Access Journals (Sweden)

    Jagdish Lal Raheja

    2010-09-01

    Full Text Available The purpose of cartographic generalization is to represent a particular situation adapted to the needs of its users, with adequate legibility of the representation and perceptional congruity with the real situation. In this paper, a simple approach is presented for the selection process of building ground plans that are represented as 2D line, square and polygon segments. It is based on simple selection process from the field of computer graphics. It is important to preserve the overall characteristics of the buildings; the lines are simplified with regard to geometric relations. These characteristics allow for an easy recognition of buildings even on small displays of mobile devices. Such equipment has become a tool for our everyday life in the form of mobile phones, personal digital assistants and GPS assisted navigation systems. Although the computing performance and network bandwidth will increase further, such devices will always be limited by the rather small display area available for communicating the spatial information. This means that an appropriate transformation and visualization of building data as presented in this paper is essential.

  20. Surface investigation of naturally corroded gilded copper-based objects

    Science.gov (United States)

    Ingo, G. M.; Riccucci, C.; Lavorgna, M.; Salzano de Luna, M.; Pascucci, M.; Di Carlo, G.

    2016-11-01

    Gold and silver coated copper-based artefacts subjected to long-term natural corrosion phenomena were studied by means of the combined use of X-ray photoelectron spectroscopy (XPS), scanning electron microscopy coupled with energy dispersive X-ray spectroscopy (SEM + EDS), and optical microscopy (OM). The results allowed the identification of the chemistry and structure of the Au or Ag layers deposited by fire-gilding or mercury-silvering and the determination of the corrosion products formed due to interaction with the surrounding environment. Different degradation phenomena of the noble metal layer and copper substrate are induced by the presence of chlorine, sulphur and phosphorous and they are boosted by the metal galvanic coupling which makes gilded-metal art works unstable from a chemico-physical point of view. The SEM + EDS and OM results also suggest that particular care must be used during the removal of the encrustations and of the external corrosion products to avoid the loss of the remains of the noble layer often floating or embedded in the corrosion products. Furthermore, in order to avoid the reaction between nantokite (CuCl) and moisture the use no or low toxic inhibitors is suggested to avoid further severe degradation phenomena enhancing the long-lasting chemico-physical stability of these precious artefacts and giving them a greater chance of survival.

  1. Spectroscopic Assessment of WISE-based Young Stellar Object Selection

    CERN Document Server

    Koenig, Xavier; Padgett, Deborah; DeFelippis, Daniel

    2015-01-01

    We have conducted a sensitive search down to the hydrogen burning limit for unextincted stars over $\\sim$200 square degrees around Lambda Orionis and 20 square degrees around Sigma Orionis using the methodology of Koenig & Leisawitz (2014). From WISE and 2MASS data we identify 544 and 418 candidate YSOs in the vicinity of Lambda and Sigma respectively. Based on our followup spectroscopy for some candidates and the existing literature for others, we found that $\\sim$80% of the K14-selected candidates are probable or likely members of the Orion star forming region. The yield from the photometric selection criteria shows that WISE sources with $K_S -w3 > 1.5$ mag and $K_S $ between 10--12 mag are most likely to show spectroscopic signs of youth, while WISE sources with $K_S -w3 > 4$ mag and $K_S > 12$ were often AGNs when followed up spectroscopically. The population of candidate YSOs traces known areas of active star formation, with a few new `hot spots' of activity near Lynds 1588 and 1589 and a more dispe...

  2. A Knowledge-Based Approach to Describe and Adapt Learning Objects

    Science.gov (United States)

    Bouzeghoub, Amel; Defude, Bruno; Duitama, John Freddy; Lecocq, Claire

    2006-01-01

    Our claim is that semantic metadata are required to allow a real reusing and assembling of learning objects. Our system is based on three models used to describe the domain, learners, and learning objects. The learning object model is inspired from knowledge representation proposals. A learning object can be reused directly or can be combined with…

  3. Attentional spreading to task-irrelevant object features: Experimental support and a 3-step model of attention for object-based selection and feature-based processing modulation

    Directory of Open Access Journals (Sweden)

    Detlef eWegener

    2014-06-01

    Full Text Available Directing attention to a specific feature of an object has been linked to different forms of attentional modulation. Object-based attention theory founds on the finding that even task-irrelevant features at the selected object are subject to attentional modulation, while feature-based attention theory proposes a global processing benefit for the selected feature even at other objects. Most studies investigated either the one or the other form of attention, leaving open the possibility that both object- and feature-specific attentional effects do occur at the same time and may just represent two sides of a single attention system. We here investigate this issue by testing attentional spreading within and across objects, using reaction time measurements to changes of attended and unattended features on both attended and unattended objects. We asked subjects to report color and speed changes occurring on one of two overlapping random dot patterns, presented at the center of gaze. The key property of the stimulation was that only one of the features (e.g. motion direction was unique for each object, whereas the other feature (e.g. color was shared by both. The results of two experiments show that co-selection of unattended features even occurs when those features have no means for selecting the object. At the same time, they demonstrate that this processing benefit is not restricted to the selected object but spreads to the task-irrelevant one. We conceptualize these findings by a 3-step model of attention that assumes a task-dependent top-down gain, object-specific feature selection based on task- and binding characteristics, and a global feature-specific processing enhancement. The model allows for the unification of a vast amount of experimental results into a single model, and makes various experimentally testable predictions for the interaction of object- and feature-specific processes.

  4. Shot noise statistics and information theory of sensitivity limits in frequency-modulated continuous-wave ladar.

    Science.gov (United States)

    Barber, Zeb W; Dahl, Jason R; Sharpe, Tia L; Erkmen, Baris I

    2013-07-01

    A theoretical analysis and experimental verification of the sensitivity limits of frequency-modulated continuous-wave (FMCW) ladar in the limit of a strong local oscillator is presented. The single-photon sensitivity of coherent heterodyne detection in this shot-noise dominated limit is verified to extend to linearly chirped waveforms. An information theoretic analysis is presented to estimate the information efficiency of received photons for the task of locating the range to single and multiple targets. It is found that the optimum receive signal level is proportional to the logarithm of the number of resolvable range locations and the maximum theoretical photon information efficiency for FMCW ranging with coherent fields is log(e)≈1.44 bits per received photon. PMID:24323147

  5. A Growth-Cone Model for the Spread of Object-Based Attention during Contour Grouping

    NARCIS (Netherlands)

    Pooresmaeili, Arezoo; Roelfsema, Pieter R

    2014-01-01

    BACKGROUND: Object-based attention can group image elements of spatially extended objects into coherent representations, but its mechanisms have remained unclear. The mechanisms for object-based attention may include shape-selective neurons in higher visual cortical areas that feed back to lower are

  6. An Automated Video Object Extraction System Based on Spatiotemporal Independent Component Analysis and Multiscale Segmentation

    Directory of Open Access Journals (Sweden)

    Zhang Xiao-Ping

    2006-01-01

    Full Text Available Video content analysis is essential for efficient and intelligent utilizations of vast multimedia databases over the Internet. In video sequences, object-based extraction techniques are important for content-based video processing in many applications. In this paper, a novel technique is developed to extract objects from video sequences based on spatiotemporal independent component analysis (stICA and multiscale analysis. The stICA is used to extract the preliminary source images containing moving objects in video sequences. The source image data obtained after stICA analysis are further processed using wavelet-based multiscale image segmentation and region detection techniques to improve the accuracy of the extracted object. An automated video object extraction system is developed based on these new techniques. Preliminary results demonstrate great potential for the new stICA and multiscale-segmentation-based object extraction system in content-based video processing applications.

  7. Guided Creation and Update of Objects in RDF(S) Bases

    OpenAIRE

    Hermann, Alice; Ferré, Sébastien; Ducassé, Mireille

    2011-01-01

    International audience Updating existing knowledge bases is crucial to take into account the information that are regularly discovered. However, this is quite tedious and in practice Semantic Web data are rarely updated by users. This paper presents UTILIS, an approach to help users create and update objects in RDF(S) bases. While creating a new object, o, UTILIS searches for similar objects, found by applying relaxation rules to the description of o, taken as a query. The resulting object...

  8. A Dynamic Object Behavior Model and Implementation Based on Computational Reflection

    Institute of Scientific and Technical Information of China (English)

    HE Cheng-wan; HE Fei; HE Ke-qing

    2005-01-01

    A dynamic object behavior model based on computational reflection is proposed. This model consists of function level and meta level, the meta objects in meta level manage the base objects and behaviors in function level, including dynamic binding and unbinding of base object and behavior.We implement this model with RoleJava Language, which is our self linguistic extension of the Java Language. Meta Objects are generated automatically at compile-time, this makes the reflecton mechanism transparent to programmers. Finally an example applying this model to a banking system is presented.

  9. Novel 3-D Object Recognition Methodology Employing a Curvature-Based Histogram

    Directory of Open Access Journals (Sweden)

    Liang-Chia Chen

    2013-07-01

    Full Text Available In this paper, a new object recognition algorithm employing a curvature-based histogram is presented. Recognition of three-dimensional (3-D objects using range images remains one of the most challenging problems in 3-D computer vision due to its noisy and cluttered scene characteristics. The key breakthroughs for this problem mainly lie in defining unique features that distinguish the similarity among various 3-D objects. In our approach, an object detection scheme is developed to identify targets underlining an automated search in the range images using an initial process of object segmentation to subdivide all possible objects in the scenes and then applying a process of object recognition based on geometric constraints and a curvature-based histogram for object recognition. The developed method has been verified through experimental tests for its feasibility confirmation.

  10. Adaptive surrogate model based multi-objective transfer trajectory optimization between different libration points

    Science.gov (United States)

    Peng, Haijun; Wang, Wei

    2016-10-01

    An adaptive surrogate model-based multi-objective optimization strategy that combines the benefits of invariant manifolds and low-thrust control toward developing a low-computational-cost transfer trajectory between libration orbits around the L1 and L2 libration points in the Sun-Earth system has been proposed in this paper. A new structure for a multi-objective transfer trajectory optimization model that divides the transfer trajectory into several segments and gives the dominations for invariant manifolds and low-thrust control in different segments has been established. To reduce the computational cost of multi-objective transfer trajectory optimization, a mixed sampling strategy-based adaptive surrogate model has been proposed. Numerical simulations show that the results obtained from the adaptive surrogate-based multi-objective optimization are in agreement with the results obtained using direct multi-objective optimization methods, and the computational workload of the adaptive surrogate-based multi-objective optimization is only approximately 10% of that of direct multi-objective optimization. Furthermore, the generating efficiency of the Pareto points of the adaptive surrogate-based multi-objective optimization is approximately 8 times that of the direct multi-objective optimization. Therefore, the proposed adaptive surrogate-based multi-objective optimization provides obvious advantages over direct multi-objective optimization methods.

  11. Intra-Inter Triplet Object Interaction Mechanism in Triplet-Based Hierarchical Interconnection Network

    Directory of Open Access Journals (Sweden)

    Shahnawaz Talpur

    2013-07-01

    Full Text Available Object oriented languages usually avoid direct message passing, due to its complicated implementation, though that is the promising way to communicate in concurrently inherited objects. With the advancement in the high performance computing system, interaction between parallel application objects onto physical cores becomes one of the significant issues, which is not fully explored yet. In object oriented programming attribute data is included in objects and their state can be changed using the methods. Objects enable massage passing to other objects interacting with each other. Comprehensive problems can be molded by object-oriented methodology, and solves difficult program running object-oriented programs.Cores communicate with each other through communicator and groups in MPI, but in our reference architecture TBHIN (Triplet Based Hierarchical Interconnection Network, the cores are already faction in Triplets. We propose IITOIM Model to improve the performance with efficient intra-inter triplet cores communication mechanism between the objects in TBHIN

  12. When action turns into words. Activation of motor-based knowledge during categorization of manipulable objects

    DEFF Research Database (Denmark)

    Gerlach, Christian; Law, Ian; Paulson, Olaf B

    2002-01-01

    Functional imaging studies have demonstrated that processing of man-made objects activate the left ventral premotor cortex, which is known to be concerned with motor function. This has led to the suggestion that the comprehension of man-made objects may rely on motor-based knowledge of object uti...

  13. 基于Object-Z的UML对象模型的形式化%The Formalization of Object Model in UML Based on Object-Z

    Institute of Scientific and Technical Information of China (English)

    杨卫东; 蔡希尧

    2000-01-01

    UML is the main visual Object-oriented modeling language currently, which is used widely and supported by most CASE tools. Comparing with traditional Object-oriented methods, LML describes its semantics and syntax more rigouly by using metamodel and Object Constrain Language. But some important concepts in UML are not specified clearly. This paper presents a formal specification for object model of UML, mainly includes the concepts of class, association, association class, aggregation, and inheritance, etc, so that the analyse, verification, refine, and consistent cheking can be applied to object model.

  14. Attribute and topology based change detection in a constellation of previously detected objects

    Energy Technology Data Exchange (ETDEWEB)

    Paglieroni, David W.; Beer, Reginald N.

    2016-01-19

    A system that applies attribute and topology based change detection to networks of objects that were detected on previous scans of a structure, roadway, or area of interest. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, size, elongation, orientation, etc. The topology of the network of previously detected objects is maintained in a constellation database that stores attributes of previously detected objects and implicitly captures the geometrical structure of the network. A change detection system detects change by comparing the attributes and topology of new objects detected on the latest scan to the constellation database of previously detected objects.

  15. Spatial Object Aggregation Based on Data Structure,Local Triangulation and Hierarchical Analyzing Method

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    This paper focuses on the methods and process of spatial aggregation based on semantic and geometric characteristics of spatial objects and relations among the objects with the help of spatial data structure (Formal Data Structure),the Local Constrained Delaunay Triangulations and semantic hierarchy.The adjacent relation among connected objects and unconnected objects has been studied through constrained triangle as elementary processing unit in aggregation operation.The hierarchical semantic analytical matrix is given for analyzing the similarity between objects types and between objects.Several different cases of aggregation have been presented in this paper.

  16. Logical Foundations of Object-Oriented and Frame-Based Languages

    OpenAIRE

    Kifer, Michael; Lausen, Georg; Wu, James

    1990-01-01

    We propose a novel logic, called Frame Logic (abbr., F-logic), that accounts in a clean, declarative fashion for most of the structural aspects of object-oriented and frame-based languages. These features include object identity, complex objects, inheritance, polymorphic types, methods, encapsulation, and others. In a sense, F-logic stands in the same relationship to the object-oriented paradigm as classical predicate calculus stands to relational programming. The syntax of F-logic is higher-...

  17. Point pattern match-based change detection in a constellation of previously detected objects

    Energy Technology Data Exchange (ETDEWEB)

    Paglieroni, David W.

    2016-06-07

    A method and system is provided that applies attribute- and topology-based change detection to objects that were detected on previous scans of a medium. The attributes capture properties or characteristics of the previously detected objects, such as location, time of detection, detection strength, size, elongation, orientation, etc. The locations define a three-dimensional network topology forming a constellation of previously detected objects. The change detection system stores attributes of the previously detected objects in a constellation database. The change detection system detects changes by comparing the attributes and topological consistency of newly detected objects encountered during a new scan of the medium to previously detected objects in the constellation database. The change detection system may receive the attributes of the newly detected objects as the objects are detected by an object detection system in real time.

  18. Robust Online Object Tracking Based on Feature Grouping and 2DPCA

    OpenAIRE

    Ming-Xin Jiang; Jun-Xing Zhang; Min Li

    2013-01-01

    We present an online object tracking algorithm based on feature grouping and two-dimensional principal component analysis (2DPCA). Firstly, we introduce regularization into the 2DPCA reconstruction and develop an iterative algorithm to represent an object by 2DPCA bases. Secondly, the object templates are grouped into a more discriminative image and a less discriminative image by computing the variance of the pixels in multiple frames. Then, the projection matrix is learned according to the m...

  19. An attitude-based reasoning strategy to enhance interaction with augmented objects

    OpenAIRE

    Iglesias Alvarez, Josué; Gómez Cordero, David; Bernardos Barbolla, Ana M.; Casar Corredera, Jose Ramon

    2012-01-01

    This paper describes a mobile-based system to interact with objects in smart spaces, where the offer of resources may be extensive. The underlying idea is to use the augmentation capabilities of the mobile device to enable it as user-object mediator. In particular, the paper details how to build an attitude-based reasoning strategy that facilitates user-object interaction and resource filtering. The strategy prioritizes the available resources depending on the spatial history of the user, his...

  20. Object-Based Image Analysis Beyond Remote Sensing - the Human Perspective

    Science.gov (United States)

    Blaschke, T.; Lang, S.; Tiede, D.; Papadakis, M.; Györi, A.

    2016-06-01

    We introduce a prototypical methodological framework for a place-based GIS-RS system for the spatial delineation of place while incorporating spatial analysis and mapping techniques using methods from different fields such as environmental psychology, geography, and computer science. The methodological lynchpin for this to happen - when aiming to delineate place in terms of objects - is object-based image analysis (OBIA).

  1. Introducing AN Agent-Based Object Recognition Operator for Proximity Analysis

    Science.gov (United States)

    Behzadi, S.; Ali. Alesheikh, A.

    2013-09-01

    Object selection is a basic procedure in a Geographic Information System (GIS). Most current methods for doing so, select objects in two phases: create a simple distance-bounded geometric buffer; and intersect it with available features. This paper introduces a novel and intelligent selection operator based on the autonomy of the agent-based approach. The proposed operator recognizes objects around one object only in one step. In the proposed approach, each point object acts as an agent-automata object. It then senses its vicinity and identifies the surrounding objects. To assess the proposed model, the operator is designed, implemented, and evaluated in a case study. Finally, the results are evaluated and presented in details in the paper.

  2. Semi-automatic classification of glaciovolcanic landforms: An object-based mapping approach based on geomorphometry

    Science.gov (United States)

    Pedersen, G. B. M.

    2016-02-01

    A new object-oriented approach is developed to classify glaciovolcanic landforms (Procedure A) and their landform elements boundaries (Procedure B). It utilizes the principle that glaciovolcanic edifices are geomorphometrically distinct from lava shields and plains (Pedersen and Grosse, 2014), and the approach is tested on data from Reykjanes Peninsula, Iceland. The outlined procedures utilize slope and profile curvature attribute maps (20 m/pixel) and the classified results are evaluated quantitatively through error matrix maps (Procedure A) and visual inspection (Procedure B). In procedure A, the highest obtained accuracy is 94.1%, but even simple mapping procedures provide good results (> 90% accuracy). Successful classification of glaciovolcanic landform element boundaries (Procedure B) is also achieved and this technique has the potential to delineate the transition from intraglacial to subaerial volcanic activity in orthographic view. This object-oriented approach based on geomorphometry overcomes issues with vegetation cover, which has been typically problematic for classification schemes utilizing spectral data. Furthermore, it handles complex edifice outlines well and is easily incorporated into a GIS environment, where results can be edited or fused with other mapping results. The approach outlined here is designed to map glaciovolcanic edifices within the Icelandic neovolcanic zone but may also be applied to similar subaerial or submarine volcanic settings, where steep volcanic edifices are surrounded by flat plains.

  3. UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning

    Directory of Open Access Journals (Sweden)

    J. Fernandez Galarreta

    2014-09-01

    Full Text Available Structural damage assessment is critical after disasters but remains a challenge. Many studies have explored the potential of remote sensing data, but limitations of vertical data persist. Oblique imagery has been identified as more useful, though the multi-angle imagery also adds a new dimension of complexity. This paper addresses damage assessment based on multi-perspective, overlapping, very high resolution oblique images obtained with unmanned aerial vehicles (UAVs. 3-D point-cloud assessment for the entire building is combined with detailed object-based image analysis (OBIA of façades and roofs. This research focuses not on automatic damage assessment, but on creating a methodology that supports the often ambiguous classification of intermediate damage levels, aiming at producing comprehensive per-building damage scores. We identify completely damaged structures in the 3-D point cloud, and for all other cases provide the OBIA-based damage indicators to be used as auxiliary information by damage analysts. The results demonstrate the usability of the 3-D point-cloud data to identify major damage features. Also the UAV-derived and OBIA-processed oblique images are shown to be a suitable basis for the identification of detailed damage features on façades and roofs. Finally, we also demonstrate the possibility of aggregating the multi-perspective damage information at building level.

  4. Video Image Object Tracking Algorithm based on Improved Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    Liping Wang

    2014-05-01

    Full Text Available Since the existing object tracking algorithms are very difficult to adapt the object appearance changes caused by illumination changes, large pose variations, and partial or full occlusions, an object tracking algorithm based on two-dimensional principal component analysis (2DPCA and sparse-representation is proposed in this paper. The tracking algorithm adopts 2DPCA and sparse-representation to establish object appearance model. In order to reduce dimension of object template, incremental subspace updating algorithm is introduced to online update the object template, reduce the requirement of memory space and enhance the precision of object appearance description. Experimental results show the proposed algorithm is robust for image illumination variance and object partial occlusion.

  5. Model of Recommendation System for for Indexing and Retrieving the Learning Object based on Multiagent System

    Directory of Open Access Journals (Sweden)

    Ronaldo Lima Rocha Campos

    2012-07-01

    Full Text Available This paper proposes a multiagent system application model for indexing, retrieving and recommendation learning objects stored in different and heterogeneous repositories. The objects within these repositories are described by filled fields using different metadata standards. The searching mechanism covers several different learning object repositories and the same object can be described in these repositories by the use of different types of fields. Aiming to improve accuracy and coverage in terms of recovering a learning object and improve the signification of the results we propose an information retrieval model based on the multiagent system approach and an ontological model to describe the knowledge domain covered.

  6. Model-based recognition of 3-D objects by geometric hashing technique

    International Nuclear Information System (INIS)

    A model-based object recognition system is developed for recognition of polyhedral objects. The system consists of feature extraction, modelling and matching stages. Linear features are used for object descriptions. Lines are obtained from edges using rotation transform. For modelling and recognition process, geometric hashing method is utilized. Each object is modelled using 2-D views taken from the viewpoints on the viewing sphere. A hidden line elimination algorithm is used to find these views from the wire frame model of the objects. The recognition experiments yielded satisfactory results. (author). 8 refs, 5 figs

  7. Retrieving top-k prestige-based relevant spatial web objects

    DEFF Research Database (Denmark)

    Cao, Xin; Cong, Gao; Jensen, Christian S.

    2010-01-01

    The location-aware keyword query returns ranked objects that are near a query location and that have textual descriptions that match query keywords. This query occurs inherently in many types of mobile and traditional web services and applications, e.g., Yellow Pages and Maps services. Previous...... of prestige-based relevance to capture both the textual relevance of an object to a query and the effects of nearby objects. Based on this, a new type of query, the Location-aware top-k Prestige-based Text retrieval (LkPT) query, is proposed that retrieves the top-k spatial web objects ranked according...... to both prestige-based relevance and location proximity. We propose two algorithms that compute LkPT queries. Empirical studies with real-world spatial data demonstrate that LkPT queries are more effective in retrieving web objects than a previous approach that does not consider the effects of nearby...

  8. Object-based Conditional Random Fields for Road Extraction from Remote Sensing Image

    International Nuclear Information System (INIS)

    To make full use of spatially contextual information and topological information in the procedure of Object-based Image Analysis (OBIA), an object-based conditional random field is proposed and used for road extraction. Objects are produced with an initial segmentation, then their neighbours are constructed. Each object is represented by three kinds of features, including the colour, the gradient of histogram and the texture. Formulating the road extraction as a binary classification problem, a Conditional Random Fields model learns and is used for inference. The experimental results demonstrate that the proposed method is effective

  9. A computer graphics based model for scattering from objects of arbitrary shapes in the optical region

    Science.gov (United States)

    Goel, Narendra S.; Rozehnal, Ivan; Thompson, Richard L.

    1991-01-01

    A computer-graphics-based model, named DIANA, is presented for generation of objects of arbitrary shape and for calculating bidirectional reflectances and scattering from them, in the visible and infrared region. The computer generation is based on a modified Lindenmayer system approach which makes it possible to generate objects of arbitrary shapes and to simulate their growth, dynamics, and movement. Rendering techniques are used to display an object on a computer screen with appropriate shading and shadowing and to calculate the scattering and reflectance from the object. The technique is illustrated with scattering from canopies of simulated corn plants.

  10. Wringing out objects for programming and modeling component-based systems

    OpenAIRE

    Spacek, Petr; Dony, Christophe; Tibermacine, Chouki; Fabresse, Luc

    2013-01-01

    International audience Languages and technologies used to implement component-based software are not component-based, i.e. while the design phase happens in the component world, the programming phase occurs in the object-oriented world. When an object-oriented language is used for the programming stage, then the original component-based design vanish, because component concepts like requirements and architectures are not treated explicitly. This makes it difficult to keep model and its imp...

  11. METHOD OF GROUP OBJECTS FORMING FOR SPACE-BASED REMOTE SENSING OF THE EARTH

    Directory of Open Access Journals (Sweden)

    A. N. Grigoriev

    2015-07-01

    Full Text Available Subject of Research. Research findings of the specific application of space-based optical-electronic and radar means for the Earth remote sensing are considered. The subject matter of the study is the current planning of objects survey on the underlying surface in order to increase the effectiveness of sensing system due to the rational use of its resources. Method. New concept of a group object, stochastic swath and stochastic length of the route is introduced. The overview of models for single, group objects and their parameters is given. The criterion for the existence of the group object based on two single objects is formulated. The method for group objects formation while current survey planning has been developed and its description is presented. The method comprises several processing stages for data about objects with the calculation of new parameters, the stochastic characteristics of space means and validates the spatial size of the object value of the stochastic swath and stochastic length of the route. The strict mathematical description of techniques for model creation of a group object based on data about a single object and onboard special complex facilities in difficult conditions of registration of spatial data is given. Main Results. The developed method is implemented on the basis of modern geographic information system in the form of a software tool layout with advanced tools of processing and analysis of spatial data in vector format. Experimental studies of the forming method for the group of objects were carried out on a different real object environment using the parameters of modern national systems of the Earth remote sensing detailed observation Canopus-B and Resurs-P. Practical Relevance. The proposed models and method are focused on practical implementation using vector spatial data models and modern geoinformation technologies. Practical value lies in the reduction in the amount of consumable resources by means of

  12. An Object-Based Fast Motion Estimation Algorithm in MPEG-4

    Institute of Scientific and Technical Information of China (English)

    SUN Lei; ZHANG Wen-jun; YU Song-yu; LIU Xun

    2006-01-01

    This paper presented an object-based fast motion estimation (ME) algorithm for object-based texture coding in moving picture experts group four (MPEG-4), which takes full advantage of the shape information of video object. Compared with the full search (FS) algorithm, the proposed algorithm can significantly speed the ME process. The speed of ME using the proposed algorithm is faster than that using new three-step search (NTSS), four-step search (4SS), diamond search (DS), and block-based gradient descent search (BBGDS) algorithms with similar motion compensation (MC) errors. The proposed algorithm can be combined with other fast ME algorithm to make the ME process faster.

  13. Laser-based detection and tracking moving objects using data-driven Markov chain Monte Carlo

    OpenAIRE

    Vu, Trung-Dung; Aycard, Olivier

    2009-01-01

    We present a method of simultaneous detection and tracking moving objects from a moving vehicle equipped with a single layer laser scanner. A model-based approach is introduced to interpret the laser measurement sequence by hypotheses of moving object trajectories over a sliding window of time. Knowledge of various aspects including object model, measurement model, motion model are integrated in one theoretically sound Bayesian framework. The data-driven Markov chain Monte Carlo (DDMCMC) tech...

  14. Object-Based Classification of Abandoned Logging Roads under Heavy Canopy Using LiDAR

    OpenAIRE

    Jason Sherba; Leonhard Blesius; Jerry Davis

    2014-01-01

    LiDAR-derived slope models may be used to detect abandoned logging roads in steep forested terrain. An object-based classification approach of abandoned logging road detection was employed in this study. First, a slope model of the study site in Marin County, California was created from a LiDAR derived DEM. Multiresolution segmentation was applied to the slope model and road seed objects were iteratively grown into candidate objects. A road classification accuracy of 86% was achieved using th...

  15. Web Services Based Learning Objects Generator for Device-Independent M-Learning

    OpenAIRE

    Akram Moh. Alkouz

    2006-01-01

    Learning objects, which are the base component of m-learning system, are usually target to modifications in contexts and formats. The device- dependent applications of hand-held devices have proven to be ineffective for creating m-learning courseware. Learning Objects Metadata (LOM) is the most popular standard specification for learning objects but lacks the ability to facilitate platforms descriptions. This paper outlines various aspects of design and implementation of Web Services Oriente...

  16. AN AUTOMATIC SEGMENTATION METHOD FOR MOVING OBJECTS BASED ON THE SPATIAL-TEMPORAL INFORMATION OF VIDEO

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    The new MPEG-4 video coding standard enables content-based functions. In order to support the new standard, frames should be decomposed into Video Object Planes (VOP),each VOP representing a moving object. This paper proposes an image segmentation method to separate moving objects from image sequences. The proposed method utilizes the spatial-temporal information. Spatial segmentation is applied to divide each image into connected areas and to find precise object boundaries of moving objects. To locate moving objects in image sequences,two consecutive image frames in the temporal direction are examined and a hypothesis testing is performed with Neyman-Pearson criterion. Spatial segmentation produces a spatial segmentation mask, and temporal segmentation yields a change detection mask that indicates moving objects and the background. Then spatial-temporal merging can be used to get the final results. This method has been tested on several images. Experimental results show that this segmentation method is efficient.

  17. Object Detection Based on Template Matching through Use of Best-So-Far ABC

    Directory of Open Access Journals (Sweden)

    Anan Banharnsakun

    2014-01-01

    Full Text Available Best-so-far ABC is a modified version of the artificial bee colony (ABC algorithm used for optimization tasks. This algorithm is one of the swarm intelligence (SI algorithms proposed in recent literature, in which the results demonstrated that the best-so-far ABC can produce higher quality solutions with faster convergence than either the ordinary ABC or the current state-of-the-art ABC-based algorithm. In this work, we aim to apply the best-so-far ABC-based approach for object detection based on template matching by using the difference between the RGB level histograms corresponding to the target object and the template object as the objective function. Results confirm that the proposed method was successful in both detecting objects and optimizing the time used to reach the solution.

  18. Object detection based on template matching through use of best-so-far ABC.

    Science.gov (United States)

    Banharnsakun, Anan; Tanathong, Supannee

    2014-01-01

    Best-so-far ABC is a modified version of the artificial bee colony (ABC) algorithm used for optimization tasks. This algorithm is one of the swarm intelligence (SI) algorithms proposed in recent literature, in which the results demonstrated that the best-so-far ABC can produce higher quality solutions with faster convergence than either the ordinary ABC or the current state-of-the-art ABC-based algorithm. In this work, we aim to apply the best-so-far ABC-based approach for object detection based on template matching by using the difference between the RGB level histograms corresponding to the target object and the template object as the objective function. Results confirm that the proposed method was successful in both detecting objects and optimizing the time used to reach the solution. PMID:24812556

  19. Object Detection Based on Template Matching through Use of Best-So-Far ABC

    Science.gov (United States)

    2014-01-01

    Best-so-far ABC is a modified version of the artificial bee colony (ABC) algorithm used for optimization tasks. This algorithm is one of the swarm intelligence (SI) algorithms proposed in recent literature, in which the results demonstrated that the best-so-far ABC can produce higher quality solutions with faster convergence than either the ordinary ABC or the current state-of-the-art ABC-based algorithm. In this work, we aim to apply the best-so-far ABC-based approach for object detection based on template matching by using the difference between the RGB level histograms corresponding to the target object and the template object as the objective function. Results confirm that the proposed method was successful in both detecting objects and optimizing the time used to reach the solution. PMID:24812556

  20. Object tracking and creation of linking information for distributed movie-based web-browsing system

    Science.gov (United States)

    Hiraiwa, Atsunobu; Fuse, Keisuke; Komatsu, Naohisa; Komiya, Kazumi; Ikeda, Hiroaki

    1998-12-01

    This paper proposes a new approach to automatically extract an accurate object from video streams. The new approach provides a useful tool creating linking information for a distributed movie-based Web-browsing system, and consists of a skip- labeling algorithm for feature-based segmentation, and a shrink-merge tracking algorithm for tracking an object. This skip-labeling algorithm can be used to segment an image into integrated regions of the same feature. The segmented regions belong to such a texture area as waves or forest. The shrink- merge tracking algorithm is executed, based on the time continuity of moving-objects, using morphological image processing, such as dilation and erosion. The dilation and erosion are repeatedly executed using the projection processing in which the object area in a next frame is derived from the object area in a current frame. The shrink-merge tracking algorithm can also project the area of a rotating- object in a current frame on the rotating-object containing the newly appearing regions in the next frame. The newly automated object extraction method works satisfactorily for the objects which move non-linearly within the video streams including MPEG and Motion JPEG, and works satisfactorily in approximately 450 frames, each with a full frame size of 704 X 480 pixels at video frame rate of 30 fps. This paper finally demonstrates that object-based linking information for a movie-based Web-browsing system contains information of objects obtained by the fully automated extraction from video- streams.

  1. A Novel Abandoned Object Detection System Based on Three-Dimensional Image Information

    Directory of Open Access Journals (Sweden)

    Yiliang Zeng

    2015-03-01

    Full Text Available A new idea of an abandoned object detection system for road traffic surveillance systems based on three-dimensional image information is proposed in this paper to prevent traffic accidents. A novel Binocular Information Reconstruction and Recognition (BIRR algorithm is presented to implement the new idea. As initial detection, suspected abandoned objects are detected by the proposed static foreground region segmentation algorithm based on surveillance video from a monocular camera. After detection of suspected abandoned objects, three-dimensional (3D information of the suspected abandoned object is reconstructed by the proposed theory about 3D object information reconstruction with images from a binocular camera. To determine whether the detected object is hazardous to normal road traffic, road plane equation and height of suspected-abandoned object are calculated based on the three-dimensional information. Experimental results show that this system implements fast detection of abandoned objects and this abandoned object system can be used for road traffic monitoring and public area surveillance.

  2. 逆合成孔径成像激光雷达微多普勒效应分析及特征提取%Analysis of Micro-Doppler Effect and Feature Extraction of Target in Inverse Synthetic Aperture Imaging Ladar

    Institute of Scientific and Technical Information of China (English)

    何劲; 张群; 罗迎; 杨小优

    2011-01-01

    研究了基于逆合成孔径成像激光雷达的目标微多普勒效应,分析了激光信号高载频和大带宽对目标微动点一维距离像的影响,在此基础上建立了相应的微多普勒特征参数方程并讨论了快时间对微多普勒效应的影响.针对逆合成孔径成像激光雷达系统目标微多普勒效应的特点,提出了一种结合二值数学形态学腐蚀膨胀运算和推广Hough变换的目标微多普勒特征提取方法.仿真实验验证了文中微多普勒效应理论分析和微多普勒特征提取算法的正确性,并证明了逆合成孔径成像激光雷达对厘米或毫米量级微动观测的有效性.%The micro-Doppler effect based on the inverse synthetic imaging ladar is studied, and the influence of the high carrier frequency and the bandwidth of laser signal on the range profiles is also analyzed.Furthermore, the corresponding parameters equation of micro-Doppler is constructed and then the influence of the fast-time on the micro-Doppler effect is also discussed. Based on the Extended Hough Transform and the erosion and dilation operations in binary mathematical morphology, a novel extraction method of micro-Doppler effect is proposed for the inverse synthetic imaging ladar accordingly. The simulations are given to verify the theoretical derivation and the validity of the proposed method. In addition, the validity of the measurement of the inverse synthetic imaging ladar for the micro-motion at the centimeter-level or the millimeter-level is also illustrated in the simulations.

  3. Visual Statistical Learning Based on the Perceptual and Semantic Information of Objects

    Science.gov (United States)

    Otsuka, Sachio; Nishiyama, Megumi; Nakahara, Fumitaka; Kawaguchi, Jun

    2013-01-01

    Five experiments examined what is learned based on the perceptual and semantic information of objects in visual statistical learning (VSL). In the familiarization phase, participants viewed a sequence of line drawings and detected repetitions of various objects. In a subsequent test phase, they watched 2 test sequences (statistically related…

  4. Nonretinotopic perception of orientation: Temporal integration of basic features operates in object-based coordinates.

    Science.gov (United States)

    Wutz, Andreas; Drewes, Jan; Melcher, David

    2016-08-01

    Early, feed-forward visual processing is organized in a retinotopic reference frame. In contrast, visual feature integration on longer time scales can involve object-based or spatiotopic coordinates. For example, in the Ternus-Pikler (T-P) apparent motion display, object identity is mapped across the object motion path. Here, we report evidence from three experiments supporting nonretinotopic feature integration even for the most paradigmatic example of retinotopically-defined features: orientation. We presented observers with a repeated series of T-P displays in which the perceived rotation of Gabor gratings indicates processing in either retinotopic or object-based coordinates. In Experiment 1, the frequency of perceived retinotopic rotations decreased exponentially for longer interstimulus intervals (ISIs) between T-P display frames, with object-based percepts dominating after about 150-250 ms. In a second experiment, we show that motion and rotation judgments depend on the perception of a moving object during the T-P display ISIs rather than only on temporal factors. In Experiment 3, we cued the observers' attentional state either toward a retinotopic or object motion-based reference frame and then tracked both the observers' eye position and the time course of the perceptual bias while viewing identical T-P display sequences. Overall, we report novel evidence for spatiotemporal integration of even basic visual features such as orientation in nonretinotopic coordinates, in order to support perceptual constancy across self- and object motion.

  5. Online decoding of object-based attention using real-time fMRI

    NARCIS (Netherlands)

    Niazi, Adnan M.; Broek, van den Philip L.C.; Klanke, Stefan; Barth, Markus; Poel, Mannes; Desain, Peter; Gerven, van Marcel A.J.

    2014-01-01

    Visual attention is used to selectively filter relevant information depending on current task demands and goals. Visual attention is called object-based attention when it is directed to coherent forms or objects in the visual field. This study used real-time functional magnetic resonance imaging for

  6. Instructional Design Issues in Computer-Based Reading: Reinforcement and Objectives.

    Science.gov (United States)

    Blanchard, Jay S.

    1987-01-01

    This review of cognitive development research in the area of computer-based reading instruction focuses on reinforcement and instructional objectives. Differences between extrinsic and intrinsic reinforcement and motivation are discussed, types of objectives and learner characteristics are described, and implications for instructional design are…

  7. An Objective Structured Clinical Examination to Assess Problem-Based Learning

    OpenAIRE

    Salinitri, Francine D.; O'Connell, Mary Beth; Garwood, Candice L.; Lehr, Victoria Tutag; Abdallah, Karina

    2012-01-01

    Objectives. To compare pharmacy students’ performance on an objective structured clinical examination (OSCE) to their performance on a written examination for the assessment of problem-based learning (PBL); and to determine students’ and faculty members’ perceptions of OSCEs for PBL evaluations.

  8. VIDEO OBJECT SEGMENTATION BY 2-D MESH-BASED MOTION ANALYSIS

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    Video object extraction is a key technology in content-based video coding. A novel video object extracting algorithm by two Dimensional (2-D) mesh-based motion analysis is proposed in this paper. Firstly, a 2-D mesh fitting the original frame image is obtained via feature detection algorithm.Then, higher order statistics motion analysis is applied on the 2-D mesh representation to get an initial motion detection mask. After post-processing, the final segmenting mask is quickly obtained. And hence the video object is effectively extracted. Experimental results show that the proposed algorithm combines the merits of mesh-based segmenting algorithms and pixel-based segmenting algorithms, and hereby achieves satisfactory subjective and objective performance while dramatically increasing the segmenting speed.

  9. Research Letter: Sensor-Based Systems and the Objective Measure of Physical Activity

    OpenAIRE

    Tuso, Phillip

    2015-01-01

    Similar to medication adherence, objective measures of physical activity may allow physicians to improve activity rates among individual patients and patient populations, which should improve health care outcomes. Sensor-based systems may become a best practice for objective measurement of physical activity and the management of physical activity programs. Given the ease of tracking with these new devices and the ability to upload information automatically, a sensor-based system has the poten...

  10. Home-Explorer: Ontology-Based Physical Artifact Search and Hidden Object Detection System

    Directory of Open Access Journals (Sweden)

    Bin Guo

    2008-01-01

    Full Text Available A new system named Home-Explorer that searches and finds physical artifacts in a smart indoor environment is proposed. The view on which it is based is artifact-centered and uses sensors attached to the everyday artifacts (called smart objects in the real world. This paper makes two main contributions: First, it addresses, the robustness of the embedded sensors, which is seldom discussed in previous smart artifact research. Because sensors may sometimes be broken or fail to work under certain conditions, smart objects become hidden ones. However, current systems provide no mechanism to detect and manage objects when this problem occurs. Second, there is no common context infrastructure for building smart artifact systems, which makes it difficult for separately developed applications to interact with each other and uneasy for them to share and reuse knowledge. Unlike previous systems, Home-Explorer builds on an ontology-based knowledge infrastructure named Sixth-Sense, which makes it easy for the system to interact with other applications or agents also based on this ontology. The hidden object problem is also reflected in our ontology, which enables Home-Explorer to deal with both smart objects and hidden objects. A set of rules for deducing an object's status or location information and for locating hidden objects are described and evaluated.

  11. [Competency-based medical education: National Catalogue of Learning Objectives in surgery].

    Science.gov (United States)

    Kadmon, M; Bender, M J; Adili, F; Arbab, D; Heinemann, M K; Hofmann, H S; König, S; Küper, M A; Obertacke, U; Rennekampff, H-O; Rolle, U; Rücker, M; Sader, R; Tingart, M; Tolksdorf, M M; Tronnier, V; Will, B; Walcher, F

    2013-04-01

    Competency-based medical education is a prerequisite to prepare students for the medical profession. A mandatory professional qualification framework is a milestone towards this aim. The National Competency-based Catalogue of Learning Objectives for Undergraduate Medical Education (NKLM) of the German Medical Faculty Association (MFT) and the German Medical Association will constitute a basis for a core curriculum of undergraduate medical training. The Surgical Working Group on Medical Education (CAL) of the German Association of Surgeons (DGCH) aims at formulating a competency-based catalogue of learning objectives for surgical undergraduate training to bridge the gap between the NKLM and the learning objectives of individual medical faculties. This is intended to enhance the prominence and visibility of the surgical discipline in the context of medical education. On the basis of different faculty catalogues of learning objectives, the catalogue of learning objectives of the German Association of Orthopedics and Orthopedic Surgery and the Swiss Catalogue of Learning Objectives representatives of all German Surgical Associations cooperated towards a structured selection process of learning objectives and the definition of levels and areas of competencies. After completion the catalogue of learning objectives will be available online on the webpage of the DGCH.

  12. Visual Tracking Based on the Adaptive Color Attention Tuned Sparse Generative Object Model.

    Science.gov (United States)

    Tian, Chunna; Gao, Xinbo; Wei, Wei; Zheng, Hong

    2015-12-01

    This paper presents a new visual tracking framework based on an adaptive color attention tuned local sparse model. The histograms of sparse coefficients of all patches in an object are pooled together according to their spatial distribution. A particle filter methodology is used as the location model to predict candidates for object verification during tracking. Since color is an important visual clue to distinguish objects from background, we calculate the color similarity between objects in the previous frames and the candidates in current frame, which is adopted as color attention to tune the local sparse representation-based appearance similarity measurement between the object template and candidates. The color similarity can be calculated efficiently with hash coded color names, which helps the tracker find more reliable objects during tracking. We use a flexible local sparse coding of the object to evaluate the degeneration degree of the appearance model, based on which we build a model updating mechanism to alleviate drifting caused by temporal varying multi-factors. Experiments on 76 challenging benchmark color sequences and the evaluation under the object tracking benchmark protocol demonstrate the superiority of the proposed tracker over the state-of-the-art methods in accuracy. PMID:26390460

  13. General moving objects recognition method based on graph embedding dimension reduction algorithm

    Institute of Scientific and Technical Information of China (English)

    Yi ZHANG; Jie YANG; Kun LIU

    2009-01-01

    Effective and robust recognition and tracking of objects are the key problems in visual surveillance systems. Most existing object recognition methods were designed with particular objects in mind. This study presents a general moving objects recognition method using global features of targets. Targets are extracted with an adaptive Gaussian mixture model and their silhouette images are captured and unified. A new objects silhouette database is built to provide abundant samples to train the subspace feature. This database is more convincing than the previous ones. A more effective dimension reduction method based on graph embedding is used to obtain the projection eigenvector. In our experiments, we show the effective performance of our method in addressing the moving objects recognition problem and its superiority compared with the previous methods.

  14. Differences between predictions of how a reflection behaves based on the behaviour of an object, and how an object behaves based on the behaviour of its reflection.

    Science.gov (United States)

    Bianchi, Ivana; Bertamini, Marco; Savardi, Ugo

    2015-10-01

    We studied adults' understanding of the relationship between objects and their reflections. Two studies investigated whether adults performed in a similar way when asked to predict the movement of a reflection in a flat mirror based on the movement of the corresponding object or, vice versa, predict the movement of the material object based on the movement of its reflection. We used simple movements in the experiments: movements in a straight line at various angles with respect to the mirror. Despite the simplicity of the task, some of the participants made incorrect predictions in a percentage of cases ranging from 0% to 54%, depending on the angle. Asymmetries between the two directions of prediction emerged, in particular in terms of types of error. Results confirmed a cognitive difference between deriving the reflected (virtual) world from the "real" (material) world and vice versa. In particular the expectation that something will be opposite in a mirror is more salient when people imagine how a reflection will be with respect to the material world rather than when they imagine how the material world will be with respect to a reflection. PMID:26322914

  15. Spatio-temporal Compensation Based Object Detection for Video Surveillance Systems

    Institute of Scientific and Technical Information of China (English)

    LI Ren-jie; YU Song-yu; XIONG Hong-kai

    2008-01-01

    Moving object detection in video surveillance is an important step.This paper addresses an automatic object detection algorithm based on spatio-temporal compensation for video surveillance.Temporal difference of the pairs of two frames with a k-frame distance is utilized to obtain coarse object masks.Usually,object regions in these coarse masks have discontinuous boundaries and some holes.Region growing with the distance constraint is proposed to compensate these coarse object regions in spatial domain,followed by filling holes.The added distance constraint can prevent object regions from growing infinitely.The proposed fining holes method is simple and effective.To solve the temporarily stopping problem of moving objects,temporal compensation is proposed to compensate the object mask by utilizing temporal coherence of moving objects in temporal domain.The proposed detection algorithm can extract moving objects as completely as possible.Experimental results have successfully demonstrated the validity of the proposed algorithm.

  16. Automatic Multi-Level Thresholding Segmentation Based on Multi-Objective Optimization

    Directory of Open Access Journals (Sweden)

    L. DJEROU,

    2012-01-01

    Full Text Available In this paper, we present a new multi-level image thresholding technique, called Automatic Threshold based on Multi-objective Optimization "ATMO" that combines the flexibility of multi-objective fitness functions with the power of a Binary Particle Swarm Optimization algorithm "BPSO", for searching the "optimum" number of the thresholds and simultaneously the optimal thresholds of three criteria: the between-class variances criterion, the minimum error criterion and the entropy criterion. Some examples of test images are presented to compare our segmentation method, based on the multi-objective optimization approach with Otsu’s, Kapur’s and Kittler’s methods. Our experimental results show that the thresholding method based on multi-objective optimization is more efficient than the classical Otsu’s, Kapur’s and Kittler’s methods.

  17. Multi-view space object recognition and pose estimation based on kernel regression

    Institute of Scientific and Technical Information of China (English)

    Zhang Haopeng; Jiang Zhiguo

    2014-01-01

    The application of high-performance imaging sensors in space-based space surveillance systems makes it possible to recognize space objects and estimate their poses using vision-based methods. In this paper, we proposed a kernel regression-based method for joint multi-view space object recognition and pose estimation. We built a new simulated satellite image dataset named BUAA-SID 1.5 to test our method using different image representations. We evaluated our method for recognition-only tasks, pose estimation-only tasks, and joint recognition and pose estimation tasks. Experimental results show that our method outperforms the state-of-the-arts in space object recognition, and can recognize space objects and estimate their poses effectively and robustly against noise and lighting conditions.

  18. Object Class Detection and Classification using Multi Scale Gradient and Corner Point based Shape Descriptors

    OpenAIRE

    Fernando, Basura; Karaoglu, Sezer; Saha, Sajib Kumar

    2015-01-01

    This paper presents a novel multi scale gradient and a corner point based shape descriptors. The novel multi scale gradient based shape descriptor is combined with generic Fourier descriptors to extract contour and region based shape information. Shape information based object class detection and classification technique with a random forest classifier has been optimized. Proposed integrated descriptor in this paper is robust to rotation, scale, translation, affine deformations, noisy contour...

  19. LABRADOR: a learning autonomous behavior-based robot for adaptive detection and object retrieval

    Science.gov (United States)

    Yamauchi, Brian; Moseley, Mark; Brookshire, Jonathan

    2013-01-01

    As part of the TARDEC-funded CANINE (Cooperative Autonomous Navigation in a Networked Environment) Program, iRobot developed LABRADOR (Learning Autonomous Behavior-based Robot for Adaptive Detection and Object Retrieval). LABRADOR was based on the rugged, man-portable, iRobot PackBot unmanned ground vehicle (UGV) equipped with an explosives ordnance disposal (EOD) manipulator arm and a custom gripper. For LABRADOR, we developed a vision-based object learning and recognition system that combined a TLD (track-learn-detect) filter based on object shape features with a color-histogram-based object detector. Our vision system was able to learn in real-time to recognize objects presented to the robot. We also implemented a waypoint navigation system based on fused GPS, IMU (inertial measurement unit), and odometry data. We used this navigation capability to implement autonomous behaviors capable of searching a specified area using a variety of robust coverage strategies - including outward spiral, random bounce, random waypoint, and perimeter following behaviors. While the full system was not integrated in time to compete in the CANINE competition event, we developed useful perception, navigation, and behavior capabilities that may be applied to future autonomous robot systems.

  20. A Framework-Based Environment for Object-Oriented Scientific Codes

    Directory of Open Access Journals (Sweden)

    Robert A. Ballance

    1993-01-01

    Full Text Available Frameworks are reusable object-oriented designs for domain-specific programs. In our estimation, frameworks are the key to productivity and reuse. However, frameworks require increased support from the programming environment. A framework-based environment must include design aides and project browsers that can mediate between the user and the framework. A framework-based approach also places new requirements on conventional tools such as compilers. This article explores the impact of object-oriented frameworks upon a programming environment, in the context of object-oriented finite element and finite difference codes. The role of tools such as design aides and project browsers is discussed, and the impact of a framework-based approach upon compilers is examined. Examples are drawn from our prototype C++ based environment.

  1. Recognition of 3-D objects based on Markov random field models

    Institute of Scientific and Technical Information of China (English)

    HUANG Ying; DING Xiao-qing; WANG Sheng-jin

    2006-01-01

    The recognition of 3-D objects is quite a difficult task for computer vision systems.This paper presents a new object framework,which utilizes densely sampled grids with different resolutions to represent the local information of the input image.A Markov random field model is then created to model the geometric distribution of the object key nodes.Flexible matching,which aims to find the accurate correspondence map between the key points of two images,is performed by combining the local similarities and the geometric relations together using the highest confidence first method.Afterwards,a global similarity is calculated for object recognition. Experimental results on Coil-100 object database,which consists of 7 200 images of 100 objects,are presented.When the numbers of templates vary from 4,8,18 to 36 for each object,and the remaining images compose the test sets,the object recognition rates are 95.75 %,99.30 %,100.0 % and 100.0 %,respectively.The excellent recognition performance is much better than those of the other cited references,which indicates that our approach is well-suited for appearance-based object recognition.

  2. An object oriented framework of EPICS for MicroTCA based control system

    International Nuclear Information System (INIS)

    EPICS (Experimental Physics and Industrial Control System) is a distributed control system platform which has been widely used for large scientific devices control like particle accelerators and fusion plant. EPICS has introduced object oriented (C++) interfaces to most of the core services. But the major part of EPICS, the run-time database, only provides C interfaces, which is hard to involve the EPICS record concerned data and routines in the object oriented architecture of the software. This paper presents an object oriented framework which contains some abstract classes to encapsulate the EPICS record concerned data and routines in C++ classes so that full OOA (Objected Oriented Analysis) and OOD (Object Oriented Design) methodologies can be used for EPICS IOC design. We also present a dynamic device management scheme for the hot swap capability of the MicroTCA based control system. (authors)

  3. Brazilian Proposal for Agent-Based Learning Objects Metadata Standard - OBAA

    Science.gov (United States)

    Vicari, Rosa Maria; Ribeiro, Alexandre; da Silva, Júlia Marques Carvalho; Santos, Elder Rizzon; Primo, Tiago; Bez, Marta

    This paper presents the Agent Based Learning Objects - OBAA standard proposal. The main goal of the research was to establish a standardized specification of the technical and functional requirements of interoperable learning objects. In our context, interoperability regards the operation of the content inside Web, Digital TV and mobile environments, supporting accessibility and pedagogical issues. In this proposal it has been explored the convergence among the multi-agent systems, learning object and ubiquitous computing technologies, allowing the authoring, storage and recovery of learning object in varied contexts and through different digital platforms. The result of this research was the definition of the OBAA proposal containing the requirements, specifications and architectures that will compose the Brazilian standard for the management, transmission, storage, search, editing and use of interoperable learning object.

  4. Techniques for efficient road-network-based tracking of moving objects

    DEFF Research Database (Denmark)

    Civilis, A.; Jensen, Christian Søndergaard; Pakalnis, Stardas

    2005-01-01

    With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects....... The main issue considered is how to represent the location of a moving object in a database so that tracking can be done with as few updates as possible. The paper proposes to use the road network within which the objects are assumed to move for predicting their future positions. The paper presents...... algorithms that modify an initial road-network representation, so that it works better as a basis for predicting an object's position; it proposes to use known movement patterns of the object, in the form of routes; and it proposes to use acceleration profiles together with the routes. Using real GPS...

  5. Techniques for Efficient Tracking of Road-Network-Based Moving Objects

    DEFF Research Database (Denmark)

    Civilis, Alminas; Jensen, Christian Søndergaard; Saltenis, Simonas

    With the continued advances in wireless communications, geo-positioning, and consumer electronics, an infrastructure is emerging that enables location-based services that rely on the tracking of the continuously changing positions of entire populations of service users, termed moving objects....... The main issue considered is how to represent the location of a moving object in a database so that tracking can be done with as few updates as possible. The paper proposes to use the road network within which the objects are assumed to move for predicting their future positions. The paper presents...... algorithms that modify an initial road-network representation, so that it works better as a basis for predicting an object's position; it proposes to use known movement patterns of the object, in the form of routes; and it proposes to use acceleration profiles together with the routes. Using real GPS...

  6. Use of Image Based Modelling for Documentation of Intricately Shaped Objects

    Science.gov (United States)

    Marčiš, M.; Barták, P.; Valaška, D.; Fraštia, M.; Trhan, O.

    2016-06-01

    In the documentation of cultural heritage, we can encounter three dimensional shapes and structures which are complicated to measure. Such objects are for example spiral staircases, timber roof trusses, historical furniture or folk costume where it is nearly impossible to effectively use the traditional surveying or the terrestrial laser scanning due to the shape of the object, its dimensions and the crowded environment. The actual methods of digital photogrammetry can be very helpful in such cases with the emphasis on the automated processing of the extensive image data. The created high resolution 3D models and 2D orthophotos are very important for the documentation of architectural elements and they can serve as an ideal base for the vectorization and 2D drawing documentation. This contribution wants to describe the various usage of image based modelling in specific interior spaces and specific objects. The advantages and disadvantages of the photogrammetric measurement of such objects in comparison to other surveying methods are reviewed.

  7. Key Object Discovery and Tracking Based on Context-Aware Saliency

    Directory of Open Access Journals (Sweden)

    Geng Zhang

    2013-01-01

    Full Text Available In this paper, we propose an online key object discovery and tracking system based on visual saliency. We formulate the problem as a temporally consistent binary labelling task on a conditional random field and solve it by using a particle filter. We also propose a context‐aware saliency measurement, which can be used to improve the accuracy of any static or dynamic saliency maps. Our refined saliency maps provide clearer indications as to where the key object lies. Based on good saliency cues, we can further segment the key object inside the resulting bounding box, considering the spatial and temporal context. We tested our system extensively on different video clips. The results show that our method has significantly improved the saliency maps and tracks the key object accurately.

  8. Affordance estimation for vision-based object replacement on a humanoid robot

    DEFF Research Database (Denmark)

    Mustafa, Wail; Wächter, Mirko; Szedmak, Sandor;

    2016-01-01

    In this paper, we address the problem of finding replacements of missing objects, involved in the execution of manipulation tasks. Our approach is based on estimating functional affordances for the unknown objects in order to propose replacements. We use a vision-based affordance estimation system...... large-scale datasets. The results indicate that the system is able to successfully predict the affordances of novel objects. We also implement our system on a humanoid robot and demonstrate the affordance estimation in a real scene....... utilizing object-wise global features and a multi-label learning method. This method also associates confidence values to the estimated affordances. We evaluate our approach on kitchen-related manipulation affordances. The evaluation also includes testing different scenarios for training the system using...

  9. Comparison of Planar Parallel Manipulator Architectures based on a Multi-objective Design Optimization Approach

    OpenAIRE

    Chablat, Damien; Caro, Stéphane; Ur-Rehman, Raza; Wenger, Philippe

    2010-01-01

    This paper deals with the comparison of planar parallel manipulator architectures based on a multi-objective design optimization approach. The manipulator architectures are compared with regard to their mass in motion and their regular workspace size, i.e., the objective functions. The optimization problem is subject to constraints on the manipulator dexterity and stiffness. For a given external wrench, the displacements of the moving platform have to be smaller than given values throughout t...

  10. Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet

    OpenAIRE

    Edmund T eRolls

    2012-01-01

    Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is ...

  11. Photo-based participatory research : exploring the objectives of visiting a historical district

    OpenAIRE

    Naoi, Taketo; Yamada, Takanobu; Iijima, Shoji; Kumazawa, Takayuki

    2013-01-01

    This study quantitatively investigates relationships between visitors’ objectives for visiting a historical district,using photo-based participatory research. Thirty Japanese undergraduates majoring in commerce and 27 Japaneseadults with an interest in architecture and/or town planning were asked to photograph noteworthy settings in ahistorical district and rate to what extent each setting portrayed nine objectives on scales. The ratings weresubjected to exploratory and confirmatory factor an...

  12. Multi-Objective Optimization and Analysis Model of Sintering Process Based on BP Neural Network

    Institute of Scientific and Technical Information of China (English)

    ZHANG Jun-hong; XIE An-guo; SHEN Feng-man

    2007-01-01

    A multi-objective optimization and analysis model of the sintering process based on BP neural network is presented. Genetic algorithms are combined to simplify the BP neural network, which can reduce the learning time and increase the forecasting accuracy of the network model. This model has been experimented in the sintering process, and the production cost, the energy consumption, the quality (revolving intensity), and the output are considered at the same time. Moreover, the relation between some factors and the multi-objectives has been analyzed, and the results are consistent with the process. Different objectives are emphasized at different practical periods, and this can provide a theoretical basis for the manager.

  13. A Methodology to Evaluate Object oriented Software Systems Using Change Requirement Traceability Based on Impact Analysis

    Directory of Open Access Journals (Sweden)

    Sunil T. D

    2014-06-01

    Full Text Available It is a well known fact that software maintenance plays a major role and finds importance in software development life cycle. As object - oriented programming has become the standard, it is very important to understand the problems of maintaining object -oriented software systems. This paper aims at evaluating object - oriented software system through change requirement traceability – based impact analysis methodology for non functional requirements using functional requirements . The major issues have been related to change impact algorithms and inheritance of functionality.

  14. Video segmentation based on the presence and/or absence of moving objects

    Science.gov (United States)

    Nitsuwat, Supot; Jin, Jesse S.; Hudson, M. B.

    1999-08-01

    Video clip is the dominant component of multimedia system. However, video data are voluminous. An effective and efficient visual data management system is highly desired. Recent technology in digital video processing has moved to 'content-based' storage and retrieval. To detect meaningful area/region, using only production and camera operation- based detection is not enough. The contents of a video also have to be considered. The basic idea of this scheme is that if we can distinguish individual objects in the whole video sequence, we would be able to capture the changes in content throughout the sequences. Among many object features, motion content has been widely used as an important key in video storage and retrieval systems. Therefore, through motion- based representation, this paper will investigate an algorithm for sub-shot extraction and key-frame selection. From a given video sequence, first we segment the sequence into shots by using some of the production and camera operation-based detection techniques. Then, from the beginning of each shot, we calculate optical flow vectors by using complex wavelet phase-matching-based method on a pair of successive frames. Next, we segment each moving object based on these vectors using clustering in a competitive agglomeration scheme and represent them into a number of layers. After separating moving object(s) from each other for every frame in this shot, we extract sub-shots and select key-frames by using information about the presence and absence of moving object in each layer. Finally, these key-frames and sub-shots have been used to represent the whole video in panoramic mosaic-based representation form. Experimental results showing the significance of the proposed method are also provided.

  15. A drifting trajectory prediction model based on object shape and stochastic mo-tion features

    Institute of Scientific and Technical Information of China (English)

    王胜正; 聂皓冰; 施朝健

    2014-01-01

    There is a huge demand to develop a method for marine search and rescue (SAR) operators automatically predicting the most probable searching area of the drifting object. This paper presents a novel drifting prediction model to improve the accuracy of the drifting trajectory computation of the sea-surface objects. First, a new drifting kinetic model based on the geometry characteristics of the objects is proposed that involves the effects of the object shape and stochastic motion features in addition to the traditional factors of wind and currents. Then, a computer simulation-based method is employed to analyze the stochastic motion features of the drifting objects, which is applied to estimate the uncertainty parameters of the stochastic factors of the drifting objects. Finally, the accuracy of the model is evaluated by comparison with the flume experimental results. It is shown that the proposed method can be used for various shape objects in the drifting trajectory prediction and the maritime search and rescue decision-making system.

  16. Investigation of Vision-based Underwater Object Detection with Multiple Datasets

    Directory of Open Access Journals (Sweden)

    Dario Lodi Rizzini

    2015-06-01

    Full Text Available In this paper, we investigate the potential of vision-based object detection algorithms in underwater environments using several datasets to highlight the issues arising in different scenarios. Underwater computer vision has to cope with distortion and attenuation due to light propagation in water, and with challenging operating conditions. Scene segmentation and shape recognition in a single image must be carefully designed to achieve robust object detection and to facilitate object pose estimation. We describe a novel multi-feature object detection algorithm conceived to find human-made artefacts lying on the seabed. The proposed method searches for a target object according to a few general criteria that are robust to the underwater context, such as salient colour uniformity and sharp contours. We assess the performance of the proposed algorithm across different underwater datasets. The datasets have been obtained using stereo cameras of different quality, and diverge for the target object type and colour, acquisition depth and conditions. The effectiveness of the proposed approach has been experimentally demonstrated. Finally, object detection is discussed in connection with the simple colour-based segmentation and with the difficulty of tri-dimensional processing on noisy data.

  17. DYNAMIC LAYOUT ADJUSTMENT AND NAVIGATION FOR ENTERPRISE GIS BASED ON OBJECT MARK RECOGNITION

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    In this paper a new method is developed to make a dynamic layout adjustment and navigation for enterprise Geographic Information System(GIS) based on object mark recognition. The extraction of object mark images is based on some morphological structural patterns, which are described by morphological structural points, contour property, and other geometrical data in a binary image of enterprise geographic information map. Some pre-processing methods, contour smooth following, linearization and extraction patterns of structural points, are introduced. If any special object is selected to make a decision in a GIS map, the all information around it will be obtained. That is, we need to investigate similar object enterprises around selected region to analyse whether it is necessary for establishing the object enterprise at that place. To further navigate GIS map, we need to move from one region to another. Each time a region is formed and displayed based on the user′ s focus. If a focus point of a map is selected, in terms of extracted object mark image, a dynamic layout and navigation diagram is constructed. When the user changes the focus (i.e. click a node in the navigation mode), a new sub-diagram is formed by dropping old nodes and adding new nodes. The prototype system provides effective interfaces that support GIS image navigation, detailed local image/map viewing, and enterprise information browsing.

  18. Edge detection based on object tree image representation and wavelet transform

    Institute of Scientific and Technical Information of China (English)

    屈彦呈; 王常虹; 庄显义

    2003-01-01

    In applications such as image retrieval and recognition, precise edge detection for interested regions plays a decisive role. Existing methods generally take little care about local characteristics, or become time-consuming if every detail is considered. In the paper, a new method is put forward based on the combination of effective image representation and multiscale wavelet analysis. A new object tree image representation is introduced. Then a series of object trees are constructed based on wavelet transform modulus maxima at different scales in descending order. Computation is only needed for interested regions. Implementation steps are also given with an illustrative example.

  19. JTpack90: A parallel, object-based, Fortran 90 linear algebra package

    Energy Technology Data Exchange (ETDEWEB)

    Turner, J.A.; Kothe, D.B. [Los Alamos National Lab., NM (United States); Ferrell, R.C. [Cambridge Power Computing Associates, Ltd., Brookline, MA (United States)

    1997-03-01

    The authors have developed an object-based linear algebra package, currently with emphasis on sparse Krylov methods, driven primarily by needs of the Los Alamos National Laboratory parallel unstructured-mesh casting simulation tool Telluride. Support for a number of sparse storage formats, methods, and preconditioners have been implemented, driven primarily by application needs. They describe the object-based Fortran 90 approach, which enhances maintainability, performance, and extensibility, the parallelization approach using a new portable gather/scatter library (PGSLib), current capabilities and future plans, and present preliminary performance results on a variety of platforms.

  20. Multi Objective Test Suite Reduction for GUI Based Software Using NSGA-II

    Directory of Open Access Journals (Sweden)

    Neha Chaudhary

    2016-08-01

    Full Text Available Regression Testing is a performed to ensure modified code does not have any unintended side effect on the software. If regression testing is performed with retest-all method it will be very time consuming as testing activity. Therefore test suite reduction methods are used to reduce the size of original test suite. Objective of test suite reduction is to reduce those test cases which are redundant or less important in their fault revealing capability. Test suite reduction can only be used when time is critical to run all test cases and selective testing can only be done. Various methods exist in the literature related to test suite reduction of traditional software. Most of the methods are based of single objective optimization. In case of multi objective optimization of test suite, usually researchers assign different weight values to different objectives and combine them as single objective. However in test suite reduction multiple Pareto-optimal solutions are present, it is difficult to select one test case over other. Since GUI based software is our concern there exist very few reduction techniques and none of them consider multiple objective based reduction. In this work we propose a new test suite reduction technique based on two objectives, event weight and number of faults identified by test case. We evaluated our results for 2 different applications and we achieved 20% reduction in test suite size for both applications. In Terp Paint 3.0 application compromise 15.6% fault revealing capability and for Notepad 11.1% fault revealing capability is reduced.

  1. A hospital information system based on Common Object Request Broker Architecture (CORBA) for exchanging distributed medical objects--an approach to future environment of sharing healthcare information.

    Science.gov (United States)

    Ohe, K

    1998-01-01

    Tightly related subsystems in a HIS have to exchange medical data flexibly by the data object rather than by the battery of the data. We developed a CPR subsystem based on Common Object Request Broker Architecture (CORBA) that retrieves and stores clinical information in the object-oriented database via Internet Intra-ORB Protocol (IIOP). The system is hybridized with the legacy HIS applications on the client terminals. We believe that our solution and the experiences will contribute to the future CORBA-based environment in which computerized patient information is shared among hospitals, clinics, and tightly related systems.

  2. Multi-class remote sensing object recognition based on discriminative sparse representation.

    Science.gov (United States)

    Wang, Xin; Shen, Siqiu; Ning, Chen; Huang, Fengchen; Gao, Hongmin

    2016-02-20

    The automatic recognition of multi-class objects with various backgrounds is a big challenge in the field of remote sensing (RS) image analysis. In this paper, we propose a novel recognition framework for multi-class RS objects based on the discriminative sparse representation. In this framework, the recognition problem is implemented in two stages. In the first, or discriminative dictionary learning stage, considering the characterization of remote sensing objects, the scale-invariant feature transform descriptor is first combined with an improved bag-of-words model for multi-class objects feature extraction and representation. Then, information about each class of training samples is fused into the dictionary learning process; by using the K-singular value decomposition algorithm, a discriminative dictionary can be learned for sparse coding. In the second, or recognition, stage, to improve the computational efficiency, the phase spectrum of a quaternion Fourier transform model is applied to the test image to predict a small set of object candidate locations. Then, a multi-scale sliding window mechanism is utilized to scan the image over those candidate locations to obtain the object candidates (or objects of interest). Subsequently, the sparse coding coefficients of these candidates under the discriminative dictionary are mapped to the discriminative vectors that have a good ability to distinguish different classes of objects. Finally, multi-class object recognition can be accomplished by analyzing these vectors. The experimental results show that the proposed work outperforms a number of state-of-the-art methods for multi-class remote sensing object recognition. PMID:26906591

  3. A multiple-point spatially weighted k-NN method for object-based classification

    Science.gov (United States)

    Tang, Yunwei; Jing, Linhai; Li, Hui; Atkinson, Peter M.

    2016-10-01

    Object-based classification, commonly referred to as object-based image analysis (OBIA), is now commonly regarded as able to produce more appealing classification maps, often of greater accuracy, than pixel-based classification and its application is now widespread. Therefore, improvement of OBIA using spatial techniques is of great interest. In this paper, multiple-point statistics (MPS) is proposed for object-based classification enhancement in the form of a new multiple-point k-nearest neighbour (k-NN) classification method (MPk-NN). The proposed method first utilises a training image derived from a pre-classified map to characterise the spatial correlation between multiple points of land cover classes. The MPS borrows spatial structures from other parts of the training image, and then incorporates this spatial information, in the form of multiple-point probabilities, into the k-NN classifier. Two satellite sensor images with a fine spatial resolution were selected to evaluate the new method. One is an IKONOS image of the Beijing urban area and the other is a WorldView-2 image of the Wolong mountainous area, in China. The images were object-based classified using the MPk-NN method and several alternatives, including the k-NN, the geostatistically weighted k-NN, the Bayesian method, the decision tree classifier (DTC), and the support vector machine classifier (SVM). It was demonstrated that the new spatial weighting based on MPS can achieve greater classification accuracy relative to the alternatives and it is, thus, recommended as appropriate for object-based classification.

  4. Class-Based Garbage Collection in Object-Oriented Programming Environments

    Institute of Scientific and Technical Information of China (English)

    张武生; 黄启峰; 沈美明; 郑纬民

    2003-01-01

    Many garbage collection algorithms have been proposed, but few address the special needs of long-running server programs. Server applications usually run for years and spawn many threads, so they create and discard thousands of objects. Therefore, efficient garbage collection is especially important for those applications. This paper presents a class-based garbage collector for object-oriented programming environments that classifies objects by their types to achieve better gradualness. Grouping objects of the same type into a group, with a limited type-lock, a mutator cache and the lease protocol will reduce memory fragmentation, which is especially important for the efficiency of long-running server applications. This class-based collector partitions the heap space by type, which provides better concurrency than the traditional mark-sweep collector, and its reusable garbaged object pool also reduces the object allocation overhead. This paper also discusses the implementation details, such as the mutator cache and the lease protocol, and techniques to achieve better accuracy.

  5. Region-Based Image Retrieval Using an Object Ontology and Relevance Feedback

    Directory of Open Access Journals (Sweden)

    Kompatsiaris Ioannis

    2004-01-01

    Full Text Available An image retrieval methodology suited for search in large collections of heterogeneous images is presented. The proposed approach employs a fully unsupervised segmentation algorithm to divide images into regions and endow the indexing and retrieval system with content-based functionalities. Low-level descriptors for the color, position, size, and shape of each region are subsequently extracted. These arithmetic descriptors are automatically associated with appropriate qualitative intermediate-level descriptors, which form a simple vocabulary termed object ontology. The object ontology is used to allow the qualitative definition of the high-level concepts the user queries for (semantic objects, each represented by a keyword and their relations in a human-centered fashion. When querying for a specific semantic object (or objects, the intermediate-level descriptor values associated with both the semantic object and all image regions in the collection are initially compared, resulting in the rejection of most image regions as irrelevant. Following that, a relevance feedback mechanism, based on support vector machines and using the low-level descriptors, is invoked to rank the remaining potentially relevant image regions and produce the final query results. Experimental results and comparisons demonstrate, in practice, the effectiveness of our approach.

  6. Thickness and clearance visualization based on distance field of 3D objects

    Directory of Open Access Journals (Sweden)

    Masatomo Inui

    2015-07-01

    Full Text Available This paper proposes a novel method for visualizing the thickness and clearance of 3D objects in a polyhedral representation. The proposed method uses the distance field of the objects in the visualization. A parallel algorithm is developed for constructing the distance field of polyhedral objects using the GPU. The distance between a voxel and the surface polygons of the model is computed many times in the distance field construction. Similar sets of polygons are usually selected as close polygons for close voxels. By using this spatial coherence, a parallel algorithm is designed to compute the distances between a cluster of close voxels and the polygons selected by the culling operation so that the fast shared memory mechanism of the GPU can be fully utilized. The thickness/clearance of the objects is visualized by distributing points on the visible surfaces of the objects and painting them with a unique color corresponding to the thickness/clearance values at those points. A modified ray casting method is developed for computing the thickness/clearance using the distance field of the objects. A system based on these algorithms can compute the distance field of complex objects within a few minutes for most cases. After the distance field construction, thickness/clearance visualization at a near interactive rate is achieved.

  7. Full-viewpoint 3D Space Object Recognition Based on Kernel Locality Preserving Projections

    Institute of Scientific and Technical Information of China (English)

    Meng Gang; Jiang Zhiguo; Liu Zhengyi; Zhang Haopeng; Zhao Danpei

    2010-01-01

    Space object recognition plays an important role in spatial exploitation and surveillance,followed by two main problems:lacking of data and drastic changes in viewpoints.In this article,firstly,we build a three-dimensional (3D) satellites dataset named BUAA Satellite Image Dataset (BUAA-SID 1.0) to supply data for 3D space object research.Then,based on the dataset,we propose to recognize full-viewpoint 3D space objects based on kemel locality preserving projections (KLPP).To obtain more accurate and separable description of the objects,firstly,we build feature vectors employing moment invariants,Fourier descriptors,region covariance and histogram of oriented gradients.Then,we map the features into kernel space followed by dimensionality reduction using KLPP to obtain the submanifold of the features.At last,k-nearest neighbor (kNN) is used to accomplish the classification.Experimental results show that the proposed approach is more appropriate for space object recognition mainly considering changes of viewpoints.Encouraging recognition rate could be obtained based on images in BUAA-SID 1.0,and the highest recognition result could achieve 95.87%.

  8. Automatic Segmentation of Nature Object Using Salient Edge Points Based Active Contour

    Directory of Open Access Journals (Sweden)

    Shangbing Gao

    2015-01-01

    Full Text Available Natural image segmentation is often a crucial first step for high-level image understanding, significantly reducing the complexity of content analysis of images. LRAC may have some disadvantages. (1 Segmentation results heavily depend on the initial contour selection which is a very skillful task. (2 In some situations, manual interactions are infeasible. To overcome these shortcomings, we propose a novel model for unsupervised segmentation of viewer’s attention object from natural images based on localizing region-based active model (LRAC. With aid of the color boosting Harris detector and the core saliency map, we get the salient object edge points. Then, these points are employed as the seeds of initial convex hull. Finally, this convex hull is improved by the edge-preserving filter to generate the initial contour for our automatic object segmentation system. In contrast with localizing region-based active contours that require considerable user interaction, the proposed method does not require it; that is, the segmentation task is fulfilled in a fully automatic manner. Extensive experiments results on a large variety of natural images demonstrate that our algorithm consistently outperforms the popular existing salient object segmentation methods, yielding higher precision and better recall rates. Our framework can reliably and automatically extract the object contour from the complex background.

  9. [A method of object detection for remote sensing-imagery based on spectral space transformation].

    Science.gov (United States)

    Wu, Gui-Ping; Xiao, Peng-Feng; Feng, Xue-Zhi; Wang, Ke

    2013-03-01

    Object detection is an intermediate link for remote sensing image processing, which is an important guarantee of remote sensing application and services aspects. In view of the characteristics of remotely sensed imagery in frequency domain, a novel object detection algorithm based on spectral space transformation was proposed in the present paper. Firstly, the Fourier transformation method was applied to transform the image in spatial domain into frequency domain. Secondly, the wedge-shaped sample and overlay analysis methods for frequency energy were used to decompose signal into different frequency spectrum zones, and the center frequency values of object's features were acquired as detection marks in frequency domain. Finally, object information was detected with the matched Gabor filters which have direction and frequency selectivity. The results indicate that the proposed algorithm here performs better and it has good detection capability in specific direction as well.

  10. Cascade Boosting-Based Object Detection from High-Level Description to Hardware Implementation

    Directory of Open Access Journals (Sweden)

    Khattab K

    2009-01-01

    Full Text Available Object detection forms the first step of a larger setup for a wide variety of computer vision applications. The focus of this paper is the implementation of a real-time embedded object detection system while relying on high-level description language such as SystemC. Boosting-based object detection algorithms are considered as the fastest accurate object detection algorithms today. However, the implementation of a real time solution for such algorithms is still a challenge. A new parallel implementation, which exploits the parallelism and the pipelining in these algorithms, is proposed. We show that using a SystemC description model paired with a mainstream automatic synthesis tool can lead to an efficient embedded implementation. We also display some of the tradeoffs and considerations, for this implementation to be effective. This implementation proves capable of achieving 42 fps for images as well as bringing regularity in time consuming.

  11. [Location selection for Shenyang urban parks based on GIS and multi-objective location allocation model].

    Science.gov (United States)

    Zhou, Yuan; Shi, Tie-Mao; Hu, Yuan-Man; Gao, Chang; Liu, Miao; Song, Lin-Qi

    2011-12-01

    Based on geographic information system (GIS) technology and multi-objective location-allocation (LA) model, and in considering of four relatively independent objective factors (population density level, air pollution level, urban heat island effect level, and urban land use pattern), an optimized location selection for the urban parks within the Third Ring of Shenyang was conducted, and the selection results were compared with the spatial distribution of existing parks, aimed to evaluate the rationality of the spatial distribution of urban green spaces. In the location selection of urban green spaces in the study area, the factor air pollution was most important, and, compared with single objective factor, the weighted analysis results of multi-objective factors could provide optimized spatial location selection of new urban green spaces. The combination of GIS technology with LA model would be a new approach for the spatial optimizing of urban green spaces.

  12. Multi-objective optimization of membrane structures based on Pareto Genetic Algorithm

    Institute of Scientific and Technical Information of China (English)

    SAN Bing-bing; SUN Xiao-ying; WU Yue

    2010-01-01

    A multi-objective optimization method based on Pareto Genetic Algorithm is presented for shape design of membrane structures from a structural view point.Several non-dimensional variables are defined as optimization variables,which are decision factors of shapes of membrane structures.Three objectives are proposed including maximization of stiffness,maximum uniformity of stress and minimum reaction under external loads.Pareto Muhi-objective Genetic Algorithm is introduced to solve the Pareto solutions.Consequently,the dependence of the optimality upon the optimization variables is derived to provide guidelines on how to determine design parameters.Moreover,several examples illustrate the proposed methods and applications.The study shows that the multi-objective optimization method in this paper is feasible and efficient for membrane structures; the research on Pareto solutions can provide explicit and useful guidelines for shape design of membrane structures.

  13. D Modelling and Interactive Web-Based Visualization of Cultural Heritage Objects

    Science.gov (United States)

    Koeva, M. N.

    2016-06-01

    Nowadays, there are rapid developments in the fields of photogrammetry, laser scanning, computer vision and robotics, together aiming to provide highly accurate 3D data that is useful for various applications. In recent years, various LiDAR and image-based techniques have been investigated for 3D modelling because of their opportunities for fast and accurate model generation. For cultural heritage preservation and the representation of objects that are important for tourism and their interactive visualization, 3D models are highly effective and intuitive for present-day users who have stringent requirements and high expectations. Depending on the complexity of the objects for the specific case, various technological methods can be applied. The selected objects in this particular research are located in Bulgaria - a country with thousands of years of history and cultural heritage dating back to ancient civilizations. This motivates the preservation, visualisation and recreation of undoubtedly valuable historical and architectural objects and places, which has always been a serious challenge for specialists in the field of cultural heritage. In the present research, comparative analyses regarding principles and technological processes needed for 3D modelling and visualization are presented. The recent problems, efforts and developments in interactive representation of precious objects and places in Bulgaria are presented. Three technologies based on real projects are described: (1) image-based modelling using a non-metric hand-held camera; (2) 3D visualization based on spherical panoramic images; (3) and 3D geometric and photorealistic modelling based on architectural CAD drawings. Their suitability for web-based visualization are demonstrated and compared. Moreover the possibilities for integration with additional information such as interactive maps, satellite imagery, sound, video and specific information for the objects are described. This comparative study

  14. 3D MODELLING AND INTERACTIVE WEB-BASED VISUALIZATION OF CULTURAL HERITAGE OBJECTS

    Directory of Open Access Journals (Sweden)

    M. N. Koeva

    2016-06-01

    Full Text Available Nowadays, there are rapid developments in the fields of photogrammetry, laser scanning, computer vision and robotics, together aiming to provide highly accurate 3D data that is useful for various applications. In recent years, various LiDAR and image-based techniques have been investigated for 3D modelling because of their opportunities for fast and accurate model generation. For cultural heritage preservation and the representation of objects that are important for tourism and their interactive visualization, 3D models are highly effective and intuitive for present-day users who have stringent requirements and high expectations. Depending on the complexity of the objects for the specific case, various technological methods can be applied. The selected objects in this particular research are located in Bulgaria – a country with thousands of years of history and cultural heritage dating back to ancient civilizations. \\this motivates the preservation, visualisation and recreation of undoubtedly valuable historical and architectural objects and places, which has always been a serious challenge for specialists in the field of cultural heritage. In the present research, comparative analyses regarding principles and technological processes needed for 3D modelling and visualization are presented. The recent problems, efforts and developments in interactive representation of precious objects and places in Bulgaria are presented. Three technologies based on real projects are described: (1 image-based modelling using a non-metric hand-held camera; (2 3D visualization based on spherical panoramic images; (3 and 3D geometric and photorealistic modelling based on architectural CAD drawings. Their suitability for web-based visualization are demonstrated and compared. Moreover the possibilities for integration with additional information such as interactive maps, satellite imagery, sound, video and specific information for the objects are described. This

  15. Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet

    Science.gov (United States)

    Rolls, Edmund T.

    2012-01-01

    Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus. PMID:22723777

  16. Automated detection of lunar craters based on object-oriented approach

    Institute of Scientific and Technical Information of China (English)

    YUE ZongYu; LIU JianZhong; WU GanGuo

    2008-01-01

    The object-oriented approach is a powerful method in making classification. With the segmentation of images to objects, many features can be calculated based on the objects so that the targets can be distinguished. However, this method has not been applied to lunar study. In this paper we attempt to apply this method to detecting lunar craters with promising results. Craters are the most obvious features on the moon and they are important for lunar geologic study. One of the important questions in lunar research is to estimate lunar surface ages by examination of crater density per unit area. Hence,proper detection of lunar craters is necessary. Manual crater identification is inefficient, and a more efficient and effective method is needed. This paper describes an object-oriented method to detect lunar craters using lunar reflectance images. In the method, many objects were first segmented from the image based on size, shape, color, and the weights to every layer. Then the feature of "contrast to neighbor objects" was selected to identify craters from the lunar image. In the next step, by merging the adjacent objects belonging to the same class, almost every crater can be taken as an independent object except several very big craters in the study area. To remove the crater rays diagnosed as craters,the feature of "length/width" was further used with suitable parameters to finish recognizing craters.Finally, the result was exported to ArcGIS for manual modification to those big craters and the number of craters was acquired.

  17. Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet.

    Science.gov (United States)

    Rolls, Edmund T

    2012-01-01

    Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus. PMID:22723777

  18. Object Hierarchy-based Supervised Characterisation ofSynthetic Aperture Radar Sensor Images

    Directory of Open Access Journals (Sweden)

    Ish Rishabh

    2008-01-01

    Full Text Available A method of supervised characterisation of synthetic aperture radar (SAR satellite imageshas been discussed in which simple object shape features of satellite images have been usedto classify and describe the terrain types. This scheme is based on a multilevel approach inwhich objects of interest are first segmented out from the image and subsequently characterisedbased on their shape features. Once all objects have been characterised, the entire image canbe characterised. Emphasis has been laid on the hierarchical information extraction from theimage which enables greater flexibility in characterising the image and is not restricted to mereclassification. The paper also describes a method for giving relative importance among features,i.e., to give more weights to those features that are better than others in distinguishing betweencompeting classes. A method of comparing two SAR sensor images based on terrain elementspresent in the images has also been described here.

  19. Vision based Object Recognition of E-Puck Mobile Robot for Warehouse Application

    Directory of Open Access Journals (Sweden)

    Mehmet S. Guzel

    2015-02-01

    Full Text Available At present, most warehouses still require human services for unloading of goods. Unloading of goods requires a continuous system to ensure the quality of work productivity. Therefore the need of autonomous robot system in warehouse is needed to improve the quality of work. Thus, a localization and recognition algorithm is developed and implemented on the E-puck robot. The task involves the recognition of desired object based on their colour (red and blue and locating the desired object to the target location (marked by green marker. In addition, the collision avoidance algorithm is also developed and integrated to allow the robot manoeuvre safely in its working environment. The colour histogram technique is used to recognize the desired object and the target location. Based on the experimental results, the developed algorithm is successfully fulfilling the pick and place requirement with success rate of approximately 70% in simulation study and 50% in real implementation.

  20. Building and Programming a Smart Robotic System for Distinguishing Objects Based on their Shape and Colour

    Science.gov (United States)

    Sharari, T. M.

    2015-03-01

    This paper presents a robotic system designed for holding and placing objects based on their colour and shape. The presented robot is given a complete set of instructions of positions and orientation angles for each manipulation motion. The main feature in this paper is that the developed robot used a combination of vision and motion systems for holding and placing the work-objects, mounted on the flat work-plane, based on their shapes and colors. This combination improves the flexibility of manipulation which may help eliminate the use of some expensive manipulation tasks in a variety of industrial applications. The robotic system presented in this paper is designed as an educational robot that possesses the ability for holding-and-placing operations with limited load. To process the various instructions for holding and placing the work objects, a main control unit - Manipulation Control Unit (MCU) is used as well as a slave unit that performed the actual instructions from the MCU.

  1. Hypergraph-based Object-oriented Model and Hypergraph Theory for GIS

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    This paper discusses the features and relevant theories of GIS spatial data model based on hypergraph,etc.The integrated concept model based on hypergraph and object-oriented model (HOOM) is proposed by the authors.The principal contribution of this paper is that we study the K-section and other theories of hypergraph.An application example using HOOM is given at the end of the paper.

  2. Personalised learning object based on multi-agent model and learners’ learning styles

    OpenAIRE

    Noppamas Pukkhem

    2011-01-01

    A multi-agent model is proposed in which learning styles and a word analysis technique to create a learning object recommendation system are used. On the basis of a learning style-based design, a concept map combination model is proposed to filter out unsuitable learning concepts from a given course. Our learner model classifies learners into eight styles and implements compatible computational methods consisting of three recommendations: i) non-personalised, ii) preferred feature-based, and ...

  3. Incremental Structured Dictionary Learning for Video Sensor-Based Object Tracking

    OpenAIRE

    Ming Xue; Hua Yang; Shibao Zheng; Yi Zhou; Zhenghua Yu

    2014-01-01

    To tackle robust object tracking for video sensor-based applications, an online discriminative algorithm based on incremental discriminative structured dictionary learning (IDSDL-VT) is presented. In our framework, a discriminative dictionary combining both positive, negative and trivial patches is designed to sparsely represent the overlapped target patches. Then, a local update (LU) strategy is proposed for sparse coefficient learning. To formulate the training and classification process, a...

  4. Development of the competency-based objective resident education using virtual patients system

    OpenAIRE

    Taylor Sawyer; Alan Stein; Holly Olson; Christopher Becket Mahnke

    2011-01-01

    The Accreditation Council for Graduate Medical Education (ACGME) requires U.S. physician training programs to teach and evaluate their trainees in six core competencies. Developing innovative methods to meet the ACGME requirements is an ongoing area of research in medical education. Here we describe the development of the Competency-based Objective Resident Education using Virtual Patients (CORE-VP) system, a web-based virtual patient simulator to teach and measure the ACGME core competencies...

  5. Objective Audio Quality Assessment Based on Spectro-Temporal Modulation Analysis

    OpenAIRE

    Guo, Ziyuan

    2011-01-01

    Objective audio quality assessment is an interdisciplinary research area that incorporates audiology and machine learning. Although much work has been made on the machine learning aspect, the audiology aspect also deserves investigation. This thesis proposes a non-intrusive audio quality assessment algorithm, which is based on an auditory model that simulates human auditory system. The auditory model is based on spectro-temporal modulation analysis of spectrogram, which has been proven to be ...

  6. A System based on Adaptive Background Subtraction Approach for Moving Object Detection and Tracking in Videos

    OpenAIRE

    Bahadır KARASULU

    2013-01-01

    Video surveillance systems are based on video and image processing research areas in the scope of computer science. Video processing covers various methods which are used to browse the changes in existing scene for specific video. Nowadays, video processing is one of the important areas of computer science. Two-dimensional videos are used to apply various segmentation and object detection and tracking processes which exists in multimedia content-based indexing, information retrieval, visual a...

  7. SATEN: An Object-Oriented Web-Based Revision and Extraction Engine

    OpenAIRE

    Williams, Mary-Anne; Sims, Aidan

    2000-01-01

    SATEN is an object-oriented web-based extraction and belief revision engine. It runs on any computer via a Java 1.1 enabled browser such as Netscape 4. SATEN performs belief revision based on the AGM approach. The extraction and belief revision reasoning engines operate on a user specified ranking of information. One of the features of SATEN is that it can be used to integrate mutually inconsistent commensuate rankings into a consistent ranking.

  8. Geomorphological change detection using object-based feature extraction from multi-temporal LIDAR data

    NARCIS (Netherlands)

    A.C. Seijmonsbergen; N.S. Anders; W. Bouten

    2012-01-01

    Multi-temporal LiDAR DTMs are used for the development and testing of a method for geomorphological change analysis in western Austria. Our test area is located on a mountain slope in the Gargellen Valley in western Austria. Six geomorphological features were mapped by using stratified Object-Based

  9. Model-based Type B uncertainty evaluations of measurement towards more objective evaluation strategies

    NARCIS (Netherlands)

    M. Boumans

    2013-01-01

    This article proposes a more objective Type B evaluation. This can be achieved when Type B uncertainty evaluations are model-based. This implies, however, grey-box modelling and validation instead of white-box modelling and validation which are appropriate for Type A evaluation.

  10. A Model for the Design of Puzzle-Based Games Including Virtual and Physical Objects

    Science.gov (United States)

    Melero, Javier; Hernandez-Leo, Davinia

    2014-01-01

    Multiple evidences in the Technology-Enhanced Learning domain indicate that Game-Based Learning can lead to positive effects in students' performance and motivation. Educational games can be completely virtual or can combine the use of physical objects or spaces in the real world. However, the potential effectiveness of these approaches…

  11. Ensemble-based multi-objective optimization of on-off control devices under geological uncertainty

    NARCIS (Netherlands)

    Fonseca, R.M.; Leeuwenburgh, O.; Rossa, E.D.; Hof, P.M.J. van den; Jansen, J.D.

    2015-01-01

    We consider robust ensemble-based (EnOpt) multi-objective production optimization of on-off inflow control devices (ICDs) for a sector model inspired on a real-field case. The use of on-off valves as optimization variables leads to a discrete control problem. We propose a re-parameterization of such

  12. A Case of Web-Based Inquiry Learning Model Using Learning Objects

    Science.gov (United States)

    Al Musawi, A.; Asan, A.; Abdelraheem, A.; Osman, M.

    2012-01-01

    This research seeks to (1) implement a model for an inquiry based learning environment using learning objects (LOs), and (2) apply the model to examine its impact on students' learning. This research showed that a well-designed learning environment can enhance students learning experiences. The proposed model was applied to an undergraduate course…

  13. Learning Mathematics by Designing, Programming, and Investigating with Interactive, Dynamic Computer-Based Objects

    Science.gov (United States)

    Marshall, Neil; Buteau, Chantal

    2014-01-01

    As part of their undergraduate mathematics curriculum, students at Brock University learn to create and use computer-based tools with dynamic, visual interfaces, called Exploratory Objects, developed for the purpose of conducting pure or applied mathematical investigations. A student's Development Process Model of creating and using an Exploratory…

  14. Development of Management System for Regional Pollution Source Based on SuperMap Objects

    Institute of Scientific and Technical Information of China (English)

    2011-01-01

    Based on the integration of C#.net and SuperMap Objects(tool software of component GIS),the management system of regional pollution source is developed.It mainly includes the demand analysis of system,function design,database construction,program design and concrete realization in the management aspect of pollution source.

  15. Development of E-Mart Based on Object-Oriented Databases (OODB)

    Institute of Scientific and Technical Information of China (English)

    SUN Li; WANG Li; LIU Hao-shuang

    2002-01-01

    Focusing on the development of electronic-mart (e-mart)based on object-oriented databases (OODB), the concepts of integrated electronic-commerce (ecommerce) environment and e-mart are introduced, and the basic characteristics of OODB Jasmine are described.In addition, the database mode and hierarchy of e-mart are discussed in derail.

  16. Flexibility on storage-release based distributed hydrologic modeling with object-oriented approach

    Science.gov (United States)

    Kang, Kwangmin; Merwade, Venkatesh; Chun, Jong Ahn; Timlin, Dennis

    2016-09-01

    With the availability of advanced hydrologic data in public domain such as remote sensed and climate change scenario data, there is a need for a modeling framework that is capable of using these data to simulate and extend hydrologic processes with multidisciplinary approaches for sustainable water resources management. To address this need, a storage-release based distributed hydrologic model (STORE DHM) is developed based on an object-oriented approach. The model is tested for demonstrating model flexibility and extensibility to know how to well integrate object-oriented approach to further hydrologic research issues, e.g., reconstructing missing precipitation in this study, without changing its main frame. Moreover, the STORE DHM is applied to simulate hydrological processes with multiple classes in the Nanticoke watershed. This study also describes a conceptual and structural framework of object-oriented inheritance and aggregation characteristics under the STORE DHM. In addition, NearestMP (missing value estimation based on nearest neighborhood regression) and KernelMP (missing value estimation based on Kernel Function) are proposed for evaluating STORE DHM flexibility. And then, STORE DHM runoff hydrographs compared with NearestMP and KernelMP runoff hydrographs. Overall results from these comparisons show promising hydrograph outputs generated by the proposed two classes. Consequently, this study suggests that STORE DHM with an object-oriented approach will be a comprehensive water resources modeling tools by adding additional classes for toward developing through its flexibility and extensibility.

  17. Competency-Based Training: Objective Structured Clinical Exercises (OSCE) in Marriage and Family Therapy

    Science.gov (United States)

    Miller, John K.

    2010-01-01

    The field of marriage and family therapy (MFT) has recently engaged in the process of defining core competencies for the profession. Many MFT training programs are adapting their curriculum to develop more competency-based training strategies. The Objective Structured Clinical "Examination" (OSCE) is widely used in the medical profession to assess…

  18. Frequency Affects Object Relative Clause Processing: Some Evidence in Favor of Usage-Based Accounts

    Science.gov (United States)

    Reali, Florencia

    2014-01-01

    The processing difficulty of nested grammatical structure has been explained by different psycholinguistic theories. Here I provide corpus and behavioral evidence in favor of usage-based models, focusing on the case of object relative clauses in Spanish as a first language. A corpus analysis of spoken Spanish reveals that, as in English, the…

  19. A Framework Relating Outcomes Based Education and the Taxonomy of Educational Objectives.

    Science.gov (United States)

    Andrich, David

    2002-01-01

    Articulates a framework that can place the Outcomes Based Education movement in a historical context and by so doing advance its discourse on assessment. Reviews the development and structure of the Taxonomy of Educational Objectives (B. Bloom et al., 1956) and the structure of Student Outcome Statements in Western Australia and explores the…

  20. A general simulation model developing process based on five-object framework

    Institute of Scientific and Technical Information of China (English)

    胡安斌; 伞冶; 陈建明; 陈永强

    2003-01-01

    Different paradigms that relate verification and validation to the simulation model have different development process. A simulation model developing process based on Five-Object Framework (FOF) is discussed in this paper. An example is given to demonstrate the applications of the proposed method.

  1. Extracting Superquadric-based Geon Description for 3D Object Recognition

    Institute of Scientific and Technical Information of China (English)

    XINGWeiwei; LIUWeibin; YUANBaozong

    2005-01-01

    Geons recognition is one key issue in developing 3D object recognition system based on Recognition by components (RBC) theory. In this paper, we present a novel approach for extracting superquadric-based geon description of 3D volumetric primitives from real shape data, which integrates the advantages of deformable superquadric models reconstruction and SVM-based classification. First, Real-coded genetic algorithm (RCGA) is used for superquadric fitting to 3D data and the quantitative parametric information is obtained; then a new sophisticated feature set is derived from superquadric parameters obtained for the next step; and SVM-based classification is proposed and implemented for geons recognition and the qualitative geometric information is obtained. Furthermore, the knowledge-based feedback of SVM network is introduced for improving the classification performance. Ex-perimental results obtained show that our approach is efficient and precise for extracting superquadric-based geon description from real shape data in 3D object recognition. The results are very encouraging and have significant benefit for developing the general 3D object recognition system.

  2. Review of Remotely Sensed Imagery Classification Patterns Based on Object-oriented Image Analysis

    Institute of Scientific and Technical Information of China (English)

    LIU Yongxue; LI Manchun; MAO Liang; XU Feifei; HUANG Shuo

    2006-01-01

    With the wide use of high-resolution remotely sensed imagery, the object-oriented remotely sensed information classification pattern has been intensively studied. Starting with the definition of object-oriented remotely sensed information classification pattern and a literature review of related research progress, this paper sums up 4 developing phases of object-oriented classification pattern during the past 20 years. Then, we discuss the three aspects of methodology in detail, namely remotely sensed imagery segmentation, feature analysis and feature selection, and classification rule generation, through comparing them with remotely sensed information classification method based on per-pixel. At last, this paper presents several points that need to be paid attention to in the future studies on object-oriented RS information classification pattern: 1) developing robust and highly effective image segmentation algorithm for multi-spectral RS imagery; 2) improving the feature-set including edge, spatial-adjacent and temporal characteristics; 3) discussing the classification rule generation classifier based on the decision tree; 4) presenting evaluation methods for classification result by object-oriented classification pattern.

  3. Comprehensive Analysis with KVM Techniques and Implementation of Object Pool Based on J2ME RMS

    Directory of Open Access Journals (Sweden)

    Nandika Sood

    2011-11-01

    Full Text Available J2ME services play an important role in the field of Communication industry. In this paper, we discuss and analyze the consumptive behaviour based on object pool with RMS capabilities. We discuss and analyze different aspects of RMS mining techniques and their behaviour in mobile devices. We also analyze the better method or rule of implementing services which is more suitable for mobile devices. The method this paper mentioned has benefit to analyze large numbers of data in consumptive behaviours and provides some instructions to improve better marketing in concerned fields. In this paper we use J2ME components like CLDC (Connected Limited Device Configuration and MIDP (Mobile Information Device Profile with data mining services (DMS that provide local storage, a user interface, and networking capabilities that runs on mobile computing devices. We also discuss the need of Object Pool in mobile devices to enhance the capability of mobile devices. Object pool model based on RMS is proposed. Aimed to solve the Memory peak problem in J2ME, on the basis of object pool design pattern, an object pool model used RMS is designed and implemented.

  4. Comprehensive Analysis with KVM Techniques and Implementation Of Object Pool Based On J2ME RMS

    Directory of Open Access Journals (Sweden)

    Ms. Nandika Sood

    2011-09-01

    Full Text Available J2ME services play an important role in the field of Communication industry. In this paper, we discuss and analyze the consumptive behaviour based on object pool with RMS capabilities. We discuss and analyze different aspects of RMS mining techniques and their behaviour in mobile devices. We also analyze the better method or rule of implementing services which is more suitable for mobile devices. The method this paper mentioned has benefit to analyze large numbers of data in consumptive behaviours and provides some instructions to improve better marketing in concerned fields. In this paper we use J2ME components like CLDC (Connected Limited Device Configuration and MIDP (Mobile Information Device Profile with data mining services (DMS that provide local storage, a user interface, and networking capabilities that runs on mobile computing devices. We also discuss the need of Object Pool in mobile devices to enhance the capability of mobile devices. Object pool model based on RMS is proposed. Aimed to solve the Memory peak problem in J2ME, on the basis of object pool design pattern, an object pool model used RMS is designed and implemented.

  5. Object-based land-cover classification for metropolitan Phoenix, Arizona, using aerial photography

    Science.gov (United States)

    Li, Xiaoxiao; Myint, Soe W.; Zhang, Yujia; Galletti, Chritopher; Zhang, Xiaoxiang; Turner, Billie L.

    2014-12-01

    Detailed land-cover mapping is essential for a range of research issues addressed by the sustainability and land system sciences and planning. This study uses an object-based approach to create a 1 m land-cover classification map of the expansive Phoenix metropolitan area through the use of high spatial resolution aerial photography from National Agricultural Imagery Program. It employs an expert knowledge decision rule set and incorporates the cadastral GIS vector layer as auxiliary data. The classification rule was established on a hierarchical image object network, and the properties of parcels in the vector layer were used to establish land cover types. Image segmentations were initially utilized to separate the aerial photos into parcel sized objects, and were further used for detailed land type identification within the parcels. Characteristics of image objects from contextual and geometrical aspects were used in the decision rule set to reduce the spectral limitation of the four-band aerial photography. Classification results include 12 land-cover classes and subclasses that may be assessed from the sub-parcel to the landscape scales, facilitating examination of scale dynamics. The proposed object-based classification method provides robust results, uses minimal and readily available ancillary data, and reduces computational time.

  6. Autonomic Management of Object Replication for FT-CORBA Based Intelligent Transportation Systems

    Science.gov (United States)

    Suh, Woonsuk; Lee, Eunseok

    Intelligent Transportation Systems (ITS) comprises the electronics, communications or information processing used singly or integrated to improve the efficiency or safety of surface transportation. Accordingly, the ITS has to perform collection, management, and provision of real time transport information reliably. It can be deployed based on the Common Object Request Broker Architecture (CORBA) of the Object Management Group (OMG) because it consists of many interconnected heterogeneous systems deployed by independent organizations. Fault Tolerant CORBA (FT-CORBA) supports real time requirement of transport information stably through redundancy by replication of server objects. However, object replication, management, and related protocols of FT-CORBA require extra system resources of CPU and memory, and can degrade the system performance both locally and as a whole. This paper proposes an architecture to enhance performance of FT-CORBA based ITS in terms of CPU and memory by managing object replication adaptively during system operation with an agent. The application of the agent is expected to support fault tolerance of real ITS efficiently.

  7. Intelligent Video Object Classification Scheme using Offline Feature Extraction and Machine Learning based Approach

    Directory of Open Access Journals (Sweden)

    Chandra Mani Sharma

    2012-01-01

    Full Text Available Classification of objects in video stream is important because of its application in many emerging areas such as visual surveillance, content based video retrieval and indexing etc. The task is far more challenging because the video data is of heavy and highly variable nature. The processing of video data is required to be in real-time. This paper presents a multiclass object classification technique using machine learning approach. Haar-like features are used for training the classifier. The feature calculation is performed using Integral Image representation and we train the classifier offline using a Stage-wise Additive Modeling using a Multiclass Exponential loss function (SAMME. The validity of the method has been verified from the implementation of a real-time human-car detector. Experimental results show that the proposed method can accurately classify objects, in video, into their respective classes. The proposed object classifier works well in outdoor environment in presence of moderate lighting conditions and variable scene background. The proposed technique is compared, with other object classification techniques, based on various performance parameters.

  8. Web Services Based Learning Objects Generator for Device-Independent M-Learning

    Directory of Open Access Journals (Sweden)

    Akram Moh. Alkouz

    2006-06-01

    Full Text Available Learning objects, which are the base component of m-learning system, are usually target to modifications in contexts and formats. The device- dependent applications of hand-held devices have proven to be ineffective for creating m-learning courseware. Learning Objects Metadata (LOM is the most popular standard specification for learning objects but lacks the ability to facilitate platforms descriptions. This paper outlines various aspects of design and implementation of Web Services Oriented Rendering Architecture (WSORA which combines LOM Editor with any available published web services. This arrangement is devised in order to make a device-independent m-learning gateway between different mobile devices, such as cell phones, PDA’s, palmtops, and laptops and the vast learning objects available on the World Wide Web. The key technologies behind WSORA are extending the IEEE LOM base scheme structure, LOM Editor, device-independent LO generator, and web services. The major advantage of WSORA is thus achieved to give mobile devices of different types clean and quick access to learning objects customarily designed for desktop browsers.

  9. Invariant visual object and face recognition: neural and computational bases, and a model, VisNet

    Directory of Open Access Journals (Sweden)

    Edmund T eRolls

    2012-06-01

    Full Text Available Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy modelin which invariant representations can be built by self-organizing learning based on the temporal and spatialstatistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associativesynaptic learning rule with a short term memory trace, and/or it can use spatialcontinuity in Continuous Spatial Transformation learning which does not require a temporal trace. The model of visual processing in theventral cortical stream can build representations of objects that are invariant withrespect to translation, view, size, and also lighting. The modelhas been extended to provide an account of invariant representations in the dorsal visualsystem of the global motion produced by objects such as looming, rotation, and objectbased movement. The model has been extended to incorporate top-down feedback connectionsto model the control of attention by biased competition in for example spatial and objectsearch tasks. The model has also been extended to account for how the visual system canselect single objects in complex visual scenes, and how multiple objects can berepresented in a scene. The model has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus.

  10. Locating the position of objects in non-line-of-sight based on time delay estimation

    Science.gov (United States)

    Wang, Xue-Feng; Wang, Yuan-Qing; Su, Jin-Shan; Yang, Xing-Yu

    2016-08-01

    Non-line-of-sight imaging detection is to detect hidden objects by indirect light and intermediary surface (diffuser). It has very important significance in indirect access to an object or dangerous object detection, such as medical treatment and rescue. An approach to locating the positions of hidden objects is proposed based on time delay estimation. The time delays between the received signals and the source signal can be obtained by correlation analysis, and then the positions of hidden objects will be located. Compared with earlier systems and methods, the proposed approach has some modifications and provides significant improvements, such as quick data acquisition, simple system structure and low cost, and can locate the positions of hidden objects as well: this technology lays a good foundation for developing a practical system that can be used in real applications. Project supported by the National Science and Technology Major Project of China (Grant No. AHJ2011Z001) and the Major Research Project of Yili Normal University (Grant No. 2016YSZD05).

  11. Automatic 3D object recognition and reconstruction based on neuro-fuzzy modelling

    Science.gov (United States)

    Samadzadegan, Farhad; Azizi, Ali; Hahn, Michael; Lucas, Curo

    Three-dimensional object recognition and reconstruction (ORR) is a research area of major interest in computer vision and photogrammetry. Virtual cities, for example, is one of the exciting application fields of ORR which became very popular during the last decade. Natural and man-made objects of cities such as trees and buildings are complex structures and automatic recognition and reconstruction of these objects from digital aerial images but also other data sources is a big challenge. In this paper a novel approach for object recognition is presented based on neuro-fuzzy modelling. Structural, textural and spectral information is extracted and integrated in a fuzzy reasoning process. The learning capability of neural networks is introduced to the fuzzy recognition process by taking adaptable parameter sets into account which leads to the neuro-fuzzy approach. Object reconstruction follows recognition seamlessly by using the recognition output and the descriptors which have been extracted for recognition. A first successful application of this new ORR approach is demonstrated for the three object classes 'buildings', 'cars' and 'trees' by using aerial colour images of an urban area of the town of Engen in Germany.

  12. Object Tracking Using Adaptive Covariance Descriptor and Clustering-Based Model Updating for Visual Surveillance

    Directory of Open Access Journals (Sweden)

    Lei Qin

    2014-05-01

    Full Text Available We propose a novel approach for tracking an arbitrary object in video sequences for visual surveillance. The first contribution of this work is an automatic feature extraction method that is able to extract compact discriminative features from a feature pool before computing the region covariance descriptor. As the feature extraction method is adaptive to a specific object of interest, we refer to the region covariance descriptor computed using the extracted features as the adaptive covariance descriptor. The second contribution is to propose a weakly supervised method for updating the object appearance model during tracking. The method performs a mean-shift clustering procedure among the tracking result samples accumulated during a period of time and selects a group of reliable samples for updating the object appearance model. As such, the object appearance model is kept up-to-date and is prevented from contamination even in case of tracking mistakes. We conducted comparing experiments on real-world video sequences, which confirmed the effectiveness of the proposed approaches. The tracking system that integrates the adaptive covariance descriptor and the clustering-based model updating method accomplished stable object tracking on challenging video sequences.

  13. A bio-inspired method and system for visual object-based attention and segmentation

    Science.gov (United States)

    Huber, David J.; Khosla, Deepak

    2010-04-01

    This paper describes a method and system of human-like attention and object segmentation in visual scenes that (1) attends to regions in a scene in their rank of saliency in the image, (2) extracts the boundary of an attended proto-object based on feature contours, and (3) can be biased to boost the attention paid to specific features in a scene, such as those of a desired target object in static and video imagery. The purpose of the system is to identify regions of a scene of potential importance and extract the region data for processing by an object recognition and classification algorithm. The attention process can be performed in a default, bottom-up manner or a directed, top-down manner which will assign a preference to certain features over others. One can apply this system to any static scene, whether that is a still photograph or imagery captured from video. We employ algorithms that are motivated by findings in neuroscience, psychology, and cognitive science to construct a system that is novel in its modular and stepwise approach to the problems of attention and region extraction, its application of a flooding algorithm to break apart an image into smaller proto-objects based on feature density, and its ability to join smaller regions of similar features into larger proto-objects. This approach allows many complicated operations to be carried out by the system in a very short time, approaching real-time. A researcher can use this system as a robust front-end to a larger system that includes object recognition and scene understanding modules; it is engineered to function over a broad range of situations and can be applied to any scene with minimal tuning from the user.

  14. Information extraction with object based support vector machines and vegetation indices

    Science.gov (United States)

    Ustuner, Mustafa; Abdikan, Saygin; Balik Sanli, Fusun

    2016-07-01

    Information extraction through remote sensing data is important for policy and decision makers as extracted information provide base layers for many application of real world. Classification of remotely sensed data is the one of the most common methods of extracting information however it is still a challenging issue because several factors are affecting the accuracy of the classification. Resolution of the imagery, number and homogeneity of land cover classes, purity of training data and characteristic of adopted classifiers are just some of these challenging factors. Object based image classification has some superiority than pixel based classification for high resolution images since it uses geometry and structure information besides spectral information. Vegetation indices are also commonly used for the classification process since it provides additional spectral information for vegetation, forestry and agricultural areas. In this study, the impacts of the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Red Edge Index (NDRE) on the classification accuracy of RapidEye imagery were investigated. Object based Support Vector Machines were implemented for the classification of crop types for the study area located in Aegean region of Turkey. Results demonstrated that the incorporation of NDRE increase the classification accuracy from 79,96% to 86,80% as overall accuracy, however NDVI decrease the classification accuracy from 79,96% to 78,90%. Moreover it is proven than object based classification with RapidEye data give promising results for crop type mapping and analysis.

  15. Multi-objective intelligent coordinating optimization blending system based on qualitative and quantitative synthetic model

    Institute of Scientific and Technical Information of China (English)

    WANG Ya-lin; MA Jie; GUI Wei-hua; YANG Chun-hua; ZHANG Chuan-fu

    2006-01-01

    A multi-objective intelligent coordinating optimization strategy based on qualitative and quantitative synthetic model for Pb-Zn sintering blending process was proposed to obtain optimal mixture ratio. The mechanism and neural network quantitative models for predicting compositions and rule models for expert reasoning were constructed based on statistical data and empirical knowledge. An expert reasoning method based on these models were proposed to solve blending optimization problem, including multi-objective optimization for the first blending process and area optimization for the second blending process, and to determine optimal mixture ratio which will meet the requirement of intelligent coordination. The results show that the qualified rates of agglomerate Pb, Zn and S compositions are increased by 7.1%, 6.5% and 6.9%, respectively, and the fluctuation of sintering permeability is reduced by 7.0 %, which effectively stabilizes the agglomerate compositions and the permeability.

  16. Multi-objective optimization of stamping forming process of head using Pareto-based genetic algorithm

    Institute of Scientific and Technical Information of China (English)

    周杰; 卓芳; 黄磊; 罗艳

    2015-01-01

    To obtain the optimal process parameters of stamping forming, finite element analysis and optimization technique were integrated via transforming multi-objective issue into a single-objective issue. A Pareto-based genetic algorithm was applied to optimizing the head stamping forming process. In the proposed optimal model, fracture, wrinkle and thickness varying are a function of several factors, such as fillet radius, draw-bead position, blank size and blank-holding force. Hence, it is necessary to investigate the relationship between the objective functions and the variables in order to make objective functions varying minimized simultaneously. Firstly, the central composite experimental (CCD) with four factors and five levels was applied, and the experimental data based on the central composite experimental were acquired. Then, the response surface model (RSM) was set up and the results of the analysis of variance (ANOVA) show that it is reliable to predict the fracture, wrinkle and thickness varying functions by the response surface model. Finally, a Pareto-based genetic algorithm was used to find out a set of Pareto front, which makes fracture, wrinkle and thickness varying minimized integrally. A head stamping case indicates that the present method has higher precision and practicability compared with the“trial and error”procedure.

  17. A vague-set-based fuzzy multi-objective decision making model for bidding purchase

    Institute of Scientific and Technical Information of China (English)

    WANG Zhou-jing; QIAN Edward Y.

    2007-01-01

    A vague-set-based fuzzy multi-objective decision making model is developed for evaluating bidding plans in a bidding purchase process. A group of decision-makers (DMs) first independently assess bidding plans according to their experience and preferences, and these assessments may be expressed as linguistic terms, which are then converted to fuzzy numbers. The resulting decision matrices are then transformed to objective membership grade matrices. The lower bound of satisfaction and upper bound of dissatisfaction are used to determine each bidding plan's supporting, opposing, and neutral objective sets, which together determine the vague value of a bidding plan. Finally, a score function is employed to rank all bidding plans. A new score function based on vague sets is introduced in the model and a novel method is presented for calculating the lower bound of satisfaction and upper bound of dissatisfaction. In a vague-set-based fuzzy multi-objective decision making model, different valuations for upper and lower bounds of satisfaction usually lead to distinct ranking results. Therefore, it is crucial to effectively contain DMs' arbitrariness and subjectivity when these values are determined.

  18. Infrared object detection using global and local cues based on LARK

    Science.gov (United States)

    Qi, Wei; Han, Jing; Zhang, Yi; Bai, Lian-fa

    2016-05-01

    Object detection has become a challenging problem in computer vision. Locally Adaptive Regression Kernel (LARK) based detection methods are able to produce visually pleasing results without any training. We in this paper present an effective object detection method by exploring global and local cues based on LARK features. First, we encode the local context similarity by exploiting region Structural LARK (SLARK) features, which measure the likeness of a pixel to its surroundings in the query image and the test image. Second, a global constraint based on SLARK features via Heat equation is learned to detect similar features in the test image. Results from matrix cosine similarity are computed to estimate similar regions between these computed features. A compactness score is provided to refine these regions. Next, we detect the location of objects in the test image using non-maxima suppression. We show in experiments that the proposed method significantly outperforms other methods on the infrared image datasets, localizing the objects in the test images effectively.

  19. Network Analysis Modeling Towards GIS Based on Object-Relation Database

    Institute of Scientific and Technical Information of China (English)

    YUE Peng; WANG Yandong; GONG Jianya; HUANG Xianfeng

    2004-01-01

    This paper compares the differences between the mathematical model in graph theory and GIS network analysis model. Thus it claims that the GIS network analysis model needs to solve. Then this paper introduces the spatial data management methods in object-relation database for GIS and discusses its effects on the network analysis model. Finally it puts forward the GIS network analysis model based on the object-relation database. The structure of the model is introduced in detail and research is done to the internal and external memory data structure of the model. The results show that it performs well in practice.

  20. Stability Analysis of Ranking Alternatives Based on Subjective and Objective Weight

    Institute of Scientific and Technical Information of China (English)

    JIANG Yan; ZUO Bao-he; YUE Chao-yuan

    2002-01-01

    Weights of criteria are used to assess the relative importance of the different criteria in multicriteria analysis, which can influence ranking result more or less depending on the multicriteria decisionmaking method used. In this paper, the influences of alternatives' ranking result associated with the change of weight are discussed by making use of the concept of weight stability intervals based on subjective and objective integrated weighting approach. Meamwhile, A model of weight proportion stability intervals is proposed. a numeral example is used to illuminate how many increment of objective weight can change the ranking results determined by subjective weight.

  1. Recognition of Gene Acceptor Site Based on Multi-objective Optimization

    Institute of Scientific and Technical Information of China (English)

    Jing ZHAO; Yue-Min ZHU; Pei-Ming SONG; Qing FANG; Jian-Hua LUO

    2005-01-01

    A new method for predicting the gene acceptor site based on multi-objective optimization is introduced in this paper. The models for the acceptor, branch and distance between acceptor site and branch site were constructed according to the characteristics of the sequences from the exon-intron database and using common biological knowledge. The acceptor function, branch function and distance function were defined respectively, and the multi-objective optimization model was constructed to recognize the splice site. The test results show that the algorithm used in this study performs better than the SplicePredictor,which is one of the leading acceptor site detectors.

  2. Context based Coding of Binary Shapes by Object Boundary Straightness Analysis

    DEFF Research Database (Denmark)

    Aghito, Shankar Manuel; Forchhammer, Søren

    2004-01-01

    A new lossless compression scheme for bilevel images targeted at binary shapes of image and video objects is presented. The scheme is based on a local analysis of the digital straightness of the causal part of the object boundary, which is used in the context definition for arithmetic encoding....... Tested on individual images of binary shapes and binary layers of digital maps the algorithm outperforms PWC, JBIG and MPEG-4 CAE. On the binary shapes the code lengths are reduced by 21%, 25%, and 42%, respectively. On the maps the reductions are 34%, 32%, and 59%, respectively. The algorithm is also...

  3. Affine Invariant, Model-Based Object Recognition Using Robust Metrics and Bayesian Statistics

    CERN Document Server

    Zografos, Vasileios; 10.1007/11559573_51

    2010-01-01

    We revisit the problem of model-based object recognition for intensity images and attempt to address some of the shortcomings of existing Bayesian methods, such as unsuitable priors and the treatment of residuals with a non-robust error norm. We do so by using a refor- mulation of the Huber metric and carefully chosen prior distributions. Our proposed method is invariant to 2-dimensional affine transforma- tions and, because it is relatively easy to train and use, it is suited for general object matching problems.

  4. Smart learning objects for smart education in computer science theory, methodology and robot-based implementation

    CERN Document Server

    Stuikys, Vytautas

    2015-01-01

    This monograph presents the challenges, vision and context to design smart learning objects (SLOs) through Computer Science (CS) education modelling and feature model transformations. It presents the latest research on the meta-programming-based generative learning objects (the latter with advanced features are treated as SLOs) and the use of educational robots in teaching CS topics. The introduced methodology includes the overall processes to develop SLO and smart educational environment (SEE) and integrates both into the real education setting to provide teaching in CS using constructivist a

  5. Robust object tracking techniques for vision-based 3D motion analysis applications

    Science.gov (United States)

    Knyaz, Vladimir A.; Zheltov, Sergey Y.; Vishnyakov, Boris V.

    2016-04-01

    Automated and accurate spatial motion capturing of an object is necessary for a wide variety of applications including industry and science, virtual reality and movie, medicine and sports. For the most part of applications a reliability and an accuracy of the data obtained as well as convenience for a user are the main characteristics defining the quality of the motion capture system. Among the existing systems for 3D data acquisition, based on different physical principles (accelerometry, magnetometry, time-of-flight, vision-based), optical motion capture systems have a set of advantages such as high speed of acquisition, potential for high accuracy and automation based on advanced image processing algorithms. For vision-based motion capture accurate and robust object features detecting and tracking through the video sequence are the key elements along with a level of automation of capturing process. So for providing high accuracy of obtained spatial data the developed vision-based motion capture system "Mosca" is based on photogrammetric principles of 3D measurements and supports high speed image acquisition in synchronized mode. It includes from 2 to 4 technical vision cameras for capturing video sequences of object motion. The original camera calibration and external orientation procedures provide the basis for high accuracy of 3D measurements. A set of algorithms as for detecting, identifying and tracking of similar targets, so for marker-less object motion capture is developed and tested. The results of algorithms' evaluation show high robustness and high reliability for various motion analysis tasks in technical and biomechanics applications.

  6. Semantic Predicate Types and Approximation for Class-based Object Oriented Programming

    CERN Document Server

    van Bakel, Steffen

    2011-01-01

    We apply the principles of the intersection type discipline to the study of class-based object oriented programs and; our work follows from a similar approach (in the context of Abadi and Cardelli's Varsigma-object calculus) taken by van Bakel and de'Liguoro. We define an extension of Featherweight Java, FJc and present a predicate system which we show to be sound and expressive. We also show that our system provides a semantic underpinning for the object oriented paradigm by generalising the concept of approximant from the Lambda Calculus and demonstrating an approximation result: all expressions to which we can assign a predicate have an approximant that satisfies the same predicate. Crucial to this result is the notion of predicate language, which associates a family of predicates with a class.

  7. Design for Sustainability of Industrial Symbiosis based on Emergy and Multi-objective Particle Swarm Optimization

    DEFF Research Database (Denmark)

    Ren, Jingzheng; Liang, Hanwei; Dong, Liang;

    2016-01-01

    approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable......Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative...... performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied...

  8. Static Object Detection Based on a Dual Background Model and a Finite-State Machine

    Directory of Open Access Journals (Sweden)

    Heras Evangelio Rubén

    2011-01-01

    Full Text Available Detecting static objects in video sequences has a high relevance in many surveillance applications, such as the detection of abandoned objects in public areas. In this paper, we present a system for the detection of static objects in crowded scenes. Based on the detection of two background models learning at different rates, pixels are classified with the help of a finite-state machine. The background is modelled by two mixtures of Gaussians with identical parameters except for the learning rate. The state machine provides the meaning for the interpretation of the results obtained from background subtraction; it can be implemented as a look-up table with negligible computational cost and it can be easily extended. Due to the definition of the states in the state machine, the system can be used either full automatically or interactively, making it extremely suitable for real-life surveillance applications. The system was successfully validated with several public datasets.

  9. Design for sustainability of industrial symbiosis based on emergy and multi-objective particle swarm optimization.

    Science.gov (United States)

    Ren, Jingzheng; Liang, Hanwei; Dong, Liang; Sun, Lu; Gao, Zhiqiu

    2016-08-15

    Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied by the proposed method, a few of compromises between high profitability and high sustainability can be obtained for the decision-makers/stakeholders to make decision.

  10. Design of object surveillance system based on enhanced fish-eye lens

    Institute of Scientific and Technical Information of China (English)

    Jianhui Wu; Kuntao Yang; Qiaolian Xiang; Nanyang Zhang

    2009-01-01

    A new method is proposed for the object surveillance system based on the enhanced fish-eye lens and the high speed digital signal processor (DSP). The improved fish-eye lens images an ellipse picture on the charge-coupled device (CCD) surface, which increases both the utilization rate of the 4:3 rectangular CCD and the imaging resolution, and remains the view angle of 183°. The algorithm of auto-adapted renewal background subtraction (ARBS) is also explored to extract the object from the monitoring image. The experimental result shows that the ARBS algorithm has high anti-jamming ability and high resolution, leading to excellent object detecting ability from the enhanced elliptical fish-eye image under varies en-vironments. This system has potential applications in different security monitoring fields due to its wide monitoring space, simple structure, working stability, and reliability.

  11. [CORBA-based design and packaging of picture archiving and communication system object].

    Science.gov (United States)

    Zhang, Zu-jin; Sun, An-yu

    2009-10-01

    Regionalization has become one of the most important trends in the development of picture archiving and communication systems (PACS) due to the existence of large amounts of information islands. The conventional PACS designed according to the DICOM standard on the basis of the C/S structure fails to meet the demand of regional information system maintenance. A regional PACS system based on common object request broker architecture (CORBA) distributed technology is therefore proposed and implemented. This article describes the design and packaging of the PACS objects. When mounting a series of separate logical and related functional PACS objects on the ORB bus, the multi-scale PACS systems can be established. This method eliminates the limitation of the C/S structure and offers good compatibility and scalability.

  12. Multidisciplinary design optimization of vehicle instrument panel based on multi-objective genetic algorithm

    Science.gov (United States)

    Wang, Ping; Wu, Guangqiang

    2013-03-01

    Typical multidisciplinary design optimization(MDO) has gradually been proposed to balance performances of lightweight, noise, vibration and harshness(NVH) and safety for instrument panel(IP) structure in the automotive development. Nevertheless, plastic constitutive relation of Polypropylene(PP) under different strain rates, has not been taken into consideration in current reliability-based and collaborative IP MDO design. In this paper, based on tensile test under different strain rates, the constitutive relation of Polypropylene material is studied. Impact simulation tests for head and knee bolster are carried out to meet the regulation of FMVSS 201 and FMVSS 208, respectively. NVH analysis is performed to obtain mainly the natural frequencies and corresponding mode shapes, while the crashworthiness analysis is employed to examine the crash behavior of IP structure. With the consideration of lightweight, NVH, head and knee bolster impact performance, design of experiment(DOE), response surface model(RSM), and collaborative optimization(CO) are applied to realize the determined and reliability-based optimizations, respectively. Furthermore, based on multi-objective genetic algorithm(MOGA), the optimal Pareto sets are completed to solve the multi-objective optimization(MOO) problem. The proposed research ensures the smoothness of Pareto set, enhances the ability of engineers to make a comprehensive decision about multi-objectives and choose the optimal design, and improves the quality and efficiency of MDO.

  13. Real-Time Projection-Based Augmented Reality System for Dynamic Objects in the Performing Arts

    Directory of Open Access Journals (Sweden)

    Jaewoon Lee

    2015-02-01

    Full Text Available This paper describes the case study of applying projection-based augmented reality, especially for dynamic objects in live performing shows, such as plays, dancing, or musicals. Our study aims to project imagery correctly inside the silhouettes of flexible objects, in other words, live actors or the surface of actor’s costumes; the silhouette transforms its own shape frequently. To realize this work, we implemented a special projection system based on the real-time masking technique, that is to say real-time projection-based augmented reality system for dynamic objects in performing arts. We installed the sets on a stage for live performance, and rehearsed particular scenes of a musical. In live performance, using projection-based augmented reality technology enhances technical and theatrical aspects which were not possible with existing video projection techniques. The projected images on the surfaces of actor’s costume could not only express the particular scene of a performance more effectively, but also lead the audience to an extraordinary visual experience.

  14. Transmission of object based fine-granular-scalability video over networks

    Science.gov (United States)

    Shi, Xu-li; Jin, Zhi-cheng; Teng, Guo-wei; Zhang, Zhao-yang; An, Ping; Xiao, Guang

    2006-05-01

    It is a hot focus of current researches in video standards that how to transmit video streams over Internet and wireless networks. One of the key methods is FGS(Fine-Granular-Scalability), which can always adapt to the network bandwidth varying but with some sacrifice of coding efficiency, is supported by MPEG-4. Object-based video coding algorithm has been firstly included in MPEG-4 standard that can be applied in interactive video. However, the real time segmentation of VOP(video object plan) is difficult that limit the application of MPEG-4 standard in interactive video. H.264/AVC is the up-to-date video-coding standard, which enhance compression performance and provision a network-friendly video representation. In this paper, we proposed a new Object Based FGS(OBFGS) coding algorithm embedded in H.264/AVC that is different from that in mpeg-4. After the algorithms optimization for the H.264 encoder, the FGS first finish the base-layer coding. Then extract moving VOP using the base-layer information of motion vectors and DCT coefficients. Sparse motion vector field of p-frame composed of 4*4 blocks, 4*8 blocks and 8*4 blocks in base-layer is interpolated. The DCT coefficient of I-frame is calculated by using information of spatial intra-prediction. After forward projecting each p-frame vector to the immediate adjacent I-frame, the method extracts moving VOPs (video object plan) using a recursion 4*4 block classification process. Only the blocks that belong to the moving VOP in 4*4 block-level accuracy is coded to produce enhancement-layer stream. Experimental results show that our proposed system can obtain high interested VOP quality at the cost of fewer coding efficiency.

  15. Bi-objective optimization for multi-modal transportation routing planning problem based on Pareto optimality

    Directory of Open Access Journals (Sweden)

    Yan Sun

    2015-09-01

    Full Text Available Purpose: The purpose of study is to solve the multi-modal transportation routing planning problem that aims to select an optimal route to move a consignment of goods from its origin to its destination through the multi-modal transportation network. And the optimization is from two viewpoints including cost and time. Design/methodology/approach: In this study, a bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. Minimizing the total transportation cost and the total transportation time are set as the optimization objectives of the model. In order to balance the benefit between the two objectives, Pareto optimality is utilized to solve the model by gaining its Pareto frontier. The Pareto frontier of the model can provide the multi-modal transportation operator (MTO and customers with better decision support and it is gained by the normalized normal constraint method. Then, an experimental case study is designed to verify the feasibility of the model and Pareto optimality by using the mathematical programming software Lingo. Finally, the sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case. Findings: The calculation results indicate that the proposed model and Pareto optimality have good performance in dealing with the bi-objective optimization. The sensitivity analysis also shows the influence of the variation of the demand and supply on the multi-modal transportation organization clearly. Therefore, this method can be further promoted to the practice. Originality/value: A bi-objective mixed integer linear programming model is proposed to optimize the multi-modal transportation routing planning problem. The Pareto frontier based sensitivity analysis of the demand and supply in the multi-modal transportation organization is performed based on the designed case.

  16. Simplified production of multimedia based radiological learning objects using the flash format

    International Nuclear Information System (INIS)

    Purpose: evaluation of the applicability of the flash format for the production of radiological learning objects used in an e-learning environment. Material and methods: five exemplary learning objects with different didactic purposes referring to radiological diagnostics are presented. They have been intended for the use within the multimedia, internet-based e-learning environment LaMedica. Interactive learning objects were composed using the Flash 5.0 software (Macromedia, San Francisco, USA) on the basis of digital CT and MR images, digitized conventional radiographs and different graphical elements prepared as TIFF files or in a vector graphics format. Results: after a short phase of initial skill adaptation training, a radiologist author was soon able to create independently all learning objects. The import of different types of images and graphical elements was carried out without complications. Despite manifold design options, handling of the program is easy due to clear arrangement and structure, thus enabling the creation of simple as well as complex learning objects that provided a high degree of attractiveness and interaction. Data volume and bandwidth demand for online use was significantly reduced by the flash format compression without a substantial loss of visual quality. (orig.)

  17. Bionics-Based Approach for Object Tracking to Implementin Robot Applications

    Directory of Open Access Journals (Sweden)

    Hussam K. Abdul-Ameer

    2010-01-01

    Full Text Available In this paper, an approach for object tracking that is inspired from human oculomotor system is proposed and verified experimentally. The developed approach divided into two phases, fast tracking or saccadic phase and smooth pursuit phase. In the first phase, the field of the view is segmented into four regions that are analogue to retinal periphery in the oculomotor system. When the object of interest is entering these regions, the developed vision system responds by changing the values of the pan and tilt angles to allow the object lies in the fovea area and then the second phase will activate. A fuzzy logic method is implemented in the saccadic phase as an intelligent decision maker to select the values of the pan and tilt angle based on suggested logical rules. In smooth pursuit phase, the object is kept in the center area of the field of the view by smooth adjusting the values of the pan and tilt angles where this stage is analogue to putting the observing object in the fovea centralis of the oculomotor system. The proposed approach was implemented by using (Camera-Pan / Tilt configuration and showed good results to improve the vision capability of the humanoid robots.

  18. Identification of the lateral position of a virtual object based on echoes by humans.

    Science.gov (United States)

    Rowan, Daniel; Papadopoulos, Timos; Edwards, David; Holmes, Hannah; Hollingdale, Anna; Evans, Leah; Allen, Robert

    2013-06-01

    Echolocation offers a promising approach to improve the quality of life of people with blindness although little is known about the factors influencing object localisation using a 'searching' strategy. In this paper, we describe a series of experiments using sighted and blind human listeners and a 'virtual auditory space' technique to investigate the effects of the distance and orientation of a reflective object and the effect of stimulus bandwidth on ability to identify the right-versus-left position of the object, with bands of noise and durations from 10-400 ms. We found that performance reduced with increasing object distance. This was more rapid for object orientations where mirror-like reflection paths do not exist to both ears (i.e., most possible orientations); performance with these orientations was indistinguishable from chance at 1.8 m for even the best performing listeners in other conditions. Above-chance performance extended to larger distances when the echo was artificially presented in isolation, as might be achieved in practice by an assistive device. We also found that performance was primarily based on information above 2 kHz. Further research should extend these investigations to include other factors that are relevant to real-life echolocation. PMID:23538130

  19. Object-based Encoding in Visual Working Memory: Evidence from Memory-driven Attentional Capture.

    Science.gov (United States)

    Gao, Zaifeng; Yu, Shixian; Zhu, Chengfeng; Shui, Rende; Weng, Xuchu; Li, Peng; Shen, Mowei

    2016-01-01

    Visual working memory (VWM) adopts a specific manner of object-based encoding (OBE) to extract perceptual information: Whenever one feature-dimension is selected for entry into VWM, the others are also extracted. Currently most studies revealing OBE probed an 'irrelevant-change distracting effect', where changes of irrelevant-features dramatically affected the performance of the target feature. However, the existence of irrelevant-feature change may affect participants' processing manner, leading to a false-positive result. The current study conducted a strict examination of OBE in VWM, by probing whether irrelevant-features guided the deployment of attention in visual search. The participants memorized an object's colour yet ignored shape and concurrently performed a visual-search task. They searched for a target line among distractor lines, each embedded within a different object. One object in the search display could match the shape, colour, or both dimensions of the memory item, but this object never contained the target line. Relative to a neutral baseline, where there was no match between the memory and search displays, search time was significantly prolonged in all match conditions, regardless of whether the memory item was displayed for 100 or 1000 ms. These results suggest that task-irrelevant shape was extracted into VWM, supporting OBE in VWM. PMID:26956084

  20. Measurement of a discontinuous object based on a dual-frequency grating

    Institute of Scientific and Technical Information of China (English)

    Qiao Nao-Sheng; Cai Xin-Hua; Yao Chun-Mei

    2009-01-01

    The dual-frequency grating measurement theory is proposed in order to carry out the measurement of a discontinuous object. Firstly, the reason why frequency spectra are produced by low frequency gratings and high frequency gratings in the field of frequency is analysed, and the relationship between the wrapped-phase and the unwrappingphase is discussed. Secondly, a method to combine the advantages of the two kinds of gratings is proposed: one stripe is produced in the mutation part of the object measured by a suitable low frequency grating designed by MATLAB, then the phase produced by the low frequency grating need not be unfolded. The integer series of stripes is produced by a high frequency grating designed by MATLAB based on the frequency ratio of the two kinds of gratings and the high frequency wrapped-phase, and the high frequency unwrapping-phase is then obtained. In order to verify the correctness of the theoretical analysis, a steep discontinuous object of 600×600 pixels and 10.00 mm in height is simulated and a discontinuous object of ladder shape which is 32.00 mm in height is used in experiment. Both the simulation and the experiment can restore the discontinuous object height accurately by using the dual-frequency grating measurement theory.

  1. Robust Online Object Tracking Based on Feature Grouping and 2DPCA

    Directory of Open Access Journals (Sweden)

    Ming-Xin Jiang

    2013-01-01

    Full Text Available We present an online object tracking algorithm based on feature grouping and two-dimensional principal component analysis (2DPCA. Firstly, we introduce regularization into the 2DPCA reconstruction and develop an iterative algorithm to represent an object by 2DPCA bases. Secondly, the object templates are grouped into a more discriminative image and a less discriminative image by computing the variance of the pixels in multiple frames. Then, the projection matrix is learned according to the more discriminative image and the less discriminative image, and the samples are projected. The object tracking results are obtained using Bayesian maximum a posteriori probability estimation. Finally, we employ a template update strategy which combines incremental subspace learning and the error matrix to reduce tracking drift. Compared with other popular methods, our method reduces the computational complexity and is very robust to abnormal changes. Both qualitative and quantitative evaluations on challenging image sequences demonstrate that the proposed tracking algorithm achieves more favorable performance than several state-of-the-art methods.

  2. Object detection and tracking method of AUV based on acoustic vision

    Science.gov (United States)

    Zhang, Tie-dong; Wan, Lei; Zeng, Wen-jing; Xu, Yu-ru

    2012-12-01

    This paper describes a new framework for object detection and tracking of AUV including underwater acoustic data interpolation, underwater acoustic images segmentation and underwater objects tracking. This framework is applied to the design of vision-based method for AUV based on the forward looking sonar sensor. First, the real-time data flow (underwater acoustic images) is pre-processed to form the whole underwater acoustic image, and the relevant position information of objects is extracted and determined. An improved method of double threshold segmentation is proposed to resolve the problem that the threshold cannot be adjusted adaptively in the traditional method. Second, a representation of region information is created in light of the Gaussian particle filter. The weighted integration strategy combining the area and invariant moment is proposed to perfect the weight of particles and to enhance the tracking robustness. Results obtained on the real acoustic vision platform of AUV during sea trials are displayed and discussed. They show that the proposed method can detect and track the moving objects underwater online, and it is effective and robust.

  3. Internet of Things based on smart objects technology, middleware and applications

    CERN Document Server

    Trunfio, Paolo

    2014-01-01

    The Internet of Things (IoT) usually refers to a world-wide network of interconnected heterogeneous objects (sensors, actuators, smart devices, smart objects, RFID, embedded computers, etc) uniquely addressable, based on standard communication protocols. Beyond such a definition, it is emerging a new definition of IoT seen as a loosely coupled, decentralized system of cooperating smart objects (SOs). A SO is an autonomous, physical digital object augmented with sensing/actuating, processing, storing, and networking capabilities. SOs are able to sense/actuate, store, and interpret information created within themselves and around the neighbouring external world where they are situated, act on their own, cooperate with each other, and exchange information with other kinds of electronic devices and human users. However, such SO-oriented IoT raises many in-the-small and in-the-large issues involving SO programming, IoT system architecture/middleware and methods/methodologies for the development of SO-based applica...

  4. A Model-Based Approach to Object-Oriented Software Metrics

    Institute of Scientific and Technical Information of China (English)

    梅宏; 谢涛; 杨芙清

    2002-01-01

    The need to improve software productivity and software quality has put for-ward the research on software metrics technology and the development of software metrics toolto support related activities. To support object-oriented software metrics practice effectively,a model-based approach to object-oriented software metrics is proposed in this paper. Thisapproach guides the metrics users to adopt the quality metrics model to measure the object-oriented software products. The development of the model can be achieved by using a top-downapproach. This approach explicitly proposes the conception of absolute normalization computa-tion and relative normalization computation for a metrics model. Moreover, a generic softwaremetrics tool - Jade Bird Object-Oriented Metrics Tool (JBOOMT) is designed to implementthis approach. The parser-based approach adopted by the tool makes the information of thesource program accurate and complete for measurement. It supports various customizablehierarchical metrics models and provides a flexible user interface for users to manipulate themodels. It also supports absolute and relative normalization mechanisms in different situations.

  5. Object-Oriented Change Detection for Remote Sensing Images Based on Multi-Scale Fusion

    Science.gov (United States)

    Feng, Wenqing; Sui, Haigang; Tu, Jihui

    2016-06-01

    In the process of object-oriented change detection, the determination of the optimal segmentation scale is directly related to the subsequent change information extraction and analysis. Aiming at this problem, this paper presents a novel object-level change detection method based on multi-scale segmentation and fusion. First of all, the fine to coarse segmentation is used to obtain initial objects of different sizes; then, according to the features of the objects, Change Vector Analysis is used to obtain the change detection results of various scales. Furthermore, in order to improve the accuracy of change detection, this paper introduces fuzzy fusion and two kinds of decision level fusion methods to get the results of multi-scale fusion. Based on these methods, experiments are done with SPOT5 multi-spectral remote sensing imagery. Compared with pixel-level change detection methods, the overall accuracy of our method has been improved by nearly 10%, and the experimental results prove the feasibility and effectiveness of the fusion strategies.

  6. Three dimensional reconstruction of irregular object with indigent texture based on structured light

    Science.gov (United States)

    Zheng, Li; Zhang, Jianqing; Zhan, Zongqian

    2005-11-01

    In this paper we describe three dimensional (3D) reconstruction of irregular object lack of texture based on structured light techniques. This system uses a CCD camera synchronized with the DLP projector captures the images, from which the 3D shape of the object is reconstructed. With the characteristic of the right image obtained from the projector and collinearity equations, the spacial point coordinates on the surface of the irregular object are obtained quickly by space intersection. As the grid table is rotating, the projector and the CCD camera are always fixed. Then all the point coordinates of different surfaces are computed in the same reference frame while the interior and exterior orientation elements of the CCD camera and projector are obtained in each different point of view. A CCD camera is also used to capture images for texture mapping. The untouched method based on close-range photogrammetry can be successfully adapted to reconstruct various kinds of shapes and some soft objects in the diverse areas.

  7. Personalised Learning Object System Based on Self-Regulated Learning Theories

    Directory of Open Access Journals (Sweden)

    Ali Alharbi

    2014-06-01

    Full Text Available Self-regulated learning has become an important construct in education research in the last few years. Selfregulated learning in its simple form is the learner’s ability to monitor and control the learning process. There is increasing research in the literature on how to support students become more self-regulated learners. However, the advancement in the information technology has led to paradigm changes in the design and development of educational content. The concept of learning object instructional technology has emerged as a result of this shift in educational technology paradigms. This paper presents the results of a study that investigated the potential educational effectiveness of a pedagogical framework based on the self-regulated learning theories to support the design of learning object systems to help computer science students. A prototype learning object system was developed based on the contemporary research on self-regulated learning. The system was educationally evaluated in a quasi-experimental study over two semesters in a core programming languages concepts course. The evaluation revealed that a learning object system that takes into consideration contemporary research on self-regulated learning can be an effective learning environment to support computer science education.

  8. Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics

    Directory of Open Access Journals (Sweden)

    Mirko M. Stojiljković

    2014-12-01

    Full Text Available In this paper, a methodology for multi-objective optimization of trigeneration plants is presented. It is primarily applicable to the systems for buildings’ energy supply characterized by high load variations on daily, weekly and annual bases, as well as the components applicable for flexible operation. The idea is that this approach should enable high accuracy and flexibility in mathematical modeling, while remaining efficient enough. The optimization problem is structurally decomposed into two new problems. The main problem of synthesis and design optimization is combinatorial and solved with different metaheuristic methods. For each examined combination of the synthesis and design variables, when calculating the values of the objective functions, the inner, mixed integer linear programming operation optimization problem is solved with the branch-and-cut method. The applicability of the exploited metaheuristic methods is demonstrated. This approach is compared with the alternative, superstructure-based approach. The potential for combining them is also examined. The methodology is applied for multi-objective optimization of a trigeneration plant that could be used for the energy supply of a real residential settlement in Niš, Serbia. Here, two objectives are considered: annual total costs and primary energy consumption. Results are obtained in the form of a Pareto chart using the epsilon-constraint method.

  9. PE-CMOS based C-scan ultrasound for foreign object detection in soft tissue.

    Science.gov (United States)

    Liu, Chu-Chuan; Lo, Shih-Chung Ben; Freedman, Matthew T; Lasser, Marvin E; Kula, John; Sarcone, Anita; Wang, Yue

    2010-01-01

    In this paper, we introduce a C-scan ultrasound prototype and three imaging modalities for the detection of foreign objects inserted in porcine soft tissue. The object materials include bamboo, plastics, glass and aluminum alloys. The images of foreign objects were acquired using the C-scan ultrasound, a portable B-scan ultrasound, film-based radiography, and computerized radiography. The C-scan ultrasound consists of a plane wave transducer, a compound acoustic lens system, and a newly developed ultrasound sensor array based on the complementary metal-oxide semiconductor coated with piezoelectric material (PE-CMOS). The contrast-to-noise ratio (CNR) of the images were analyzed to quantitatively evaluate the detectability using different imaging modalities. The experimental results indicate that the C-scan prototype has better CNR values in 4 out of 7 objects than other modalities. Specifically, the C-scan prototype provides more detail information of the soft tissues without the speckle artifacts that are commonly seen with conventional B-scan ultrasound, and has the same orientation as the standard radiographs but without ionizing radiation. PMID:20036873

  10. Recovering Use Case Diagrams from Object Oriented Code: an MDA-based Approach

    Directory of Open Access Journals (Sweden)

    Claudia T. Pereira

    2012-07-01

    Full Text Available Modernization of legacy systems requires the existence of technical frameworks for information integration and tool interoperability that allow managing new platform technologies, design techniques and processes. MDA (Model Driven Architecture, adopted by the OMG (Object Management Group, is aligned with this requirement. Reverse engineering techniques play a crucial role in system modernization. In light of these issues, this article describes a framework to reverse engineering MDA models from object oriented code. This framework distinguishes three different abstraction levels linked to models, metamodels and formal specifications. At model level, transformations are based on static and dynamic analysis. At metamodel level, transformations are specified as OCL (Object Constraint Language contracts between MOF (Meta Object Facility metamodels which control the consistency of these transformations. The level of formal specification includes algebraic specifications of MOF metamodels and metamodel-based transformations. This article shows how to reverse engineering use case diagrams from Java code in the MDA context focusing on transformations at model and metamodel levels. We validate our approach by using Eclipse Modeling Framework, Ecore metamodels and ATL (Atlas Transformation Language.

  11. Robust Object-Based Watermarking Using SURF Feature Matching and DFT Domain

    Directory of Open Access Journals (Sweden)

    M. Cedillo-Hernandez

    2013-12-01

    Full Text Available In this paper we propose a robust object-based watermarking method, in which the watermark is embedded into the middle frequencies band of the Discrete Fourier Transform (DFT magnitude of the selected object region, altogether with the Speeded Up Robust Feature (SURF algorithm to allow the correct watermark detection, even if the watermarked image has been distorted. To recognize the selected object region after geometric distortions, during the embedding process the SURF features are estimated and stored in advance to be used during the detection process. In the detection stage, the SURF features of the distorted image are estimated and match them with the stored ones. From the matching result, SURF features are used to compute the Affine-transformation parameters and the object region is recovered. The quality of the watermarked image is measured using the Peak Signal to Noise Ratio (PSNR, Structural Similarity Index (SSIM and the Visual Information Fidelity (VIF. The experimental results show the proposed method provides robustness against several geometric distortions, signal processing operations and combined distortions. The receiver operating characteristics (ROC curves also show the desirable detection performance of the proposed method. The comparison with a previously reported methods based on different techniques is also provided.

  12. Strategic flight assignment approach based on multi-objective parallel evolution algorithm with dynamic migration interval

    Directory of Open Access Journals (Sweden)

    Zhang Xuejun

    2015-04-01

    Full Text Available The continuous growth of air traffic has led to acute airspace congestion and severe delays, which threatens operation safety and cause enormous economic loss. Flight assignment is an economical and effective strategic plan to reduce the flight delay and airspace congestion by reasonably regulating the air traffic flow of China. However, it is a large-scale combinatorial optimization problem which is difficult to solve. In order to improve the quality of solutions, an effective multi-objective parallel evolution algorithm (MPEA framework with dynamic migration interval strategy is presented in this work. Firstly, multiple evolution populations are constructed to solve the problem simultaneously to enhance the optimization capability. Then a new strategy is proposed to dynamically change the migration interval among different evolution populations to improve the efficiency of the cooperation of populations. Finally, the cooperative co-evolution (CC algorithm combined with non-dominated sorting genetic algorithm II (NSGA-II is introduced for each population. Empirical studies using the real air traffic data of the Chinese air route network and daily flight plans show that our method outperforms the existing approaches, multi-objective genetic algorithm (MOGA, multi-objective evolutionary algorithm based on decomposition (MOEA/D, CC-based multi-objective algorithm (CCMA as well as other two MPEAs with different migration interval strategies.

  13. Object Detection and Tracking Method of AUV Based on Acoustic Vision

    Institute of Scientific and Technical Information of China (English)

    ZHANG Tie-dong; WAN Lei; ZENG Wen-jing; XU Yu-ru

    2012-01-01

    This paper describes a new framework for object detection and tracking of AUV including underwater acoustic data interpolation,underwater acoustic images segmentation and underwater objects tracking.This framework is applied to the design of vision-based method for AUV based on the forward looking sonar sensor.First,the real-time data flow (underwater acoustic images) is pre-processed to form the whole underwater acoustic image,and the relevant position information of objects is extracted and determined.An improved method of double threshold segmentation is proposed to resolve the problem that the threshold cannot be adjusted adaptively in the traditional method.Second,a representation of region information is created in light of the Gaussian particle filter.The weighted integration strategy combining the area and invariant moment is proposed to perfect the weight of particles and to enhance the tracking robustness.Results obtained on the real acoustic vision platform of AUV during sea trials are displayed and discussed.They show that the proposed method can detect and track the moving objects underwater online,and it is effective and robust.

  14. A 3-Step Algorithm Using Region-Based Active Contours for Video Objects Detection

    Directory of Open Access Journals (Sweden)

    Stéphanie Jehan-Besson

    2002-06-01

    Full Text Available We propose a 3-step algorithm for the automatic detection of moving objects in video sequences using region-based active contours. First, we introduce a very full general framework for region-based active contours with a new Eulerian method to compute the evolution equation of the active contour from a criterion including both region-based and boundary-based terms. This framework can be easily adapted to various applications, thanks to the introduction of functions named descriptors of the different regions. With this new Eulerian method based on shape optimization principles, we can easily take into account the case of descriptors depending upon features globally attached to the regions. Second, we propose a 3-step algorithm for detection of moving objects, with a static or a mobile camera, using region-based active contours. The basic idea is to hierarchically associate temporal and spatial information. The active contour evolves with successively three sets of descriptors: a temporal one, and then two spatial ones. The third spatial descriptor takes advantage of the segmentation of the image in intensity homogeneous regions. User interaction is reduced to the choice of a few parameters at the beginning of the process. Some experimental results are supplied.

  15. Unified web-based network management based on distributed object orientated software agents

    Science.gov (United States)

    Djalalian, Amir; Mukhtar, Rami; Zukerman, Moshe

    2002-09-01

    This paper presents an architecture that provides a unified web interface to managed network devices that support CORBA, OSI or Internet-based network management protocols. A client gains access to managed devices through a web browser, which is used to issue management operations and receive event notifications. The proposed architecture is compatible with both the OSI Management reference Model and CORBA. The steps required for designing the building blocks of such architecture are identified.

  16. Empirical analysis of web-based user-object bipartite networks

    CERN Document Server

    Shang, Mingsheng; Zhang, Yi-Cheng; Zhou, Tao

    2009-01-01

    Understanding the structure and evolution of web-based user-object networks is a significant task since they play a crucial role in e-commerce nowadays. This Letter reports the empirical analysis on two large-scale web sites, audioscrobbler.com and del.icio.us, where users are connected with music groups and bookmarks, respectively. The degree distributions and degree-degree correlations for both users and objects are reported. We propose a new index, named collaborative clustering coefficient, to quantify the clustering behavior based on the collaborative selection. Accordingly, the clustering properties and clustering-degree correlations are investigated. We report some novel phenomena well characterizing the selection mechanism of web users and outline the relevance of these phenomena to the information recommendation problem.

  17. Retrospective cues based on object features improve visual working memory performance in older adults.

    Science.gov (United States)

    Gilchrist, Amanda L; Duarte, Audrey; Verhaeghen, Paul

    2016-01-01

    Research with younger adults has shown that retrospective cues can be used to orient top-down attention toward relevant items in working memory. We examined whether older adults could take advantage of these cues to improve memory performance. Younger and older adults were presented with visual arrays of five colored shapes; during maintenance, participants were presented either with an informative cue based on an object feature (here, object shape or color) that would be probed, or with an uninformative, neutral cue. Although older adults were less accurate overall, both age groups benefited from the presentation of an informative, feature-based cue relative to a neutral cue. Surprisingly, we also observed differences in the effectiveness of shape versus color cues and their effects upon post-cue memory load. These results suggest that older adults can use top-down attention to remove irrelevant items from visual working memory, provided that task-relevant features function as cues. PMID:26208404

  18. Implementation of a strain energy-based nonlinear finite element in the object-oriented environment

    Science.gov (United States)

    Wegner, Tadeusz; Pęczak, Andrzej

    2010-03-01

    The objective of the paper is to describe a novel finite element computational method based on a strain energy density function and to implement it in the object-oriented environment. The original energy-based finite element was put into the known standard framework of classes and handled in a different manner. The nonlinear properties of material are defined with a modified strain energy density function. The local relaxation procedure proposed as a method used to resolve a nonlinear problem is implemented in C++ language. The hexahedral element with eight nodes as well as the adaptation of the nonlinear finite element is introduced. The chosen numerical model is made of nearly incompressible hyperelastic material. The application of the proposed element is shown on the example of a rectangular parallelepiped with a hollow port.

  19. Computation of Edge-Edge-Edge Events Based on Conicoid Theory for 3-D Object Recognition

    Institute of Scientific and Technical Information of China (English)

    WU Chenye; MA Huimin

    2009-01-01

    The availability of a good viewpoint space partition is crucial in three dimensional (3-D) object rec-ognition on the approach of aspect graph. There are two important events depicted by the aspect graph ap-proach, edge-edge-edge (EEE) events and edge-vertex (EV) events. This paper presents an algorithm to compute EEE events by characteristic analysis based on conicoid theory, in contrast to current algorithms that focus too much on EV events and often overlook the importance of EEE events. Also, the paper provides a standard flowchart for the viewpoint space partitioning based on aspect graph theory that makes it suitable for perspective models. The partitioning result best demonstrates the algorithm's efficiency with more valu-able viewpoints found with the help of EEE events, which can definitely help to achieve high recognition rate for 3-D object recognition.

  20. An Efficient Role and Object Based Access Control Model Implemented in a PDM System

    Institute of Scientific and Technical Information of China (English)

    HUANG Xiaowen; TAN Jian; HUANG Xiangguo

    2006-01-01

    An effective and reliable access control is crucial to a PDM system. This article has discussed the commonly used access control models, analyzed their advantages and disadvantages, and proposed a new Role and Object based access control model that suits the particular needs of a PDM system. The new model has been implemented in a commercial PDM system, which has demonstrated enhanced flexibility and convenience.

  1. Viola-Jones based hybrid framework for real-time object detection in multispectral images

    Science.gov (United States)

    Kuznetsova, E.; Shvets, E.; Nikolaev, D.

    2015-12-01

    This paper describes a method for real-time object detection based on a hybrid of a Viola-Jones cascade with a convolutional neural network. This scheme allows flexible trade-offs between detection quality and computational performance. We also propose a generalization of this method to multispectral images that effectively and efficiently utilizes information from each spectral channel. The new scheme is experimentally compared to traditional Viola-Jones, showing improved detection quality with adjustable performance.

  2. Creating telecommunication services based on object-oriented frameworks and SDL

    OpenAIRE

    Sinnott, R. O.; Kolberg, M.

    1999-01-01

    This paper describes the tools and techniques being applied in the TINA Open Service Creation Architecture (TOSCA) project to develop object-oriented models of distributed telecommunication services in SDL. The paper also describes the way in which Tree and Tabular Combined Notation (TTCN) test cases are derived from these models and subsequently executed against the CORBA-based implementations of these services through a TTCN/CORBA gateway.

  3. 3D MODELLING AND INTERACTIVE WEB-BASED VISUALIZATION OF CULTURAL HERITAGE OBJECTS

    OpenAIRE

    Koeva, M. N.

    2016-01-01

    Nowadays, there are rapid developments in the fields of photogrammetry, laser scanning, computer vision and robotics, together aiming to provide highly accurate 3D data that is useful for various applications. In recent years, various LiDAR and image-based techniques have been investigated for 3D modelling because of their opportunities for fast and accurate model generation. For cultural heritage preservation and the representation of objects that are important for tourism and their interact...

  4. Query and Update Efficient B+-Tree Based Indexing of Moving Objects

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard; Lin, Dan; Ooi, Beng Chin

    2004-01-01

    A number of emerging applications of data management technology involve the monitoring and querying of large quantities of continuous variables, e.g., the positions of mobile service users, termed moving objects. In such applications, large quantities of state samples obtained via sensors are str...... the performance characteristics of the proposal and also shows that it is capable of substantially outperforming the R-tree based TPR-tree for both single and concurrent access scenarios....

  5. Comparing Machine Learning Classifiers for Object-Based Land Cover Classification Using Very High Resolution Imagery

    OpenAIRE

    Yuguo Qian; Weiqi Zhou; Jingli Yan; Weifeng Li; Lijian Han

    2014-01-01

    This study evaluates and compares the performance of four machine learning classifiers—support vector machine (SVM), normal Bayes (NB), classification and regression tree (CART) and K nearest neighbor (KNN)—to classify very high resolution images, using an object-based classification procedure. In particular, we investigated how tuning parameters affect the classification accuracy with different training sample sizes. We found that: (1) SVM and NB were superior to CART and KNN, and both could...

  6. A Java-based Smart Object Model for use in Digital Learning Environments

    OpenAIRE

    Pushpagiri, Vara Prashanth

    2003-01-01

    The last decade has seen the scope of digital library usage extend from data warehousing and other common library services to building quality collections of electronic resources and providing web-based information retrieval mechanisms for distributed learning. This is clear from the number of ongoing research initiatives aiming to provide dynamic learning environments. A major task in providing learning environments is to define a resource model (learning object). The flexibility of the ...

  7. Semantic annotation of multilingual learning objects based on a domain ontology

    OpenAIRE

    Knoth, Petr

    2009-01-01

    One of the important tasks in the use of learning resources in e-learning is the necessity to annotate learning objects with appropriate metadata. However, annotating resources by hand is time consuming and difficult. Here we explore the problem of automatic extraction of metadata for description of learning resources. First, theoretical constraints for gathering certain types of metadata important for e-learning systems are discussed. Our approach to annotation is then outlined. This is base...

  8. Dual objective active suspension system based on a novel nonlinear disturbance compensator

    Science.gov (United States)

    Deshpande, Vaijayanti S.; Shendge, P. D.; Phadke, S. B.

    2016-09-01

    This paper proposes an active suspension system to fulfil the dual objective of improving ride comfort while trying to keep the suspension deflection within the limits of the rattle space. The scheme is based on a novel nonlinear disturbance compensator which employs a nonlinear function of the suspension deflection. The scheme is analysed and validated by simulation and experimentation on a laboratory setup. The performance is compared with a passive suspension system for a variety of road profiles.

  9. Fourier-transform Ghost Imaging for pure phase object based on Compressive Sampling algorithm

    OpenAIRE

    Wang, Hui; Han, Shensheng

    2009-01-01

    A special algorithm for the Fourier-transform Ghost Imaging (GI) scheme is discussed based on the Compressive Sampling (CS) theory. Though developed mostly in real space, CS algorithm could also be used for the Fourier spectrum reconstruction of pure phase object by setting a proper sensing matrix. This could find its application in diffraction imaging of X-ray, neutron and electron with higher efficiency and resolution. Simulation and experiment results are also presented to prove the feasib...

  10. Home-Explorer: Ontology-Based Physical Artifact Search and Hidden Object Detection System

    OpenAIRE

    Bin Guo; Satoru Satake; Michita Imai

    2008-01-01

    A new system named Home-Explorer that searches and finds physical artifacts in a smart indoor environment is proposed. The view on which it is based is artifact-centered and uses sensors attached to the everyday artifacts (called smart objects) in the real world. This paper makes two main contributions: First, it addresses, the robustness of the embedded sensors, which is seldom discussed in previous smart artifact research. Because sensors may sometimes be broken or fail to work under certai...

  11. Validating an objective video-based dyskinesia severity score in Parkinson’s disease patients

    OpenAIRE

    Rao, Anusha Sathyanarayanan; Dawant, Benoit M.; Bodenheimer, Robert E.; Li, Rui; Fang, John; Phibbs, Fenna; Hedera, Peter; Davis, Thomas

    2012-01-01

    Dyskinesia is a common side effect of prolonged dopaminergic therapy in Parkinson’s disease patients. Assessing the severity of dyskinesia can help develop better pharmacological and surgical interventions. We have developed a semi-automatic video-based objective dyskinesia quantifying measure called the severity score (SVS) that was evaluated on 35 patient videos. We present a study to evaluate the utility of our severity score and compare its performance to clinical ratings of neurologists....

  12. Evidence-Based Robust Design of Deflection Actions for Near Earth Objects

    OpenAIRE

    Zuiani, Federico; Vasile, Massimiliano; Gibbings, Alison

    2012-01-01

    This paper presents a novel approach to the robust design of deflection actions for Near Earth Objects (NEO). In particular, the case of deflection by means of Solar-pumped Laser ablation is studied here in detail. The basic idea behind Laser ablation is that of inducing a sublimation of the NEO surface, which produces a low thrust thereby slowly deviating the asteroid from its initial Earth threatening trajectory. This work investigates the integrated design of the Space-based Laser system a...

  13. Real-Time Object Recognition Based on Cortical Multi-scale Keypoints

    OpenAIRE

    Tersic, K.; Rodrigues, J. M. F.; du Buf, J. M. H.

    2013-01-01

    In recent years, a large number of impressive object categorisation algorithms have surfaced, both computational and biologically motivated. While results on standardised benchmarks are impressive, very few of the best-performing algorithms took run-time performance into account, rendering most of them useless for real-time active vision scenarios such as cognitive robots. In this paper, we combine cortical keypoints based on primate area V1 with a state-of-the-art nearest neighbour classifie...

  14. Object-Based Crop Classification with Landsat-MODIS Enhanced Time-Series Data

    OpenAIRE

    Qingting Li; Cuizhen Wang; Bing Zhang; Linlin Lu

    2015-01-01

    Cropland mapping via remote sensing can provide crucial information for agri-ecological studies. Time series of remote sensing imagery is particularly useful for agricultural land classification. This study investigated the synergistic use of feature selection, Object-Based Image Analysis (OBIA) segmentation and decision tree classification for cropland mapping using a finer temporal-resolution Landsat-MODIS Enhanced time series in 2007. The enhanced time series extracted 26 layers of Normali...

  15. Application Mapping and Communication Synthesis for Object-Oriented Platform-Based Design

    OpenAIRE

    Grüttner, Kim

    2015-01-01

    Platform-based design of embedded systems on a chip consists of the parallel functional application specification, configuration of the hardware platform (i.e. connection of processing, memory and physical communication channels) and mapping of the application description on the processing, memory and communication resources of the hardware platform. The main contribution of this work is the seamless object-oriented modelling and automatic refinement of communication. In the application model...

  16. A NEW FRAMEWORK FOR OBJECT-BASED IMAGE ANALYSIS BASED ON SEGMENTATION SCALE SPACE AND RANDOM FOREST CLASSIFIER

    Directory of Open Access Journals (Sweden)

    A. Hadavand

    2015-12-01

    Full Text Available In this paper a new object-based framework is developed for automate scale selection in image segmentation. The quality of image objects have an important impact on further analyses. Due to the strong dependency of segmentation results to the scale parameter, choosing the best value for this parameter, for each class, becomes a main challenge in object-based image analysis. We propose a new framework which employs pixel-based land cover map to estimate the initial scale dedicated to each class. These scales are used to build segmentation scale space (SSS, a hierarchy of image objects. Optimization of SSS, respect to NDVI and DSM values in each super object is used to get the best scale in local regions of image scene. Optimized SSS segmentations are finally classified to produce the final land cover map. Very high resolution aerial image and digital surface model provided by ISPRS 2D semantic labelling dataset is used in our experiments. The result of our proposed method is comparable to those of ESP tool, a well-known method to estimate the scale of segmentation, and marginally improved the overall accuracy of classification from 79% to 80%.

  17. Moment feature based fast feature extraction algorithm for moving object detection using aerial images.

    Directory of Open Access Journals (Sweden)

    A F M Saifuddin Saif

    Full Text Available Fast and computationally less complex feature extraction for moving object detection using aerial images from unmanned aerial vehicles (UAVs remains as an elusive goal in the field of computer vision research. The types of features used in current studies concerning moving object detection are typically chosen based on improving detection rate rather than on providing fast and computationally less complex feature extraction methods. Because moving object detection using aerial images from UAVs involves motion as seen from a certain altitude, effective and fast feature extraction is a vital issue for optimum detection performance. This research proposes a two-layer bucket approach based on a new feature extraction algorithm referred to as the moment-based feature extraction algorithm (MFEA. Because a moment represents the coherent intensity of pixels and motion estimation is a motion pixel intensity measurement, this research used this relation to develop the proposed algorithm. The experimental results reveal the successful performance of the proposed MFEA algorithm and the proposed methodology.

  18. Automated Visual Inspection: Position Identification of Object for Industrial Robot Application based on Color and Shape

    Directory of Open Access Journals (Sweden)

    Muralindran Mariappan

    2016-01-01

    Full Text Available Inspection task is traditionally carried out by human. However, Automated Visual Inspection (AVI has gradually become more popular than human inspection due to the advantageous in the aspect of high precision and short processing time. Therefore, this paper proposed a system which identifies the object’s position for industrial robot based on colors and shapes where, red, green, blue and circle, square, triangle are recognizable. The proposed system is capable to identify the object’s position in three modes, either based on color, shape or both color and shape of the desired objects. During the image processing, RGB color space is utilized by the proposed system while winner take all approach is used to classify the color of the object through the evaluation of the pixel’s intensity value of the R, G and B channel. Meanwhile, the shapes and position of the objects are determined based on the compactness and the centroid of the region respectively. Camera settings, such as brightness, contrast and exposure is another important factor which can affect the performance of the proposed system. Lastly, a Graphical User Interface was developed. The experimental result shows that the developed system is highly efficient when implemented in the selected database.

  19. Geographic Object-Based Image Analysis – Towards a new paradigm

    Science.gov (United States)

    Blaschke, Thomas; Hay, Geoffrey J.; Kelly, Maggi; Lang, Stefan; Hofmann, Peter; Addink, Elisabeth; Queiroz Feitosa, Raul; van der Meer, Freek; van der Werff, Harald; van Coillie, Frieke; Tiede, Dirk

    2014-01-01

    The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the ‘per-pixel paradigm’ and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm. PMID:24623958

  20. An advanced object-based software framework for complex ecosystem modeling and simulation

    Energy Technology Data Exchange (ETDEWEB)

    Sydelko, P. J.; Dolph, J. E.; Majerus, K. A.; Taxon, T. N.

    2000-06-29

    Military land managers and decision makers face an ever increasing challenge to balance maximum flexibility for the mission with a diverse set of multiple land use, social, political, and economic goals. In addition, these goals encompass environmental requirements for maintaining ecosystem health and sustainability over the long term. Spatiotemporal modeling and simulation in support of adaptive ecosystem management can be best accomplished through a dynamic, integrated, and flexible approach that incorporates scientific and technological components into a comprehensive ecosystem modeling framework. The Integrated Dynamic Landscape Analysis and Modeling System (IDLAMS) integrates ecological models and decision support techniques through a geographic information system (GIS)-based backbone. Recently, an object-oriented (OO) architectural framework was developed for IDLAMS (OO-IDLAMS). This OO-IDLAMS Prototype was built upon and leverages from the Dynamic Information Architecture System (DIAS) developed by Argonne National Laboratory. DIAS is an object-based architectural framework that affords a more integrated, dynamic, and flexible approach to comprehensive ecosystem modeling than was possible with the GIS-based integration approach of the original IDLAMS. The flexibility, dynamics, and interoperability demonstrated through this case study of an object-oriented approach have the potential to provide key technology solutions for many of the military's multiple-use goals and needs for integrated natural resource planning and ecosystem management.

  1. A novel space-based observation strategy for GEO objects based on daily pointing adjustment of multi-sensors

    Science.gov (United States)

    Hu, Yun-peng; Li, Ke-bo; Xu, Wei; Chen, Lei; Huang, Jian-yu

    2016-08-01

    Space-based visible (SBV) program has been proved to be with a large advantage to observe geosynchronous earth orbit (GEO) objects. With the development of SBV observation started from 1996, many strategies have come out for the purpose of observing GEO objects more efficiently. However it is a big challenge to visit all the GEO objects in a relatively short time because of the distribution characteristics of GEO belt and limited field of view (FOV) of sensor. And it's also difficult to keep a high coverage of the GEO belt every day in a whole year. In this paper, a space-based observation strategy for GEO objects is designed based on the characteristics of the GEO belt. The mathematical formula of GEO belt is deduced and the evolvement of GEO objects is illustrated. There are basically two kinds of orientation strategies for most observation satellites, i.e., earth-oriented and inertia-directional. Influences of both strategies to their own observation regions are analyzed and compared with each other. A passive optical instrument with daily attitude-adjusting strategies is proposed to increase the daily coverage rate of GEO objects in a whole year. Furthermore, in order to observe more GEO objects in a relatively short time, the strategy of a satellite with multi-sensors is proposed. The installation parameters between different sensors are optimized, more than 98% of GEO satellites can be observed every day and almost all the GEO satellites can be observed every two days with 3 sensors (FOV: 6° × 6°) on the satellite under the strategy of daily pointing adjustment in a whole year.

  2. Geomorphological change detection using object-based feature extraction from multi-temporal LIDAR data

    OpenAIRE

    Seijmonsbergen, A. C.; Anders, N.S.; W. Bouten

    2012-01-01

    Multi-temporal LiDAR DTMs are used for the development and testing of a method for geomorphological change analysis in western Austria. Our test area is located on a mountain slope in the Gargellen Valley in western Austria. Six geomorphological features were mapped by using stratified Object-Based Image Analysis (OBIA) and segmentation optimization using 1m LiDAR DTMs of 2002 and 2005. Based on the 2002 data, the scale parameter for each geomorphological feature was optimized by comparing ma...

  3. Wireless Location Determination for Mobile Objects Based on GSM in Intelligent Transportation Systems

    Institute of Scientific and Technical Information of China (English)

    徐志扬; 施鹏飞

    2003-01-01

    The mobile object (MO) location determination technologies which can be used in intelligent transportation system (ITS) are studied in this paper. The principles and characteristics of wireless location determination technologies are introduced and the characteristics of GSM useful for location determination are also summarized. An experimental positioning system based on GSM is proposed, and the architecture is described. TOA method based on GSM signals and TDOA method are used in the experimental system. Moreover, the methods are simulated. The performance of the positioning methods is assessed in the simulation environment, and the accuracy for 67% mobile stations (MS) is 70m in urban areas.

  4. Multi-objective optimum design of fast tool servo based on improved differential evolution algorithm

    International Nuclear Information System (INIS)

    The flexure-based mechanism is a promising realization of fast tool servo (FTS), and the optimum determination of flexure hinge parameters is one of the most important elements in the FTS design. This paper presents a multi-objective optimization approach to optimizing the dimension and position parameters of the flexure-based mechanism, which is based on the improved differential evolution algorithm embedding chaos and nonlinear simulated anneal algorithm. The results of optimum design show that the proposed algorithm has excellent performance and a well-balanced compromise is made between two conflicting objectives, the stroke and natural frequency of the FTS mechanism. The validation tests based on finite element analysis (FEA) show good agreement with the results obtained by using the proposed theoretical algorithm of this paper. Finally, a series of experimental tests are conducted to validate the design process and assess the performance of the FTS mechanism. The designed FTS reaches up to a stroke of 10.25 μm with at least 2 kHz bandwidth. Both of the FEA and experimental results demonstrate that the parameters of the flexure-based mechanism determined by the proposed approaches can achieve the specified performance and the proposed approach is suitable for the optimum design of FTS mechanism and of excellent performances

  5. Highly accurate moving object detection in variable bit rate video-based traffic monitoring systems.

    Science.gov (United States)

    Huang, Shih-Chia; Chen, Bo-Hao

    2013-12-01

    Automated motion detection, which segments moving objects from video streams, is the key technology of intelligent transportation systems for traffic management. Traffic surveillance systems use video communication over real-world networks with limited bandwidth, which frequently suffers because of either network congestion or unstable bandwidth. Evidence supporting these problems abounds in publications about wireless video communication. Thus, to effectively perform the arduous task of motion detection over a network with unstable bandwidth, a process by which bit-rate is allocated to match the available network bandwidth is necessitated. This process is accomplished by the rate control scheme. This paper presents a new motion detection approach that is based on the cerebellar-model-articulation-controller (CMAC) through artificial neural networks to completely and accurately detect moving objects in both high and low bit-rate video streams. The proposed approach is consisted of a probabilistic background generation (PBG) module and a moving object detection (MOD) module. To ensure that the properties of variable bit-rate video streams are accommodated, the proposed PBG module effectively produces a probabilistic background model through an unsupervised learning process over variable bit-rate video streams. Next, the MOD module, which is based on the CMAC network, completely and accurately detects moving objects in both low and high bit-rate video streams by implementing two procedures: 1) a block selection procedure and 2) an object detection procedure. The detection results show that our proposed approach is capable of performing with higher efficacy when compared with the results produced by other state-of-the-art approaches in variable bit-rate video streams over real-world limited bandwidth networks. Both qualitative and quantitative evaluations support this claim; for instance, the proposed approach achieves Similarity and F1 accuracy rates that are 76

  6. Objective Evaluation Method of Steering Comfort Based on Movement Quality Evaluation of Driver Steering Maneuver

    Institute of Scientific and Technical Information of China (English)

    YANG Yiyong; LIU Yahui; WANG Man; JI Run; JI Xuewu

    2014-01-01

    The existing research of steering comfort mainly focuses on the subjective evaluation, aiming at designing and optimizing the steering system. In the development of steering system, especially the evaluation of steering comfort, the objective evaluation methods considered the kinematic characteristics of driver steering maneuver are not proposed, which means that the objective evaluation of steering cannot be conducted with the evaluation of kinematic characteristics of driver in steering maneuver. In order to propose the objective evaluation methods of steering comfort, the evaluation of steering movement quality of driver is developed on the basis of the study of the kinematic characteristics of steering maneuver. First, the steering motion trajectories of the driver in both comfortable and certain extreme uncomfortable operation conditions are detected using the Vicon motion capture system. The operation conditions are under the restrictions of the vertical height and horizontal distance between steering wheel center and the H-point of driver, and the steering resisting torque else. Next, the movement quality evaluation of driver steering maneuver is assessed using twelve kinds of evaluation indices based on the kinematic analyses of the steering motion trajectories to propose an objective evaluation method. Finally, an integrated discomfort index of steering maneuver is proposed on the basis of the regression analysis of subjective evaluation rating and the movement quality evaluation indices, including the Jerk, Discomfort and Joint Torque indices. The test results show that the proposed integrated discomfort index gives a good fitting with the subjective evaluation of discomfort, which means it can be used to evaluate or predict the discomfort level of steering maneuver. This paper proposes an objective evaluation method of steering comfort based on the movement quality evaluation of driver steering maneuver.

  7. High Quality Prime Farmland extraction pattern based on object-oriented image analysis

    Science.gov (United States)

    Liu, Yong-xue; Li, Man-chun; Chen, Zhen-jie; Li, Fei-xue; Zhang, Yu; Zhao, Bo; Tan, Lu

    2008-10-01

    High Quality Prime Farmland (HQPF) is high, stable yields based on land consolidation of prime farmland, and has its important impact upon China's food security. To make clear the status-in-quo of the HQPF is important to its construction and management. However, it is difficult to get the spatial distribution information of the constructed HQPF enough rapidly in mountainous area using ground investigation, as well as hard to satisfy the requirements of large-scale promotion. A HQPF extraction framework based on object-oriented image analysis is discussed and applied to aerial imageries of Tonglu County. The approach can be divided into 3 steps: image segmentation, feature analysis & feature selection and extraction rules generation. In the image segmentation procedure, canny operator is used in edge detection, an edge growth algorithm is used to link discontinuous edge, and region labelling is carried out to generate image object. In the feature analysis & selection procedure, object-oriented feature analysis and feature selection methods are also discussed to construct a feature subset with fine divisibility for HQPF extraction. In the extraction rules generation procedure, the C4.5 algorithm is used to establish and trim the decision tree, then HQPF decision rules are generated from the decision tree. Compared with supervised classification (MLC classifier, ERDAS 8.7) and another object-oriented image analysis method (FNEA, e-Cognition4.0), the accuracy assessment shows that the extraction results by the object-oriented extraction patters have a high level of category consistency, size consistency and shape consistency.

  8. PIXEL VS OBJECT-BASED IMAGE CLASSIFICATION TECHNIQUES FOR LIDAR INTENSITY DATA

    Directory of Open Access Journals (Sweden)

    N. El-Ashmawy

    2012-09-01

    Full Text Available Light Detection and Ranging (LiDAR systems are remote sensing techniques used mainly for terrain surface modelling. LiDAR sensors record the distance between the sensor and the targets (range data with a capability to record the strength of the backscatter energy reflected from the targets (intensity data. The LiDAR sensors use the near-infrared spectrum range which provides high separability in the reflected energy by the target. This phenomenon is investigated to use the LiDAR intensity data for land-cover classification. The goal of this paper is to investigate and evaluates the use of different image classification techniques applied on LiDAR intensity data for land cover classification. The two techniques proposed are: a Maximum likelihood classifier used as pixel- based classification technique; and b Image segmentation used as object-based classification technique. A study area covers an urban district in Burnaby, British Colombia, Canada, is selected to test the different classification techniques for extracting four feature classes: buildings, roads and parking areas, trees, and low vegetation (grass areas, from the LiDAR intensity data. Generally, the results show that LiDAR intensity data can be used for land cover classification. An overall accuracy of 63.5% can be achieved using the pixel-based classification technique. The overall accuracy of the results is improved to 68% using the object- based classification technique. Further research is underway to investigate different criteria for segmentation process and to refine the design of the object-based classification algorithm.

  9. 基于UniNet的对象概念研究%Object Concepts Research Based on UniNet

    Institute of Scientific and Technical Information of China (English)

    周国富; 余鹏; 袁崇义

    2003-01-01

    This paper discusses concepts on object from UniNet view and shows that there exists the flow of controlin object system except for exchanging of messages between objects. Meanwhile, the paper presents an independent mechanism of object communication separated from object that will result in a more general reuse of object. With helpof the control flow and the data flow, UniNet can describe not only the static features, but also the dynamic featuresof object system, which naturally solve the inheritance anomaly and the flow of data and control. In addition, based on UniNet specification, the object system can be verified easily and create the program code automatically.

  10. Discriminative boosted forest with convolutional neural network-based patch descriptor for object detection

    Science.gov (United States)

    Xiang, Tao; Li, Tao; Ye, Mao; Li, Xudong

    2016-01-01

    Object detection with intraclass variations is challenging. The existing methods have not achieved the optimal combinations of classifiers and features, especially features learned by convolutional neural networks (CNNs). To solve this problem, we propose an object-detection method based on improved random forest and local image patches represented by CNN features. First, we compute CNN-based patch descriptors for each sample by modified CNNs. Then, the random forest is built whose split functions are defined by patch selector and linear projection learned by linear support vector machine. To improve the classification accuracy, the split functions in each depth of the forest make up a local classifier, and all local classifiers are assembled in a layer-wise manner by a boosting algorithm. The main contributions of our approach are summarized as follows: (1) We propose a new local patch descriptor based on CNN features. (2) We define a patch-based split function which is optimized with maximum class-label purity and minimum classification error over the samples of the node. (3) Each local classifier is assembled by minimizing the global classification error. We evaluate the method on three well-known challenging datasets: TUD pedestrians, INRIA pedestrians, and UIUC cars. The experiments demonstrate that our method achieves state-of-the-art or competitive performance.

  11. Joint source-channel coding for wireless object-based video communications utilizing data hiding.

    Science.gov (United States)

    Wang, Haohong; Tsaftaris, Sotirios A; Katsaggelos, Aggelos K

    2006-08-01

    In recent years, joint source-channel coding for multimedia communications has gained increased popularity. However, very limited work has been conducted to address the problem of joint source-channel coding for object-based video. In this paper, we propose a data hiding scheme that improves the error resilience of object-based video by adaptively embedding the shape and motion information into the texture data. Within a rate-distortion theoretical framework, the source coding, channel coding, data embedding, and decoder error concealment are jointly optimized based on knowledge of the transmission channel conditions. Our goal is to achieve the best video quality as expressed by the minimum total expected distortion. The optimization problem is solved using Lagrangian relaxation and dynamic programming. The performance of the proposed scheme is tested using simulations of a Rayleigh-fading wireless channel, and the algorithm is implemented based on the MPEG-4 verification model. Experimental results indicate that the proposed hybrid source-channel coding scheme significantly outperforms methods without data hiding or unequal error protection.

  12. Uncertain Training Data Edition for Automatic Object-Based Change Map Extraction

    Science.gov (United States)

    Hajahmadi, S.; Mokhtarzadeh, M.; Mohammadzadeh, A.; Valadanzouj, M. J.

    2013-09-01

    Due to the rapid transformation of the societies, and the consequent growth of the cities, it is necessary to study these changes in order to achieve better control and management of urban areas and assist the decision-makers. Change detection involves the ability to quantify temporal effects using multi-temporal data sets. The available maps of the under study area is one of the most important sources for this reason. Although old data bases and maps are a great resource, it is more than likely that the training data extracted from them might contain errors, which affects the procedure of the classification; and as a result the process of the training sample editing is an essential matter. Due to the urban nature of the area studied and the problems caused in the pixel base methods, object-based classification is applied. To reach this, the image is segmented into 4 scale levels using a multi-resolution segmentation procedure. After obtaining the segments in required levels, training samples are extracted automatically using the existing old map. Due to the old nature of the map, these samples are uncertain containing wrong data. To handle this issue, an editing process is proposed according to K-nearest neighbour and k-means algorithms. Next, the image is classified in a multi-resolution object-based manner and the effects of training sample refinement are evaluated. As a final step this classified image is compared with the existing map and the changed areas are detected.

  13. Ecosystem-based management objectives for the North Sea: riding the forage fish rollercoaster

    DEFF Research Database (Denmark)

    Dickey-Collas, Mark; Engelhard, Georg H.; Rindorf, Anna;

    2014-01-01

    The North Sea provides a useful model for considering forage fish (FF) within ecosystem-based management as it has a complex assemblage of FF species. This paper is designed to encourage further debate and dialogue between stakeholders about management objectives. Changing the management of fishe......The North Sea provides a useful model for considering forage fish (FF) within ecosystem-based management as it has a complex assemblage of FF species. This paper is designed to encourage further debate and dialogue between stakeholders about management objectives. Changing the management...... whether maintaining the reserves of prey biomass or a more integral approach of monitoring mortality rates across the trophic system is more robust under the ecosystem approach. In terms of trophic energy transfer, stability, and resilience of the ecosystem, FF should be considered as both a sized......-based pool of biomass and as species components of the system by managers and modellers. Policy developers should not consider the knowledge base robust enough to embark on major projects of ecosystem engineering. Management plans appear able to maintain sustainable exploitation in the short term. Changes...

  14. Global stability-based design optimization of truss structures using multiple objectives

    Indian Academy of Sciences (India)

    Tugrul Talaslioglu

    2013-02-01

    This paper discusses the effect of global stability on the optimal size and shape of truss structures taking into account of a nonlinear critical load, truss weight and serviceability at the same time. The nonlinear critical load is computed by arc-length method. In order to increase the accuracy of the estimation of critical load (ignoring material nonlinearity), an eigenvalue analysis is implemented into the arc-length method. Furthermore, a pure pareto-ranking based multi-objective optimization model is employed for the design optimization of the truss structure with multiple objectives. The computational performance of the optimization model is increased by implementing an island model into its evolutionary search mechanism. The proposed design optimization approach is applied for both size and shape optimization of real world trusses including 101, 224 and 444 bars and successful in generating feasible designations in a large and complex design space. It is observed that the computational performance of pareto-ranking based island model is better than the pure pareto-ranking based model. Therefore, pareto-ranking based island model is recommended to optimize the design of truss structure possessing geometric nonlinearity

  15. Simulated Prosthetic Vision: The Benefits of Computer-Based Object Recognition and Localization.

    Science.gov (United States)

    Macé, Marc J-M; Guivarch, Valérian; Denis, Grégoire; Jouffrais, Christophe

    2015-07-01

    Clinical trials with blind patients implanted with a visual neuroprosthesis showed that even the simplest tasks were difficult to perform with the limited vision restored with current implants. Simulated prosthetic vision (SPV) is a powerful tool to investigate the putative functions of the upcoming generations of visual neuroprostheses. Recent studies based on SPV showed that several generations of implants will be required before usable vision is restored. However, none of these studies relied on advanced image processing. High-level image processing could significantly reduce the amount of information required to perform visual tasks and help restore visuomotor behaviors, even with current low-resolution implants. In this study, we simulated a prosthetic vision device based on object localization in the scene. We evaluated the usability of this device for object recognition, localization, and reaching. We showed that a very low number of electrodes (e.g., nine) are sufficient to restore visually guided reaching movements with fair timing (10 s) and high accuracy. In addition, performance, both in terms of accuracy and speed, was comparable with 9 and 100 electrodes. Extraction of high level information (object recognition and localization) from video images could drastically enhance the usability of current visual neuroprosthesis. We suggest that this method-that is, localization of targets of interest in the scene-may restore various visuomotor behaviors. This method could prove functional on current low-resolution implants. The main limitation resides in the reliability of the vision algorithms, which are improving rapidly.

  16. A web product data management system based on Simple Object Access Protocol

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    A new web product data management architecture is presented. The three-tier web architecture and Simple Object Access Protocol (SOAP) are combined to build the web-based product data management (PDM) system which includes three tiers: the user services tier, the business services tier, and the data services tier. The client service component uses the serverside technology, and Extensible Markup Language (XML) web service which uses SOAP as the communication protocol is chosen as the business service component. To illustrate how to build a web-based PDM system using the proposed architecture,a case PDM system which included three logical tires was built. To use the security and central management features of the database, a stored procedure was recommended in the data services tier. The business object was implemented as an XML web service so that client could use standard internet protocols to communicate with the business object from any platform. In order to satisfy users using all sorts of browser, the server-side technology and Microsoft ASP.NET was used to create the dynamic user interface.

  17. Building and Programming a Smart Robotic System for Distinguishing Objects Based on their Shape and Colour

    Directory of Open Access Journals (Sweden)

    Sharari T. M.

    2015-03-01

    Full Text Available This paper presents a robotic system designed for holding and placing objects based on their colour and shape. The presented robot is given a complete set of instructions of positions and orientation angles for each manipulation motion. The main feature in this paper is that the developed robot used a combination of vision and motion systems for holding and placing the work-objects, mounted on the flat work-plane, based on their shapes and colors. This combination improves the flexibility of manipulation which may help eliminate the use of some expensive manipulation tasks in a variety of industrial applications. The robotic system presented in this paper is designed as an educational robot that possesses the ability for holding-and-placing operations with limited load. To process the various instructions for holding and placing the work objects, a main control unit - Manipulation Control Unit (MCU is used as well as a slave unit that performed the actual instructions from the MCU.

  18. Job-shop Scheduling with Multi-objectives Based on Genetic Algorithms

    Institute of Scientific and Technical Information of China (English)

    周亚勤; 李蓓智; 陈革

    2003-01-01

    The technology of production planning and scheduling is one of the critical technologies that decide whether the automated manufacturing systems can get the expected economy. Job shop scheduling belongs to the special class of NP-hard problems. Most of the algorithms used to optimize this class of problems have an exponential time; that is, the computation time increases exponentially with problem size. In scheduling study, makespan is often considered as the main objective. In this paper, makespan, the due date request of the key jobs, the availability of the key machine, the average wait-time of the jobs, and the similarities between the jobs and so on are taken into accotmt based on the application of mechanical engineering. The job shop scheduling problem with multi-objectives is analyzed and studied by using genetic algorithms based on the mechanics of genetics and natural selection. In this research, the tactics of the coding and decoding and the design of the genetic operators, along with the description of the mathematic model of the multi-objective functions,are presented. Finally an illu-strative example is given to testify the validity of this algorithm.

  19. [An object-based information extraction technology for dominant tree species group types].

    Science.gov (United States)

    Tian, Tian; Fan, Wen-yi; Lu, Wei; Xiao, Xiang

    2015-06-01

    Information extraction for dominant tree group types is difficult in remote sensing image classification, howevers, the object-oriented classification method using high spatial resolution remote sensing data is a new method to realize the accurate type information extraction. In this paper, taking the Jiangle Forest Farm in Fujian Province as the research area, based on the Quickbird image data in 2013, the object-oriented method was adopted to identify the farmland, shrub-herbaceous plant, young afforested land, Pinus massoniana, Cunninghamia lanceolata and broad-leave tree types. Three types of classification factors including spectral, texture, and different vegetation indices were used to establish a class hierarchy. According to the different levels, membership functions and the decision tree classification rules were adopted. The results showed that the method based on the object-oriented method by using texture, spectrum and the vegetation indices achieved the classification accuracy of 91.3%, which was increased by 5.7% compared with that by only using the texture and spectrum.

  20. Moving Object Tracking and Avoidance Algorithm for Differential Driving AGV Based on Laser Measurement Technology

    Directory of Open Access Journals (Sweden)

    Pandu Sandi Pratama

    2012-12-01

    Full Text Available This paper proposed an algorithm to track the obstacle position and avoid the moving objects for differential driving Automatic Guided Vehicles (AGV system in industrial environment. This algorithm has several abilities such as: to detect the moving objects, to predict the velocity and direction of moving objects, to predict the collision possibility and to plan the avoidance maneuver. For sensing the local environment and positioning, the laser measurement system LMS-151 and laser navigation system NAV-200 are applied. Based on the measurement results of the sensors, the stationary and moving obstacles are detected and the collision possibility is calculated. The velocity and direction of the obstacle are predicted using Kalman filter algorithm. Collision possibility, time, and position can be calculated by comparing the AGV movement and obstacle prediction result obtained by Kalman filter. Finally the avoidance maneuver using the well known tangent Bug algorithm is decided based on the calculation data. The effectiveness of proposed algorithm is verified using simulation and experiment. Several examples of experiment conditions are presented using stationary obstacle, and moving obstacles. The simulation and experiment results show that the AGV can detect and avoid the obstacles successfully in all experimental condition. [Keywords— Obstacle avoidance, AGV, differential drive, laser measurement system, laser navigation system].

  1. An object-based classification method for automatic detection of lunar impact craters from topographic data

    Science.gov (United States)

    Vamshi, Gasiganti T.; Martha, Tapas R.; Vinod Kumar, K.

    2016-05-01

    Identification of impact craters is a primary requirement to study past geological processes such as impact history. They are also used as proxies for measuring relative ages of various planetary or satellite bodies and help to understand the evolution of planetary surfaces. In this paper, we present a new method using object-based image analysis (OBIA) technique to detect impact craters of wide range of sizes from topographic data. Multiresolution image segmentation of digital terrain models (DTMs) available from the NASA's LRO mission was carried out to create objects. Subsequently, objects were classified into impact craters using shape and morphometric criteria resulting in 95% detection accuracy. The methodology developed in a training area in parts of Mare Imbrium in the form of a knowledge-based ruleset when applied in another area, detected impact craters with 90% accuracy. The minimum and maximum sizes (diameters) of impact craters detected in parts of Mare Imbrium by our method are 29 m and 1.5 km, respectively. Diameters of automatically detected impact craters show good correlation (R2 > 0.85) with the diameters of manually detected impact craters.

  2. A building extraction approach for Airborne Laser Scanner data utilizing the Object Based Image Analysis paradigm

    Science.gov (United States)

    Tomljenovic, Ivan; Tiede, Dirk; Blaschke, Thomas

    2016-10-01

    In the past two decades Object-Based Image Analysis (OBIA) established itself as an efficient approach for the classification and extraction of information from remote sensing imagery and, increasingly, from non-image based sources such as Airborne Laser Scanner (ALS) point clouds. ALS data is represented in the form of a point cloud with recorded multiple returns and intensities. In our work, we combined OBIA with ALS point cloud data in order to identify and extract buildings as 2D polygons representing roof outlines in a top down mapping approach. We performed rasterization of the ALS data into a height raster for the purpose of the generation of a Digital Surface Model (DSM) and a derived Digital Elevation Model (DEM). Further objects were generated in conjunction with point statistics from the linked point cloud. With the use of class modelling methods, we generated the final target class of objects representing buildings. The approach was developed for a test area in Biberach an der Riß (Germany). In order to point out the possibilities of the adaptation-free transferability to another data set, the algorithm has been applied "as is" to the ISPRS Benchmarking data set of Toronto (Canada). The obtained results show high accuracies for the initial study area (thematic accuracies of around 98%, geometric accuracy of above 80%). The very high performance within the ISPRS Benchmark without any modification of the algorithm and without any adaptation of parameters is particularly noteworthy.

  3. A System based on Adaptive Background Subtraction Approach for Moving Object Detection and Tracking in Videos

    Directory of Open Access Journals (Sweden)

    Bahadır KARASULU

    2013-04-01

    Full Text Available Video surveillance systems are based on video and image processing research areas in the scope of computer science. Video processing covers various methods which are used to browse the changes in existing scene for specific video. Nowadays, video processing is one of the important areas of computer science. Two-dimensional videos are used to apply various segmentation and object detection and tracking processes which exists in multimedia content-based indexing, information retrieval, visual and distributed cross-camera surveillance systems, people tracking, traffic tracking and similar applications. Background subtraction (BS approach is a frequently used method for moving object detection and tracking. In the literature, there exist similar methods for this issue. In this research study, it is proposed to provide a more efficient method which is an addition to existing methods. According to model which is produced by using adaptive background subtraction (ABS, an object detection and tracking system’s software is implemented in computer environment. The performance of developed system is tested via experimental works with related video datasets. The experimental results and discussion are given in the study

  4. Multi-objective scheduling in an agent based Holonic manufacturing system

    Directory of Open Access Journals (Sweden)

    T. K. Jana

    2014-01-01

    Full Text Available The present paper is aimed at multi-objective scheduling in an agent based holonic manufacturing system to satisfy the goal of several communities namely the product, the resource, and the organization simultaneously. In this attempt, first a multi criteria based priority rule is developed following Simple Additive Weight (SAW method under Multi Criteria Decision Making (MCDM environment to rank the products. Accordingly, the products are allowed to select a particular resource for execution by negotiation considering minimum time as criterion. The interests of different communities are accomplished by allocating the ordered rank of products to the ordered rank of resources. Conflict, if arises between products and resources, are resolved by introducing the concept of Early Finish Time (EFT as criterion for task allocation. A scheduling algorithm is proposed for execution of the rule. In view of machine failure, a cooperation strategy is evolved that also optimizes reallocation of the incomplete task. It is concluded that the proposed scheduling algorithm together with the disturbance handling algorithm are poised to satisfy the agent’s local objective as well as organization’s global objective concurrently and are commensurable with multi agent paradigm.

  5. ROCIT : a visual object recognition algorithm based on a rank-order coding scheme.

    Energy Technology Data Exchange (ETDEWEB)

    Gonzales, Antonio Ignacio; Reeves, Paul C.; Jones, John J.; Farkas, Benjamin D.

    2004-06-01

    This document describes ROCIT, a neural-inspired object recognition algorithm based on a rank-order coding scheme that uses a light-weight neuron model. ROCIT coarsely simulates a subset of the human ventral visual stream from the retina through the inferior temporal cortex. It was designed to provide an extensible baseline from which to improve the fidelity of the ventral stream model and explore the engineering potential of rank order coding with respect to object recognition. This report describes the baseline algorithm, the model's neural network architecture, the theoretical basis for the approach, and reviews the history of similar implementations. Illustrative results are used to clarify algorithm details. A formal benchmark to the 1998 FERET fafc test shows above average performance, which is encouraging. The report concludes with a brief review of potential algorithmic extensions for obtaining scale and rotational invariance.

  6. COMPLEX SURFACE RECONSTRUCTION BASED ON OBJECT-ORIENTED DEVELOPING TOOL VBA

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Taking AutoCAD2000 as platform, an algorithm for the reconstruction of surface from scattered data points based on VBA is presented. With this core technology customers can be free from traditional AutoCAD as an electronic board and begin to create actual presentation of real-world objects. VBA is not only a very powerful tool of development, but with very simple syntax. Associating with those solids, objects and commands of AutoCAD 2000, VBA notably simplifies previous complex algorithms, graphical presentations and processing, etc. Meanwhile, it can avoid appearance of complex data structure and data format in reverse design with other modeling software. Applying VBA to reverse engineering can greatly improve modeling efficiency and facilitate surface reconstruction.

  7. Evolutionary Algorithm based on simulated annealing for the multi-objective optimization of combinatorial problems

    Directory of Open Access Journals (Sweden)

    Elias David Nino Ruiz

    2013-05-01

    Full Text Available This paper states a novel hybrid-metaheuristic based on the Theory of Deterministic Swapping, Theory of Evolution and Simulated Annealing Metaheuristic for the multi-objective optimization of combinatorial problems. The proposed algorithm is named EMSA. It is an improvement of MODS algorithm. Unlike MODS, EMSA works using a search direction given through the assignation of weights to each function of the combinatorial problem to optimize. Also, in order to avoid local optimums, EMSA uses crossover strategy of Genetic Algorithm. Lastly, EMSA is tested using well know instances of the Bi-Objective Traveling Salesman Problem (TSP from TSPLIB. Its results were compared with MODS Metaheuristic (its precessor. The comparison was made using metrics from the specialized literature such as Spacing, Generational Distance, Inverse Generational Distance and Non-Dominated Generation Vectors. In every case, the EMSA results on the metrics were always better and in some of those cases, the superiority was 100%.

  8. Extracting Objects and Events from MPEG Videos for Highlight-based Indexing and Retrieval

    Directory of Open Access Journals (Sweden)

    Jinchang Ren

    2010-04-01

    Full Text Available Automatic recognition of highlights from videos is a fundamental and challenging problem for content-based indexing and retrieval applications. In this paper, we propose techniques to solve this problem using knowledge supported extraction of semantics, and compressed-domain processing is employed for efficiency. Firstly, knowledgebased rules are utilized for shot detection on extracted DCimages, and statistical skin detection is applied for human object detection. Secondly, through filtering outliers in motion vectors, improved detection of camera motions like zooming, panning and tilting are achieved. Video highlight high-level semantics are then automatically extracted via low-level analysis in the detection of human objects and camera motion events, and finally these highlights are taken for shot-level annotation, indexing and retrieval. Results using a large test video data set have demonstrated the accuracy and robustness of the proposed techniques.

  9. Development of an image based system to objectively score the severity of phoriasis

    DEFF Research Database (Denmark)

    Gomez, David Delgado

    2005-01-01

    The objective of this thesis is to provide a possible solution to one of the current problems in dermatology: the lack of suitable methods to objectively evaluate the severity of dermatological lesions. An image based system is developed with the goal of automatically obtaining summarization values...... that characterize the lesion and help to track the evolution of the disease. The thesis starts by analyzing an accurate type of equipment with which collect dermatological images. Later, a method to segment the different areas embedded in dermatological lesions is developed. Results of the segmentation task...... will be used to obtain values that characterize the lesion. The last part of the thesis considers the possibility of including more bands in the analysis in order to increase the accuracy of the proposed method....

  10. Observational Iinearization and tracking objective excitation control strategy based on phasor measurement unit

    Institute of Scientific and Technical Information of China (English)

    QIU Xiaoyan; LI Xingyuan; WANG Xiaoyan

    2007-01-01

    To improve the transient stability ofmultimachine power systems,observational linearization and tracking objective excitation control laws were derived from the phasor measurement unit (PMU),observational linearization,and tracking objective control theory based on synchronized coordinates and reference generator coordinates.The control strategies utilized real-time state variables obtained by PMU to linearize the state equations of the system,and then the linear optimal control strategy was used to design excitation controllers.The inaccuracy of the local linearization method and the complexity of the system models designed in the exact linearization method for nonlinear systems were avoided.Therefore,the control strategies were applied in real time.Simulation results show that the proposed method can improve the transient stability of power systems more efficiently than nonlinear optimal excitation control.

  11. Monitoring Post Disturbance Forest Regeneration with Hierarchical Object-Based Image Analysis

    Directory of Open Access Journals (Sweden)

    L. Monika Moskal

    2013-10-01

    Full Text Available The main goal of this exploratory project was to quantify seedling density in post fire regeneration sites, with the following objectives: to evaluate the application of second order image texture (SOIT in image segmentation, and to apply the object-based image analysis (OBIA approach to develop a hierarchical classification. With the utilization of image texture we successfully developed a methodology to classify hyperspatial (high-spatial imagery to fine detail level of tree crowns, shadows and understory, while still allowing discrimination between density classes and mature forest versus burn classes. At the most detailed hierarchical Level I classification accuracies reached 78.8%, a Level II stand density classification produced accuracies of 89.1% and the same accuracy was achieved by the coarse general classification at Level III. Our interpretation of these results suggests hyperspatial imagery can be applied to post-fire forest density and regeneration mapping.

  12. Multi-Objective Fuzzy Optimum Design Based on Reliability for Offshore Jacket Platforms

    Institute of Scientific and Technical Information of China (English)

    康海贵; 刘未; 翟钢军; 徐发淙; 封盛

    2001-01-01

    In consideration of the fuzzy constraint boundary and through analysis of structural reliability, a model of structural fuzzy optimum design is established based on reliability for offshore jacket platforms. According to the characteristics of offshore jacket platforms, the tolerance coefficient of the constraint boundary is determined with the fuzzy optimization method. The optimum level cut set λ *, which is the intersection of the fuzzy constraint set and fuzzy objective set, is determined with the bound search method, and then the fuzzy optimum solution to the fuzzy optimization problem is obtained. The central offshore platform SZ36-1 is designed with the fuzzy optimum model based on reliability; the results are compared with those from deterministic optimum design and fuzzy optimum design. The tendency of design variables in the above three methods and its reasons are analyzed. The results of an example show that the fuzzy optimum design based on reliability is stable and reliable.

  13. Validation of a computer based objective structured clinical examination in the assessment of undergraduate dermatology courses

    Directory of Open Access Journals (Sweden)

    Feroze Kaliyadan

    2014-01-01

    Full Text Available Many teaching centers have now adopted objective structured clinical examination (OSCE as an assessment method for undergraduate dermatology courses. A modification of the standard OSCE in dermatology is computer based or electronic OSCE (eOSCE. We attempted to validate the use of a computer-based OSCE in dermatology in a group of fifth year medical students. The scores of the students in the computer-based OSCE showed a strong positive correlation with the scores on the clinical presentation (Pearson′s co-efficient - 0.923, P value <0.000, significant at the 0.01 level and a good correlation with overall scores of the student (Pearson′s co-efficient - 0.728, P value <0.000, significant at the 0.01 level, indicating that this is a reliable method for assessment in dermatology. Generally, the students′ feedback regarding the methods was positive.

  14. Multi-equipment condition based maintenance optimization by multi- objective genetic algorithm

    Directory of Open Access Journals (Sweden)

    Š. Valčuha

    2011-04-01

    Full Text Available Purpose: This paper deals with the optimization of the condition based maintenance (CBM applied on manufacturing multi-equipment system under cost and benefit criteria.Design/methodology/approach: The system is modeled using Discrete Event Simulation (DES and optimized by means of the application of a Multi-Objective Evolutionary Algorithm (MOEA.Findings: Solution for the joint optimization of the condition based maintenance model applied on several equipment has been obtained.Research limitations/implications: The developed approach has been successfully applied to the optimization of condition based maintenance activities of a hubcap production system composed by three plastic injection machines and a painting station, for management decision support.Originality/value: This paper provides a solution for the joint optimization of CBM strategies applied on several equipments

  15. A new optimization algorithm based on a combination of particle swarm optimization, convergence and divergence operators for single-objective and multi-objective problems

    Science.gov (United States)

    Mahmoodabadi, M. J.; Bagheri, A.; Nariman-zadeh, N.; Jamali, A.

    2012-10-01

    Particle swarm optimization (PSO) is a randomized and population-based optimization method that was inspired by the flocking behaviour of birds and human social interactions. In this work, multi-objective PSO is modified in two stages. In the first stage, PSO is combined with convergence and divergence operators. Here, this method is named CDPSO. In the second stage, to produce a set of Pareto optimal solutions which has good convergence, diversity and distribution, two mechanisms are used. In the first mechanism, a new leader selection method is defined, which uses the periodic iteration and the concept of the particle's neighbour number. This method is named periodic multi-objective algorithm. In the second mechanism, an adaptive elimination method is employed to limit the number of non-dominated solutions in the archive, which has influences on computational time, convergence and diversity of solution. Single-objective results show that CDPSO performs very well on the complex test functions in terms of solution accuracy and convergence speed. Furthermore, some benchmark functions are used to evaluate the performance of periodic multi-objective CDPSO. This analysis demonstrates that the proposed algorithm operates better in three metrics through comparison with three well-known elitist multi-objective evolutionary algorithms. Finally, the algorithm is used for Pareto optimal design of a two-degree of freedom vehicle vibration model. The conflicting objective functions are sprung mass acceleration and relative displacement between sprung mass and tyre. The feasibility and efficiency of periodic multi-objective CDPSO are assessed in comparison with multi-objective modified NSGAII.

  16. Balancing Multiple Objectives Using a Classification-Based Forest Management System in Changbai Mountains, China

    Science.gov (United States)

    Zhao, Fuqiang; Yang, Jian; Liu, Zhihua; Dai, Limin; He, Hong S.

    2011-12-01

    Contemporary forest management often consists of multiple objectives, including restoration of human-impacted forested landscapes toward their range of natural variability (RNV) and sustainable levels of timber production. Balancing multiple management objectives is often challenging due to intrinsic conflicts between these objectives and a lack of reference conditions for evaluating the effectiveness of forest restoration efforts. We used a spatially explicit forest landscape model to assess how well a classification-based forest management (CFM) system could achieve multiple objectives in a Korean pine broadleaf mixed forest ecosystem at Changbai Mountain in Northeast China. The CFM system divided the forest landscape into three management areas (Commercial Forest, Special Ecological Welfare Forest, and General Ecological Welfare Forest), each with its own management objectives and prescriptions, but with an overall goal of increasing the ecological and economic sustainability of the entire landscape. The zoning approach adopted in the Chinese CFM system is very similar to the TRIAD approach that is being advocated for managing public forests in Canada. In this study, a natural disturbance scenario and seven harvest scenarios (one identical to the current harvest regime and six alternative scenarios) were simulated to examine how tree species composition, age structure, and timber production at the landscape level can be affected by different strategies under the CFM system. The results indicated that the current forest management regime would not only fail to reach the designated timber production level but also move the forest landscape far away from its RNV. In order to return the currently altered forest landscape to approach its RNV while providing a stable level of timber production over time, harvest intensities should be reduced to a level that is equivalent to the amount of timber removals that would occur under the natural disturbances; and the

  17. Automated multi-objective calibration of biological agent-based simulations.

    Science.gov (United States)

    Read, Mark N; Alden, Kieran; Rose, Louis M; Timmis, Jon

    2016-09-01

    Computational agent-based simulation (ABS) is increasingly used to complement laboratory techniques in advancing our understanding of biological systems. Calibration, the identification of parameter values that align simulation with biological behaviours, becomes challenging as increasingly complex biological domains are simulated. Complex domains cannot be characterized by single metrics alone, rendering simulation calibration a fundamentally multi-metric optimization problem that typical calibration techniques cannot handle. Yet calibration is an essential activity in simulation-based science; the baseline calibration forms a control for subsequent experimentation and hence is fundamental in the interpretation of results. Here, we develop and showcase a method, built around multi-objective optimization, for calibrating ABSs against complex target behaviours requiring several metrics (termed objectives) to characterize. Multi-objective calibration (MOC) delivers those sets of parameter values representing optimal trade-offs in simulation performance against each metric, in the form of a Pareto front. We use MOC to calibrate a well-understood immunological simulation against both established a priori and previously unestablished target behaviours. Furthermore, we show that simulation-borne conclusions are broadly, but not entirely, robust to adopting baseline parameter values from different extremes of the Pareto front, highlighting the importance of MOC's identification of numerous calibration solutions. We devise a method for detecting overfitting in a multi-objective context, not previously possible, used to save computational effort by terminating MOC when no improved solutions will be found. MOC can significantly impact biological simulation, adding rigour to and speeding up an otherwise time-consuming calibration process and highlighting inappropriate biological capture by simulations that cannot be well calibrated. As such, it produces more accurate

  18. Automated multi-objective calibration of biological agent-based simulations.

    Science.gov (United States)

    Read, Mark N; Alden, Kieran; Rose, Louis M; Timmis, Jon

    2016-09-01

    Computational agent-based simulation (ABS) is increasingly used to complement laboratory techniques in advancing our understanding of biological systems. Calibration, the identification of parameter values that align simulation with biological behaviours, becomes challenging as increasingly complex biological domains are simulated. Complex domains cannot be characterized by single metrics alone, rendering simulation calibration a fundamentally multi-metric optimization problem that typical calibration techniques cannot handle. Yet calibration is an essential activity in simulation-based science; the baseline calibration forms a control for subsequent experimentation and hence is fundamental in the interpretation of results. Here, we develop and showcase a method, built around multi-objective optimization, for calibrating ABSs against complex target behaviours requiring several metrics (termed objectives) to characterize. Multi-objective calibration (MOC) delivers those sets of parameter values representing optimal trade-offs in simulation performance against each metric, in the form of a Pareto front. We use MOC to calibrate a well-understood immunological simulation against both established a priori and previously unestablished target behaviours. Furthermore, we show that simulation-borne conclusions are broadly, but not entirely, robust to adopting baseline parameter values from different extremes of the Pareto front, highlighting the importance of MOC's identification of numerous calibration solutions. We devise a method for detecting overfitting in a multi-objective context, not previously possible, used to save computational effort by terminating MOC when no improved solutions will be found. MOC can significantly impact biological simulation, adding rigour to and speeding up an otherwise time-consuming calibration process and highlighting inappropriate biological capture by simulations that cannot be well calibrated. As such, it produces more accurate

  19. Target Object Identification and Location Based on Multi-sensor Fusion

    Directory of Open Access Journals (Sweden)

    Yong Jiang

    2013-03-01

    Full Text Available For an unknown environment, how to make a mobile robot identify a target object and locate it autonomously, this is a very challenging question. In this paper, a novel multi-sensor fusion method based on a camera and a laser range finder (LRF for mobile manipulations is proposed. Although a camera can acquire large quantities of information, it does not directly get the 3D data of the environment. Moreover, the camera image processing is complex and easily influenced from the change in ambient light. In view of the ability of the LRF to directly get the 3D coordinates of the environment and its stability against outside influence, and the superiority of the camera to acquire rich color information, the combination of the two sensors by making use of their advantages is employed to obtain more accurate measurement as well as to simplify information processing. To overlay the camera image with the measurement point cloud of the pitching LRF and to reconstruct the 3D image which includes pixel depth information, the homogeneous transformation model of the system is built. Then, based on the combination of the color features from the camera image and the shape features from the LRF measurement data, the autonomous identification and location of target object are achieved. In order to extract the shape features of the object, a two-step method is introduced, and a sliced point cloud algorithm is proposed for the preliminary classification of the measurement data of the LRF. The effectiveness of the proposed method is validated by the experimental testing and analysis carried out on the mobile manipulator platform. The experimental results show that by this method, the robot can not only identify target object autonomously, but also determine whether it can be operated, and acquire a proper grasping location.

  20. Multi-Objective Predictive Balancing Control of Battery Packs Based on Predictive Current

    Directory of Open Access Journals (Sweden)

    Wenbiao Li

    2016-04-01

    Full Text Available Various balancing topology and control methods have been proposed for the inconsistency problem of battery packs. However, these strategies only focus on a single objective, ignore the mutual interaction among various factors and are only based on the external performance of the battery pack inconsistency, such as voltage balancing and state of charge (SOC balancing. To solve these problems, multi-objective predictive balancing control (MOPBC based on predictive current is proposed in this paper, namely, in the driving process of an electric vehicle, using predictive control to predict the battery pack output current the next time. Based on this information, the impact of the battery pack temperature caused by the output current can be obtained. Then, the influence is added to the battery pack balancing control, which makes the present degradation, temperature, and SOC imbalance achieve balance automatically due to the change of the output current the next moment. According to MOPBC, the simulation model of the balancing circuit is built with four cells in Matlab/Simulink. The simulation results show that MOPBC is not only better than the other traditional balancing control strategies but also reduces the energy loss in the balancing process.

  1. Common toxicities and objective response rate in metastatic colorectal cancer patients treated with irinotecan based regimens

    Institute of Scientific and Technical Information of China (English)

    Liu Huang; Xin Liao; Qianqian Yu; Qiang Fu; Kai Qin; Huanlei Wu; Lihong Zhang; Xianglin Yuan

    2013-01-01

    Objective: The aim of our study was to investigate if common toxicities are correlated to objective response rate (ORR) in metastatic colorectal cancer (mCRC) patients treated by irinotecan based regimens. Methods: Univariate and multivariate logistic regression analyses were performed to evaluate correlations between common toxicities and binary ORR in 106 mCRC patients from a prospective cohort treated with irinotecan based regimens. Results: The most frequent severe toxicities (Grade 3/4) were as follows: neutropenia (27.4%), diarrhea (16.9%), leucopenia (12.6%), vomiting (3.2%) and thrombocytopenia (2.1%). Thrombocytosis was observed in 25 (26.3%) patients. ORR was 25.3%. Thrombocytopenia (P = 0.014), line of chemotherapy (P = 0.028) and thrombocytosis (P = 0.033) were correlated with ORR in univariate analysis. In multivariate analysis, thrombocytopenia (odds ratio [OR] = 8.600, 95% confidence interval [CI] = 1.705–43.385, P = 0.009) and first line chemotherapy (OR = 5.155, 95% CI = 1.153–23.256, P = 0.032) positively related to ORR. Conclusion: Throm-bocytopenia may be an indicator of ORR in mCRC patients treated by irinotecan plus 5-fluorouracil/capecitabine. Evidence is not strong enough to prove that irinotecan based regimens-induced diarrhea, leucopenia, neutropenia or vomiting is associ-ated with ORR.

  2. Web of Objects Based Ambient Assisted Living Framework for Emergency Psychiatric State Prediction

    Science.gov (United States)

    Alam, Md Golam Rabiul; Abedin, Sarder Fakhrul; Al Ameen, Moshaddique; Hong, Choong Seon

    2016-01-01

    Ambient assisted living can facilitate optimum health and wellness by aiding physical, mental and social well-being. In this paper, patients’ psychiatric symptoms are collected through lightweight biosensors and web-based psychiatric screening scales in a smart home environment and then analyzed through machine learning algorithms to provide ambient intelligence in a psychiatric emergency. The psychiatric states are modeled through a Hidden Markov Model (HMM), and the model parameters are estimated using a Viterbi path counting and scalable Stochastic Variational Inference (SVI)-based training algorithm. The most likely psychiatric state sequence of the corresponding observation sequence is determined, and an emergency psychiatric state is predicted through the proposed algorithm. Moreover, to enable personalized psychiatric emergency care, a service a web of objects-based framework is proposed for a smart-home environment. In this framework, the biosensor observations and the psychiatric rating scales are objectified and virtualized in the web space. Then, the web of objects of sensor observations and psychiatric rating scores are used to assess the dweller’s mental health status and to predict an emergency psychiatric state. The proposed psychiatric state prediction algorithm reported 83.03 percent prediction accuracy in an empirical performance study. PMID:27608023

  3. Web of Objects Based Ambient Assisted Living Framework for Emergency Psychiatric State Prediction.

    Science.gov (United States)

    Alam, Md Golam Rabiul; Abedin, Sarder Fakhrul; Al Ameen, Moshaddique; Hong, Choong Seon

    2016-01-01

    Ambient assisted living can facilitate optimum health and wellness by aiding physical, mental and social well-being. In this paper, patients' psychiatric symptoms are collected through lightweight biosensors and web-based psychiatric screening scales in a smart home environment and then analyzed through machine learning algorithms to provide ambient intelligence in a psychiatric emergency. The psychiatric states are modeled through a Hidden Markov Model (HMM), and the model parameters are estimated using a Viterbi path counting and scalable Stochastic Variational Inference (SVI)-based training algorithm. The most likely psychiatric state sequence of the corresponding observation sequence is determined, and an emergency psychiatric state is predicted through the proposed algorithm. Moreover, to enable personalized psychiatric emergency care, a service a web of objects-based framework is proposed for a smart-home environment. In this framework, the biosensor observations and the psychiatric rating scales are objectified and virtualized in the web space. Then, the web of objects of sensor observations and psychiatric rating scores are used to assess the dweller's mental health status and to predict an emergency psychiatric state. The proposed psychiatric state prediction algorithm reported 83.03 percent prediction accuracy in an empirical performance study. PMID:27608023

  4. Multi-objective Decision Based Available Transfer Capability in Deregulated Power System Using Heuristic Approaches

    Science.gov (United States)

    Pasam, Gopi Krishna; Manohar, T. Gowri

    2016-09-01

    Determination of available transfer capability (ATC) requires the use of experience, intuition and exact judgment in order to meet several significant aspects in the deregulated environment. Based on these points, this paper proposes two heuristic approaches to compute ATC. The first proposed heuristic algorithm integrates the five methods known as continuation repeated power flow, repeated optimal power flow, radial basis function neural network, back propagation neural network and adaptive neuro fuzzy inference system to obtain ATC. The second proposed heuristic model is used to obtain multiple ATC values. Out of these, a specific ATC value will be selected based on a number of social, economic, deregulated environmental constraints and related to specific applications like optimization, on-line monitoring, and ATC forecasting known as multi-objective decision based optimal ATC. The validity of results obtained through these proposed methods are scrupulously verified on various buses of the IEEE 24-bus reliable test system. The results presented and derived conclusions in this paper are very useful for planning, operation, maintaining of reliable power in any power system and its monitoring in an on-line environment of deregulated power system. In this way, the proposed heuristic methods would contribute the best possible approach to assess multiple objective ATC using integrated methods.

  5. A part-based probabilistic model for object detection with occlusion.

    Directory of Open Access Journals (Sweden)

    Chunhui Zhang

    Full Text Available The part-based method has been a fast rising framework for object detection. It is attracting more and more attention for its detection precision and partial robustness to the occlusion. However, little research has been focused on the problem of occlusion overlapping of the part regions, which can reduce the performance of the system. This paper proposes a part-based probabilistic model and the corresponding inference algorithm for the problem of the part occlusion. The model is based on the Bayesian theory integrally and aims to be robust to the large occlusion. In the stage of the model construction, all of the parts constitute the vertex set of a fully connected graph, and a binary variable is assigned to each part to indicate its occlusion status. In addition, we introduce a penalty term to regularize the argument space of the objective function. Thus, the part detection is formulated as an optimization problem, which is divided into two alternative procedures: the outer inference and the inner inference. A stochastic tentative method is employed in the outer inference to determine the occlusion status for each part. In the inner inference, the gradient descent algorithm is employed to find the optimal positions of the parts, in term of the current occlusion status. Experiments were carried out on the Caltech database. The results demonstrated that the proposed method achieves a strong robustness to the occlusion.

  6. Method of Designing Missile Controller Based on Multi-Objective Optimization

    Institute of Scientific and Technical Information of China (English)

    LIN Bo; MENG Xiu-yun; LIU Zao-zhen

    2006-01-01

    A method of designing robust controller based on genetic algorithm is presented in order to overcome the drawback of manual modification and trial in designing the control system of missile. Specification functions which reflect the dynamic performance in time domain and robustness in frequency domain are presented,then dynamic/static performance, control cost and robust stability are incorporated into a multi-objective optimization problem. Genetic algorithm is used to solve the problem and achieve the optimal controller directly.Simulation results show that the controller provides a good stability and offers a good dynamic performance in a large flight envelope. The results also validate the effectiveness of the method.

  7. VISUAL SIMULATION OF COLD ROLL-FORMING BASED ON OBJECT ORIENTED PROGRAMMING

    Institute of Scientific and Technical Information of China (English)

    Zhang Lele; Tan Nanlin; Zhang Huadi; Liu Cai

    2004-01-01

    To simulate the process of cold roll-forming process, a new method is adopted.The theoretical foundation of this method is an elastic-plastic large deformation spline finite strip method based on object-oriented programming.Combined with the computer graphics technology, the visual simulation of cold roll-forming is completed and the system is established.By analyzing common channel steel, the process is shown and explained including theory method, model and result display.So the simulation system is already a kind of mature and effective tool to analyze the process of cold roll forming.

  8. A high energy physics run control system based on an object oriented approach

    International Nuclear Information System (INIS)

    This paper reports describes the Run Control system developed for the Obelix experiment at the Low Energy Antiproton Ring of CERN. The adopted approach is based on a State Manager developed as a part of the MODEL project. The State Manager incorporates a model of the different activities and of the way they must be organized. An object-oriented decomposition of the on-line system is performed. A clean separation of the control. logic and operating tasks is achieved. Remote Procedure Call techniques are employed to cope with the problems of a distributed system architecture

  9. MO-Miner: A Data Mining Tool Based on Multi-Objective Genetic Algorithms

    OpenAIRE

    Oliveira, Gina M. B.; Martins, Luiz G. A.; C, Maria; Takiguti, S.

    2008-01-01

    The application of a multi-objective GA-based environment named MO-miner, inspired by the family of algorithms NSGA and designed to discover accurate and interesting dependence modeling rules, was investigated in this work. Our investigation was performed by applying MO-miner to two distinct public data sets named Nursery and Zoo, composed by 12960 and 101 registers, respectively. The accuracy and the interestingness of the rules mined by MO-miner were compared with those found by a single-ob...

  10. Multi-agent reinforcement learning based on policies of global objective

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    In general-sum games, taking all agent's collective rationality into account, we define agents' global objective,and propose a novel multi-agent reinforcement learning(RL) algorithm based on global policy. In each learning step, all agents commit to select the global policy to achieve the global goal. We prove this learning algorithm converges given certain restrictions on stage games of learned Q values, and show that it has quite lower computation time complexity than already developed multi-agent learning algorithms for general-sum games. An example is analyzed to show the algorithm' s merits.

  11. Solving multi-object radar cross section based on wide-angle parabolic equation method

    Institute of Scientific and Technical Information of China (English)

    Huang Zhixiang; Wu Qiong; Wu Xianliang

    2006-01-01

    Based on a Padé approximation, a wide-angle parabolic equation method is introduced for computing the multiobject radar cross section (RCS) for the first time. The method is a paraxial version of the scalar wave equation, which solves the field by marching them along the paraxial direction. Numerical results show that a single wide-angle parabolic equation run can compute multi-object RCS efficiently for angles up to 45°.The method provides a new and efficient numerical method for computation electromagnetics.

  12. An image-tracking algorithm based on object center distance-weighting and image feature recognition

    Institute of Scientific and Technical Information of China (English)

    JIANG Shuhong; WANG Qin; ZHANG Jianqiu; HU Bo

    2007-01-01

    Areal-time image-tracking algorithm is proposed.which gives small weights to pixels farther from the object center and uses the quantized image gray scales as a template.It identifies the target's location by the mean-shift iteration method and arrives at the target's scale by using image feature recognition.It improves the kernel-based algorithm in tracking scale-changing targets.A decimation mcthod is proposed to track large-sized targets and real-time experimental results verify the effectiveness of the proposed algorithm.

  13. An operational framework for object-based land use classification of heterogeneous rural landscapes

    DEFF Research Database (Denmark)

    Watmough, Gary Richard; Palm, Cheryl; Sullivan, Clare

    2016-01-01

    and transferable land use classification definitions and algorithms. We present an operational framework for classifying VHR satellite data in heterogeneous rural landscapes using an object-based and random forest classifier. The framework overcomes the challenges of classifying VHR data in anthropogenic......The characteristics of very high resolution (VHR) satellite data are encouraging development agencies to investigate its use in monitoring and evaluation programmes. VHR data pose challenges for land use classification of heterogeneous rural landscapes as it is not possible to develop generalised...

  14. Effective and efficient visual description based on local binary patterns and gradient distribution for object recognition

    OpenAIRE

    Zhu, Chao

    2012-01-01

    This thesis is dedicated to the problem of machine-based visual object recognition, which has become a very popular and important research topic in recent years because of its wide range of applications such as image/video indexing and retrieval, security access control, video monitoring, etc. Despite a lot of e orts and progress that have been made during the past years, it remains an open problem and is still considered as one of the most challenging problems in computer vision community, m...

  15. A KIND OF FUZZY MULTI-OBJECTIVE LINEAR PROGRAMMING PROBLEMS BASED ON INTERVAL VALUED FUZZY SETS

    Institute of Scientific and Technical Information of China (English)

    XU Jiuping

    2001-01-01

    This paper presents a general solution procedure and an interactive fuzzy satisfying method for a kind of fuzzy multi-objective linear programming problems based on interval valued fuzzy sets. Firstly, a fuzzy set of the fuzzy solutions, which can be focused on providing complete information for the final decision, can be obtained by the proposed tolerance analysis of a non-dominated set. Secondly, the satisfying solution for the decisionmaker can be derived from Pareto optimal solutions by updating the current reference membership levels on the basis of the current levels of the membership functions together with the trade-off rates between the membership functions.

  16. Browse evaluation of tall shrubs based on direct measurement of a management objective

    Science.gov (United States)

    Keigley, R.B.; Frisina, M.R.; Kitchen, Stanley G.; Pendleton, Rosemary L.; Monaco, Thomas A.; Vernon, Jason

    2008-01-01

    The monitoring of Geyer willow was based on the following management objective: Browsing will prevent fewer than 50 percent of Geyer willow shrubs from growing taller than 3 m . Three questions were addressed: (1) Is browsing a potential factor? (2) If so, can young plants grow taller than 3 meters? (3) If not, is browsing the dominant factor? All shrubs were intensely browsed. With a post-browsing growth rate of 5.0 cm per yr, no shrub could grow 3 m tall. Analyses of stem growth rate excluded dominant roles for climate and plant vigor. Browsing and stem age were the dominant factors that limited growth to 3 m tall.

  17. How a face may affect object-based attention: Evidence from adults and 8-month-old infants

    OpenAIRE

    Eloisa eValenza; Laura eFranchin; Hermann eBulf

    2014-01-01

    Object-based attention operates on perceptual objects, opening the possibility that the costs and benefits humans have to pay to move attention between objects might be affected by the nature of the stimuli. The current study reported two experiments with adults and 8-month-old infants investigating whether object-based-attention is affected by the stimulus social salience (faces vs. non-faces stimuli). Using the well-known cueing task developed by Egly et al. (1994) to study the object-based...

  18. Cooperative Moving Object Segmentation using Two Cameras based on Background Subtraction and Image Registration

    Directory of Open Access Journals (Sweden)

    Zhigao Cui

    2014-03-01

    Full Text Available Moving camera, such as PTZ (pan-tilt-zoom camera, has been widely applied in visual surveillance system. However, it’s difficult to extract moving objects because of the dynamic background caused by the camera motion. In this paper, a novel framework for moving object segmentation exploiting two cameras collaboration is presented by combining background subtraction and image registration method. The proposed method uses one static camera to capture large-view images at low resolution, and one moving camera (i.e. PTZ camera to capture local-view images at high resolution. Different with methods using a single moving camera, the moving objects can be effectively segmented in the static camera image by background subtraction method. Then image registration method can be applied to extract moving region in the moving camera image. To deal with the resolution and intensity discrepancy between two synchronized images, we design a practical three-step image registration method, which has higher registration accuracy than traditional feature based method. Experimental results on outdoor scene demonstrate the effectiveness and robustness of proposed approach.

  19. Associating optical measurements of MEO and GEO objects using Population-Based Meta-Heuristic methods

    Science.gov (United States)

    Zittersteijn, M.; Vananti, A.; Schildknecht, T.; Dolado Perez, J. C.; Martinot, V.

    2016-11-01

    Currently several thousands of objects are being tracked in the MEO and GEO regions through optical means. The problem faced in this framework is that of Multiple Target Tracking (MTT). The MTT problem quickly becomes an NP-hard combinatorial optimization problem. This means that the effort required to solve the MTT problem increases exponentially with the number of tracked objects. In an attempt to find an approximate solution of sufficient quality, several Population-Based Meta-Heuristic (PBMH) algorithms are implemented and tested on simulated optical measurements. These first results show that one of the tested algorithms, namely the Elitist Genetic Algorithm (EGA), consistently displays the desired behavior of finding good approximate solutions before reaching the optimum. The results further suggest that the algorithm possesses a polynomial time complexity, as the computation times are consistent with a polynomial model. With the advent of improved sensors and a heightened interest in the problem of space debris, it is expected that the number of tracked objects will grow by an order of magnitude in the near future. This research aims to provide a method that can treat the association and orbit determination problems simultaneously, and is able to efficiently process large data sets with minimal manual intervention.

  20. TOWARDS ENHANCING SOLUTION SPACE DIVERSITY IN MULTI-OBJECTIVE OPTIMIZATION: A HYPERVOLUME-BASED APPROACH

    Directory of Open Access Journals (Sweden)

    Kamyab Tahernezhadiani

    2012-02-01

    Full Text Available Diversity is an important notion in multi-objective evolutionary algorithms (MOEAs and a lot ofresearchers have investigated this issue by means of appropriate methods. However most of evolutionarymulti-objective algorithms have attempted to take control on diversity in the objective space only andmaximized diversity of solutions (population on Pareto- front. Nowadays due to importance of Multiobjectiveoptimization in industry and engineering, most of the designers want to find a diverse set ofPareto-optimal solutions which cover as much as space in its feasible regain of the solution space. Thispaper addresses this issue and attempt to introduce a method for preserving diversity of non-dominatedsolution (i.e. Pareto-set in the solution space. This paper introduces the novel diversity measure as a firsttime, and then this new diversity measure is integrated efficiently into the hypervolume based Multiobjectivemethod. At end of this paper we compare the proposed method with other state-of-the-artalgorithms on well-established test problems. Experimental results show that the proposed methodoutperforms its competitive MOEAs respect to the quality of solution space criteria and Pareto-setapproximation.

  1. Object-Based Classification of Abandoned Logging Roads under Heavy Canopy Using LiDAR

    Directory of Open Access Journals (Sweden)

    Jason Sherba

    2014-05-01

    Full Text Available LiDAR-derived slope models may be used to detect abandoned logging roads in steep forested terrain. An object-based classification approach of abandoned logging road detection was employed in this study. First, a slope model of the study site in Marin County, California was created from a LiDAR derived DEM. Multiresolution segmentation was applied to the slope model and road seed objects were iteratively grown into candidate objects. A road classification accuracy of 86% was achieved using this fully automated procedure and post processing increased this accuracy to 90%. In order to assess the sensitivity of the road classification to LiDAR ground point spacing, the LiDAR ground point cloud was repeatedly thinned by a fraction of 0.5 and the classification procedure was reapplied. The producer’s accuracy of the road classification declined from 79% with a ground point spacing of 0.91 to below 50% with a ground point spacing of 2, indicating the importance of high point density for accurate classification of abandoned logging roads.

  2. Real-time framework for tensor-based image enhancement for object classification

    Science.gov (United States)

    Cyganek, Bogusław; Smołka, Bogdan

    2016-04-01

    In many practical situations visual pattern recognition is vastly burdened by low quality of input images due to noise, geometrical distortions, as well as low quality of the acquisition hardware. However, although there are techniques of image quality improvements, such as nonlinear filtering, there are only few attempts reported in the literature that try to build these enhancement methods into a complete chain for multi-dimensional object recognition such as color video or hyperspectral images. In this work we propose a joint multilinear signal filtering and classification system built upon the multi-dimensional (tensor) approach. Tensor filtering is performed by the multi-dimensional input signal projection into the tensor subspace spanned by the best-rank tensor decomposition method. On the other hand, object classification is done by construction of the tensor sub-space constructed based on the Higher-Order Singular Value Decomposition method applied to the prototype patters. In the experiments we show that the proposed chain allows high object recognition accuracy in the real-time even from the poor quality prototypes. Even more importantly, the proposed framework allows unified classification of signals of any dimensions, such as color images or video sequences which are exemplars of 3D and 4D tensors, respectively. The paper discussed also some practical issues related to implementation of the key components of the proposed system.

  3. Culture belief based multi-objective hybrid differential evolutionary algorithm in short term hydrothermal scheduling

    International Nuclear Information System (INIS)

    Highlights: ► Culture belief is integrated into multi-objective differential evolution. ► Chaotic sequence is imported to improve evolutionary population diversity. ► The priority of convergence rate is proved in solving hydrothermal problem. ► The results show the quality and potential of proposed algorithm. - Abstract: A culture belief based multi-objective hybrid differential evolution (CB-MOHDE) is presented to solve short term hydrothermal optimal scheduling with economic emission (SHOSEE) problem. This problem is formulated for compromising thermal cost and emission issue while considering its complicated non-linear constraints with non-smooth and non-convex characteristics. The proposed algorithm integrates a modified multi-objective differential evolutionary algorithm into the computation model of culture algorithm (CA) as well as some communication protocols between population space and belief space, three knowledge structures in belief space are redefined according to these problem-solving characteristics, and in the differential evolution a chaotic factor is embedded into mutation operator for avoiding the premature convergence by enlarging the search scale when the search trajectory reaches local optima. Furthermore, a new heuristic constraint-handling technique is utilized to handle those complex equality and inequality constraints of SHOSEE problem. After the application on hydrothermal scheduling system, the efficiency and stability of the proposed CB-MOHDE is verified by its more desirable results in comparison to other method established recently, and the simulation results also reveal that CB-MOHDE can be a promising alternative for solving SHOSEE.

  4. Design for sustainability of industrial symbiosis based on emergy and multi-objective particle swarm optimization.

    Science.gov (United States)

    Ren, Jingzheng; Liang, Hanwei; Dong, Liang; Sun, Lu; Gao, Zhiqiu

    2016-08-15

    Industrial symbiosis provides novel and practical pathway to the design for the sustainability. Decision support tool for its verification is necessary for practitioners and policy makers, while to date, quantitative research is limited. The objective of this work is to present an innovative approach for supporting decision-making in the design for the sustainability with the implementation of industrial symbiosis in chemical complex. Through incorporating the emergy theory, the model is formulated as a multi-objective approach that can optimize both the economic benefit and sustainable performance of the integrated industrial system. A set of emergy based evaluation index are designed. Multi-objective Particle Swarm Algorithm is proposed to solve the model, and the decision-makers are allowed to choose the suitable solutions form the Pareto solutions. An illustrative case has been studied by the proposed method, a few of compromises between high profitability and high sustainability can be obtained for the decision-makers/stakeholders to make decision. PMID:27110990

  5. An interactive system for creating object models from range data based on simulated annealing

    International Nuclear Information System (INIS)

    In hazardous applications such as remediation of buried waste and dismantlement of radioactive facilities, robots are an attractive solution. Sensing to recognize and locate objects is a critical need for robotic operations in unstructured environments. An accurate 3-D model of objects in the scene is necessary for efficient high level control of robots. Drawing upon concepts from supervisory control, the authors have developed an interactive system for creating object models from range data, based on simulated annealing. Site modeling is a task that is typically performed using purely manual or autonomous techniques, each of which has inherent strengths and weaknesses. However, an interactive modeling system combines the advantages of both manual and autonomous methods, to create a system that has high operator productivity as well as high flexibility and robustness. The system is unique in that it can work with very sparse range data, tolerate occlusions, and tolerate cluttered scenes. The authors have performed an informal evaluation with four operators on 16 different scenes, and have shown that the interactive system is superior to either manual or automatic methods in terms of task time and accuracy

  6. A novel objective sour taste evaluation method based on near-infrared spectroscopy.

    Science.gov (United States)

    Hoshi, Ayaka; Aoki, Soichiro; Kouno, Emi; Ogasawara, Masashi; Onaka, Takashi; Miura, Yutaka; Mamiya, Kanji

    2014-05-01

    One of the most important themes in the development of foods and drinks is the accurate evaluation of taste properties. In general, a sensory evaluation system is frequently used for evaluating food and drink. This method, which is dependent on human senses, is highly sensitive but is influenced by the eating experience and food palatability of individuals, leading to subjective results. Therefore, a more effective method for objectively estimating taste properties is required. Here we show that salivary hemodynamic signals, as measured by near-infrared spectroscopy, are a useful objective indicator for evaluating sour taste stimulus. In addition, the hemodynamic responses of the parotid gland are closely correlated to the salivary secretion volume of the parotid gland in response to basic taste stimuli and respond to stimuli independently of the hedonic aspect. Moreover, we examined the hemodynamic responses to complex taste stimuli in food-based solutions and demonstrated for the first time that the complicated phenomenon of the "masking effect," which decreases taste intensity despite the additional taste components, can be successfully detected by near-infrared spectroscopy. In summary, this study is the first to demonstrate near-infrared spectroscopy as a novel tool for objectively evaluating complex sour taste properties in foods and drinks.

  7. Intuitive Terrain Reconstruction Using Height Observation-Based Ground Segmentation and 3D Object Boundary Estimation

    Directory of Open Access Journals (Sweden)

    Sungdae Sim

    2012-12-01

    Full Text Available Mobile robot operators must make rapid decisions based on information about the robot’s surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot’s array of sensors, but some upper parts of objects are beyond the sensors’ measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances.

  8. Intuitive terrain reconstruction using height observation-based ground segmentation and 3D object boundary estimation.

    Science.gov (United States)

    Song, Wei; Cho, Kyungeun; Um, Kyhyun; Won, Chee Sun; Sim, Sungdae

    2012-12-12

    Mobile robot operators must make rapid decisions based on information about the robot's surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot's array of sensors, but some upper parts of objects are beyond the sensors' measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances.

  9. Research on Object Model-Based Architecture for Service Robot System

    Institute of Scientific and Technical Information of China (English)

    邵鹏鸣; 李成刚; 吴翰声

    2002-01-01

    An object model-based software architecture for service robot system is presented, which addresses both software engineering issues such as reuse, extensibility, and management of complexity as well as system engineering issues like scalability, reactivity, and robustness. A novel approach to the service robot system architecture is discussed. Cognitive psychology is considered in designing the software system, i.e., a humans way of vision and planning is applied. The planner can incorporate the users request into its task selection mechanism and generate plans biased toward picking the most reliable task execution in a given situation, and the planner can alter task selection based on changes that occur in dynamic and uncertain environments.

  10. ARTIFICIAL NEURAL NETWORK BASED DISCRIMINATION OF MINELIKE OBJECTS IN INFRARED IMAGES

    Directory of Open Access Journals (Sweden)

    G.Suganthi

    2014-09-01

    Full Text Available An artificial neural network (ANN model with a simple architecture containing a single hidden layer is presented to discriminate the landmine objects from the acquired infrared images. The proposed method consists of preprocessing, segmentation, feature extraction and ANN based classification. Texture features based on gray level co-occurrence matrix (GLCM are considered as inputs to the neural network classifier. The proposed method is tested on the infrared images acquired from two different soil types namely black cotton soil and Maharashtra sand. The ability of the back propagation neural network in discriminating the landmines from the clutters in the infrared images acquired from inhomogeneous soil is discussed. The results of the field experiments carried out at the outdoor land mine detection test facility, DRDO, Pune are presented. The results are encouraging.

  11. Objective evaluation of pronunciation of standard Chinese final based on formant pattern

    Institute of Scientific and Technical Information of China (English)

    DONG Bin; ZHAO Qingwei; YAN Yonghong

    2007-01-01

    A method used for objective evaluation of pronunciation of finals in standard Chinese is presented. The formant pattern of final is selected as the main feature and an improved evaluation algorithm based on Support Vector Machine is proposed. In this algorithm, two-level classification strategy is employed. A full-classification model and a sub-classification model are trained for each final. The pronunciation quality is evaluated based on the classification results of this two-level strategy with scoring model of each final. The new evaluation method is compared with traditional methods such as Hidden Markov Model (HMM) posterior probability scoring method and feature of Mel-Frequency Cepstrum Coefficients (MFCC), and the results show that the performance is effectively improved by the proposed method. The correlation of scores between human testers and machine has achieved 82%.

  12. Real-time object tracking based on scale-invariant features employing bio-inspired hardware.

    Science.gov (United States)

    Yasukawa, Shinsuke; Okuno, Hirotsugu; Ishii, Kazuo; Yagi, Tetsuya

    2016-09-01

    We developed a vision sensor system that performs a scale-invariant feature transform (SIFT) in real time. To apply the SIFT algorithm efficiently, we focus on a two-fold process performed by the visual system: whole-image parallel filtering and frequency-band parallel processing. The vision sensor system comprises an active pixel sensor, a metal-oxide semiconductor (MOS)-based resistive network, a field-programmable gate array (FPGA), and a digital computer. We employed the MOS-based resistive network for instantaneous spatial filtering and a configurable filter size. The FPGA is used to pipeline process the frequency-band signals. The proposed system was evaluated by tracking the feature points detected on an object in a video. PMID:27268260

  13. Approach to proliferation risk assessment based on multiple objective analysis framework

    Energy Technology Data Exchange (ETDEWEB)

    Andrianov, A.; Kuptsov, I. [Obninsk Institute for Nuclear Power Engineering of NNRU MEPhI (Russian Federation); Studgorodok 1, Obninsk, Kaluga region, 249030 (Russian Federation)

    2013-07-01

    The approach to the assessment of proliferation risk using the methods of multi-criteria decision making and multi-objective optimization is presented. The approach allows the taking into account of the specifics features of the national nuclear infrastructure, and possible proliferation strategies (motivations, intentions, and capabilities). 3 examples of applying the approach are shown. First, the approach has been used to evaluate the attractiveness of HEU (high enriched uranium)production scenarios at a clandestine enrichment facility using centrifuge enrichment technology. Secondly, the approach has been applied to assess the attractiveness of scenarios for undeclared production of plutonium or HEU by theft of materials circulating in nuclear fuel cycle facilities and thermal reactors. Thirdly, the approach has been used to perform a comparative analysis of the structures of developing nuclear power systems based on different types of nuclear fuel cycles, the analysis being based on indicators of proliferation risk.

  14. Combining TerraSAR-X and SPOT-5 data for object-based landslide detection

    Science.gov (United States)

    Friedl, B.; Hölbling, D.; Füreder, P.

    2012-04-01

    Landslide detection and classification is an essential requirement in pre- and post-disaster hazard analysis. In earlier studies landslide detection often was achieved through time-consuming and cost-intensive field surveys and visual orthophoto interpretation. Recent studies show that Earth Observation (EO) data offer new opportunities for fast, reliable and accurate landslide detection and classification, which may conduce to an effective landslide monitoring and landslide hazard management. To ensure the fast recognition and classification of landslides at a regional scale, a (semi-)automated object-based landslide detection approach is established for a study site situated in the Huaguoshan catchment, Southern Taiwan. The study site exhibits a high vulnerability to landslides and debris flows, which are predominantly typhoon-induced. Through the integration of optical satellite data (SPOT-5 with 2.5 m GSD), SAR (Synthetic Aperture Radar) data (TerraSAR-X Spotlight with 2.95 m GSD) and digital elevation information (DEM with 5 m GSD) including its derived products (e.g. slope, curvature, flow accumulation) landslides may be examined in a more efficient way as if relying on single data sources only. The combination of optical and SAR data in an object-based image analysis (OBIA) domain for landslide detection and classification has not been investigated so far, even if SAR imagery show valuable properties for landslide detection, which differ from optical data (e.g. high sensitivity to surface roughness and soil moisture). The main purpose of this study is to recognize and analyze existing landslides by applying object-based image analysis making use of eCognition software. OBIA provides a framework for examining features defined by spectral, spatial, textural, contextual as well as hierarchical properties. Objects are derived through image segmentation and serve as input for the classification process, which relies on transparent rulesets, representing knowledge

  15. Increasing the range accuracy of three-dimensional ghost imaging ladar using optimum slicing number method

    Science.gov (United States)

    Yang, Xu; Zhang, Yong; Xu, Lu; Yang, Cheng-Hua; Wang, Qiang; Liu, Yue-Hao; Zhao, Yuan

    2015-12-01

    The range accuracy of three-dimensional (3D) ghost imaging is derived. Based on the derived range accuracy equation, the relationship between the slicing number and the range accuracy is analyzed and an optimum slicing number (OSN) is determined. According to the OSN, an improved 3D ghost imaging algorithm is proposed to increase the range accuracy. Experimental results indicate that the slicing number can affect the range accuracy significantly and the highest range accuracy can be achieved if the 3D ghost imaging system works with OSN. Project supported by the Young Scientist Fund of the National Natural Science Foundation of China (Grant No. 61108072).

  16. Object-based image analysis and data mining for building ontology of informal urban settlements

    Science.gov (United States)

    Khelifa, Dejrriri; Mimoun, Malki

    2012-11-01

    During recent decades, unplanned settlements have been appeared around the big cities in most developing countries and as consequence, numerous problems have emerged. Thus the identification of different kinds of settlements is a major concern and challenge for authorities of many countries. Very High Resolution (VHR) Remotely Sensed imagery has proved to be a very promising way to detect different kinds of settlements, especially through the using of new objectbased image analysis (OBIA). The most important key is in understanding what characteristics make unplanned settlements differ from planned ones, where most experts characterize unplanned urban areas by small building sizes at high densities, no orderly road arrangement and Lack of green spaces. Knowledge about different kinds of settlements can be captured as a domain ontology that has the potential to organize knowledge in a formal, understandable and sharable way. In this work we focus on extracting knowledge from VHR images and expert's knowledge. We used an object based strategy by segmenting a VHR image taken over urban area into regions of homogenous pixels at adequate scale level and then computing spectral, spatial and textural attributes for each region to create objects. A genetic-based data mining was applied to generate high predictive and comprehensible classification rules based on selected samples from the OBIA result. Optimized intervals of relevant attributes are found, linked with land use types for forming classification rules. The unplanned areas were separated from the planned ones, through analyzing of the line segments detected from the input image. Finally a simple ontology was built based on the previous processing steps. The approach has been tested to VHR images of one of the biggest Algerian cities, that has grown considerably in recent decades.

  17. AN INTEGRATIVE OBJECT-BASED IMAGE ANALYSIS WORKFLOW FOR UAV IMAGES

    Directory of Open Access Journals (Sweden)

    H. Yu

    2016-06-01

    Full Text Available In this work, we propose an integrative framework to process UAV images. The overall process can be viewed as a pipeline consisting of the geometric and radiometric corrections, subsequent panoramic mosaicking and hierarchical image segmentation for later Object Based Image Analysis (OBIA. More precisely, we first introduce an efficient image stitching algorithm after the geometric calibration and radiometric correction, which employs a fast feature extraction and matching by combining the local difference binary descriptor and the local sensitive hashing. We then use a Binary Partition Tree (BPT representation for the large mosaicked panoramic image, which starts by the definition of an initial partition obtained by an over-segmentation algorithm, i.e., the simple linear iterative clustering (SLIC. Finally, we build an object-based hierarchical structure by fully considering the spectral and spatial information of the super-pixels and their topological relationships. Moreover, an optimal segmentation is obtained by filtering the complex hierarchies into simpler ones according to some criterions, such as the uniform homogeneity and semantic consistency. Experimental results on processing the post-seismic UAV images of the 2013 Ya’an earthquake demonstrate the effectiveness and efficiency of our proposed method.

  18. Application of In-Segment Multiple Sampling in Object-Based Classification

    Directory of Open Access Journals (Sweden)

    Nataša Đurić

    2014-12-01

    Full Text Available When object-based analysis is applied to very high-resolution imagery, pixels within the segments reveal large spectral inhomogeneity; their distribution can be considered complex rather than normal. When normality is violated, the classification methods that rely on the assumption of normally distributed data are not as successful or accurate. It is hard to detect normality violations in small samples. The segmentation process produces segments that vary highly in size; samples can be very big or very small. This paper investigates whether the complexity within the segment can be addressed using multiple random sampling of segment pixels and multiple calculations of similarity measures. In order to analyze the effect sampling has on classification results, statistics and probability value equations of non-parametric two-sample Kolmogorov-Smirnov test and parametric Student’s t-test are selected as similarity measures in the classification process. The performance of both classifiers was assessed on a WorldView-2 image for four land cover classes (roads, buildings, grass and trees and compared to two commonly used object-based classifiers—k-Nearest Neighbor (k-NN and Support Vector Machine (SVM. Both proposed classifiers showed a slight improvement in the overall classification accuracies and produced more accurate classification maps when compared to the ground truth image.

  19. Three Dimentional Reconstruction of Large Cultural Heritage Objects Based on Uav Video and Tls Data

    Science.gov (United States)

    Xu, Z.; Wu, T. H.; Shen, Y.; Wu, L.

    2016-06-01

    This paper investigates the synergetic use of unmanned aerial vehicle (UAV) and terrestrial laser scanner (TLS) in 3D reconstruction of cultural heritage objects. Rather than capturing still images, the UAV that equips a consumer digital camera is used to collect dynamic videos to overcome its limited endurance capacity. Then, a set of 3D point-cloud is generated from video image sequences using the automated structure-from-motion (SfM) and patch-based multi-view stereo (PMVS) methods. The TLS is used to collect the information that beyond the reachability of UAV imaging e.g., partial building facades. A coarse to fine method is introduced to integrate the two sets of point clouds UAV image-reconstruction and TLS scanning for completed 3D reconstruction. For increased reliability, a variant of ICP algorithm is introduced using local terrain invariant regions in the combined designation. The experimental study is conducted in the Tulou culture heritage building in Fujian province, China, which is focused on one of the TuLou clusters built several hundred years ago. Results show a digital 3D model of the Tulou cluster with complete coverage and textural information. This paper demonstrates the usability of the proposed method for efficient 3D reconstruction of heritage object based on UAV video and TLS data.

  20. Object-based approach to national land cover mapping using HJ satellite imagery

    Science.gov (United States)

    Zhang, Lei; Li, Xiaosong; Yuan, Quanzhi; Liu, Yu

    2014-01-01

    To meet the carbon storage estimate in ecosystems for a national carbon strategy, we introduce a consistent database of China land cover. The Chinese Huan Jing (HJ) satellite is proven efficient in the cloud-free acquisition of seasonal image series in a monsoon region and in vegetation identification for mesoscale land cover mapping. Thirty-eight classes of level II land cover are generated based on the Land Cover Classification System of the United Nations Food and Agriculture Organization that follows a standard and quantitative definition. Twenty-four layers of derivative spectral, environmental, and spatial features compose the classification database. Object-based approach characterizing additional nonspectral features is conducted through mapping, and multiscale segmentations are applied on object boundary match to target real-world conditions. This method sufficiently employs spatial information, in addition to spectral characteristics, to improve classification accuracy. The algorithm of hierarchical classification is employed to follow step-by-step procedures that effectively control classification quality. This algorithm divides the dual structures of universal and local trees. Consistent universal trees suitable to most regions are performed first, followed by local trees that depend on specific features of nine climate stratifications. The independent validation indicates the overall accuracy reaches 86%.