Chidananda, H.; Reddy, T. Hanumantha
This paper presents a natural representation of numerical digit(s) using hand activity analysis based on number of fingers out stretched for each numerical digit in sequence extracted from a video. The analysis is based on determining a set of six features from a hand image. The most important features used from each frame in a video are the first fingertip from top, palm-line, palm-center, valley points between the fingers exists above the palm-line. Using this work user can convey any number of numerical digits using right or left or both the hands naturally in a video. Each numerical digit ranges from 0 to9. Hands (right/left/both) used to convey digits can be recognized accurately using the valley points and with this recognition whether the user is a right / left handed person in practice can be analyzed. In this work, first the hand(s) and face parts are detected by using YCbCr color space and face part is removed by using ellipse based method. Then, the hand(s) are analyzed to recognize the activity that represents a series of numerical digits in a video. This work uses pixel continuity algorithm using 2D coordinate geometry system and does not use regular use of calculus, contours, convex hull and datasets.
Ramirez-Cortes, Juan Manuel; Gomez-Gil, Pilar; Sanchez-Perez, Gabriel; Prieto-Castro, Cesar
We propose the use of the morphological pattern spectrum, or pecstrum, as the base of a biometric shape-based hand recognition system. The system receives an image of the right hand of a subject in an unconstrained pose, which is captured with a commercial flatbed scanner. According to pecstrum property of invariance to translation and rotation, the system does not require the use of pegs for a fixed hand position, which simplifies the image acquisition process. This novel feature-extraction method is tested using a Euclidean distance classifier for identification and verification cases, obtaining 97% correct identification, and an equal error rate (EER) of 0.0285 (2.85%) for the verification mode. The obtained results indicate that the pattern spectrum represents a good feature-extraction alternative for low- and medium-level hand-shape-based biometric applications.
Longcamp, Marieke; Boucard, Céline; Gilhodes, Jean-Claude; Anton, Jean-Luc; Roth, Muriel; Nazarian, Bruno; Velay, Jean-Luc
Fast and accurate visual recognition of single characters is crucial for efficient reading. We explored the possible contribution of writing memory to character recognition processes. We evaluated the ability of adults to discriminate new characters from their mirror images after being taught how to produce the characters either by traditional pen-and-paper writing or with a computer keyboard. After training, we found stronger and longer lasting (several weeks) facilitation in recognizing the orientation of characters that had been written by hand compared to those typed. Functional magnetic resonance imaging recordings indicated that the response mode during learning is associated with distinct pathways during recognition of graphic shapes. Greater activity related to handwriting learning and normal letter identification was observed in several brain regions known to be involved in the execution, imagery, and observation of actions, in particular, the left Broca's area and bilateral inferior parietal lobules. Taken together, these results provide strong arguments in favor of the view that the specific movements memorized when learning how to write participate in the visual recognition of graphic shapes and letters.
Full Text Available This paper presents a new profile shape matching stereovision algorithm that is designed to extract 3D information in real time. This algorithm obtains 3D information by matching profile intensity shapes of each corresponding row of the stereo image pair. It detects the corresponding matching patterns of the intensity profile rather than the intensity values of individual pixels or pixels in a small neighbourhood. This approach reduces the effect of the intensity and colour variations caused by lighting differences. As with all real-time vision algorithms, there is always a trade-off between accuracy and processing speed. This algorithm achieves a balance between the two to produce accurate results for real-time applications. To demonstrate its performance, the proposed algorithm is tested for human pose and hand gesture recognition to control a smart phone and an entertainment system.
Pesyna, Colin; Pundi, Krishna; Flanders, Martha
The neural control of hand movement involves coordination of the sensory, motor, and memory systems. Recent studies have documented the motor coordinates for hand shape, but less is known about the corresponding patterns of somatosensory activity. To initiate this line of investigation, the present study characterized the sense of hand shape by evaluating the influence of differences in the amount of grasping or twisting force, and differences in forearm orientation. Human subjects were asked to use the left hand to report the perceived shape of the right hand. In the first experiment, six commonly grasped items were arranged on the table in front of the subject: bottle, doorknob, egg, notebook, carton, and pan. With eyes closed, subjects used the right hand to lightly touch, forcefully support, or imagine holding each object, while 15 joint angles were measured in each hand with a pair of wired gloves. The forces introduced by supporting or twisting did not influence the perceptual report of hand shape, but for most objects, the report was distorted in a consistent manner by differences in forearm orientation. Subjects appeared to adjust the intrinsic joint angles of the left hand, as well as the left wrist posture, so as to maintain the imagined object in its proper spatial orientation. In a second experiment, this result was largely replicated with unfamiliar objects. Thus, somatosensory and motor information appear to be coordinated in an object-based, spatial-coordinate system, sensitive to orientation relative to gravitational forces, but invariant to grasp forcefulness.
K. Dijkstra (Katinka); M.P. Kaschak; R.A. Zwaan (Rolf)
textabstractThe present study examined the ways that body posture facilitated retrieval of autobiographical memories in more detail by focusing on two aspects of congruence in position of a specific body part: hand shape and hand orientation. Hand shape is important in the tactile perception and
Ramachandra, Poornima; Shrikhande, Neelima
The problem of recognizing gestures from images using computers can be approached by closely understanding how the human brain tackles it. A full fledged gesture recognition system will substitute mouse and keyboards completely. Humans can recognize most gestures by looking at the characteristic external shape or the silhouette of the fingers. Many previous techniques to recognize gestures dealt with motion and geometric features of hands. In this thesis gestures are recognized by the Codon-list pattern extracted from the object contour. All edges of an image are described in terms of sequence of Codons. The Codons are defined in terms of the relationship between maxima, minima and zeros of curvature encountered as one traverses the boundary of the object. We have concentrated on a catalog of 24 gesture images from the American Sign Language alphabet (Letter J and Z are ignored as they are represented using motion) . The query image given as an input to the system is analyzed and tested against the Codon-lists, which are shape descriptors for external parts of a hand gesture. We have used the Weighted Frequency Indexing Transform (WFIT) approach which is used in DNA sequence matching for matching the Codon-lists. The matching algorithm consists of two steps: 1) the query sequences are converted to short sequences and are assigned weights and, 2) all the sequences of query gestures are pruned into match and mismatch subsequences by the frequency indexing tree based on the weights of the subsequences. The Codon sequences with the most weight are used to determine the most precise match. Once a match is found, the identified gesture and corresponding interpretation are shown as output.
Du, Youchen; Liu, Shenglan; Feng, Lin; Chen, Menghui; Wu, Jie
The recent introduction of depth cameras like Leap Motion Controller allows researchers to exploit the depth information to recognize hand gesture more robustly. This paper proposes a novel hand gesture recognition system with Leap Motion Controller. A series of features are extracted from Leap Motion tracking data, we feed these features along with HOG feature extracted from sensor images into a multi-class SVM classifier to recognize performed gesture, dimension reduction and feature weight...
Park, GiTae; Kim, Soowon
A hand biometric authentication method based on measurements of the user's hand geometry and vascular pattern is proposed. To acquire the hand geometry, the thickness of the side view of the hand, the K-curvature with a hand-shaped chain code, the lengths and angles of the finger valleys, and the lengths and profiles of the fingers were used, and for the vascular pattern, the direction-based vascular-pattern extraction method was used, and thus, a new multimodal biometric approach is proposed. The proposed multimodal biometric system uses only one image to extract the feature points. This system can be configured for low-cost devices. Our multimodal biometric-approach hand-geometry (the side view of the hand and the back of hand) and vascular-pattern recognition method performs at the score level. The results of our study showed that the equal error rate of the proposed system was 0.06%. PMID:23449119
Park, GiTae; Kim, Soowon
A hand biometric authentication method based on measurements of the user's hand geometry and vascular pattern is proposed. To acquire the hand geometry, the thickness of the side view of the hand, the K-curvature with a hand-shaped chain code, the lengths and angles of the finger valleys, and the lengths and profiles of the fingers were used, and for the vascular pattern, the direction-based vascular-pattern extraction method was used, and thus, a new multimodal biometric approach is proposed. The proposed multimodal biometric system uses only one image to extract the feature points. This system can be configured for low-cost devices. Our multimodal biometric-approach hand-geometry (the side view of the hand and the back of hand) and vascular-pattern recognition method performs at the score level. The results of our study showed that the equal error rate of the proposed system was 0.06%.
AlSharif, Mohammed Hussain
Gesturing is a natural way of communication between people and is used in our everyday conversations. Hand gesture recognition systems are used in many applications in a wide variety of fields, such as mobile phone applications, smart TVs, video gaming, etc. With the advances in human-computer interaction technology, gesture recognition is becoming an active research area. There are two types of devices to detect gestures; contact based devices and contactless devices. Using ultrasonic waves for determining gestures is one of the ways that is employed in contactless devices. Hand gesture recognition utilizing ultrasonic waves will be the focus of this thesis work. This thesis presents a new method for detecting and classifying a predefined set of hand gestures using a single ultrasonic transmitter and a single ultrasonic receiver. This method uses a linear frequency modulated ultrasonic signal. The ultrasonic signal is designed to meet the project requirements such as the update rate, the range of detection, etc. Also, it needs to overcome hardware limitations such as the limited output power, transmitter, and receiver bandwidth, etc. The method can be adapted to other hardware setups. Gestures are identified based on two main features; range estimation of the moving hand and received signal strength (RSS). These two factors are estimated using two simple methods; channel impulse response (CIR) and cross correlation (CC) of the reflected ultrasonic signal from the gesturing hand. A customized simple hardware setup was used to classify a set of hand gestures with high accuracy. The detection and classification were done using methods of low computational cost. This makes the proposed method to have a great potential for the implementation in many devices including laptops and mobile phones. The predefined set of gestures can be used for many control applications.
Paleari, Marco; Luciani, Riccardo; Ariano, Paolo
This work reports on preliminary results about on hand movement recognition with Near InfraRed Spectroscopy (NIRS) and surface ElectroMyoGraphy (sEMG). Either basing on physical contact (touchscreens, data-gloves, etc.), vision techniques (Microsoft Kinect, Sony PlayStation Move, etc.), or other modalities, hand movement recognition is a pervasive function in today environment and it is at the base of many gaming, social, and medical applications. Albeit, in recent years, the use of muscle information extracted by sEMG has spread out from the medical applications to contaminate the consumer world, this technique still falls short when dealing with movements of the hand. We tested NIRS as a technique to get another point of view on the muscle phenomena and proved that, within a specific movements selection, NIRS can be used to recognize movements and return information regarding muscles at different depths. Furthermore, we propose here three different multimodal movement recognition approaches and compare their performances.
Olsen, Søren I.
This paper presents an approach of visual shape recognition based on exemplars of attributed keypoints. Training is performed by storing exemplars of keypoints detected in labeled training images. Recognition is made by keypoint matching and voting according to the labels for the matched keypoint....... The matching is insensitive to rotations, limited scalings and small deformations. The recognition is robust to noise, background clutter and partial occlusion. Recognition is possible from few training images and improve with the number of training images.......This paper presents an approach of visual shape recognition based on exemplars of attributed keypoints. Training is performed by storing exemplars of keypoints detected in labeled training images. Recognition is made by keypoint matching and voting according to the labels for the matched keypoints...
Wang, W; Mottershead, J E; Mares, C
The most widely used method for comparing mode shapes from finite elements and experimental measurements is the Modal Assurance Criterion (MAC), which returns a single numerical value and carries no explicit information on shape features. New techniques, based on image processing (IP) and pattern recognition (PR) are described in this paper. The Zernike moment descriptor (ZMD), Fourier descriptor (FD), and wavelet descriptor (WD), presented in this article, are the most popular shape descriptors having properties that include efficiency of expression, robustness to noise, invariance to geometric transformation and rotation, separation of local and global shape features and computational efficiency. The comparison of mode shapes is readily achieved by assembling the shape features of each mode shape into multi-dimensional shape feature vectors (SFVs) and determining the distances separating them.
AlSharif, Mohammed Hussain
estimation of the moving hand and received signal strength (RSS). These two factors are estimated using two simple methods; channel impulse response (CIR) and cross correlation (CC) of the reflected ultrasonic signal from the gesturing hand. A customized
Pisharady, Pramod Kumar; Poh, Loh Ai
This book presents a collection of computational intelligence algorithms that addresses issues in visual pattern recognition such as high computational complexity, abundance of pattern features, sensitivity to size and shape variations and poor performance against complex backgrounds. The book has 3 parts. Part 1 describes various research issues in the field with a survey of the related literature. Part 2 presents computational intelligence based algorithms for feature selection and classification. The algorithms are discriminative and fast. The main application area considered is hand posture recognition. The book also discusses utility of these algorithms in other visual as well as non-visual pattern recognition tasks including face recognition, general object recognition and cancer / tumor classification. Part 3 presents biologically inspired algorithms for feature extraction. The visual cortex model based features discussed have invariance with respect to appearance and size of the hand, and provide good...
Bhuyan, M. K.; Kar, Mithun Kumar; Neog, Debanga Raj
In this paper, a novel algorithm is proposed for fingertips detection in view of two-handed static hand pose recognition. In our method, finger tips of both hands are detected after detecting hand regions by skin color-based segmentation. At first, the face is removed in the image by using Haar classifier and subsequently, the regions corresponding to the gesturing hands are isolated by a region labeling technique. Next, the key geometric features characterizing gesturing hands are extracted for two hands. Finally, for all possible/allowable finger movements, a probabilistic model is developed for pose recognition. Proposed method can be employed in a variety of applications like sign language recognition and human-robot-interactions etc.
Veldhuis, Raymond N.J.; Bazen, A.M.; Booij, W.D.T.; Hendrikse, A.J.; Jain, A.K.; Ratha, N.K.
This paper demonstrates the feasibility of a new method of hand-geometry recognition based on parameters derived from the contour of the hand. The contour is completely determined by the black-and-white image of the hand and can be derived from it by means of simple image-processing techniques. It
Baby, Sanmohan; Krüger, Volker
Imitation learning is considered to be an effective way of teaching humanoid robots and action recognition is the key step to imitation learning. In this paper an online algorithm to recognize parametric actions with object context is presented. Objects are key instruments in understanding...
The basic goal of human computer interaction is to improve the interaction between users and computers by making computers more usable and receptive to the user's needs. Within this context, the use of hand postures in replacement of traditional devices such as keyboards, mice and joysticks is being explored by many researchers. The goal is to interpret human postures via mathematical algorithms. Hand posture recognition has gained popularity in recent years, and could become the future tool for humans to interact with computers or virtual environments. An exhaustive description of the frequently used methods available in literature for hand posture recognition is provided. It focuses on the different types of sensors and data used, the segmentation and tracking methods, the features used to represent the hand postures as well as the classifiers considered in the recognition process. Those methods are usually presented as highly robust with a recognition rate close to 100%. However, a couple of critical points necessary for a successful real-time hand posture recognition system require major improvement. Those points include the features used to represent the hand segment, the number of postures simultaneously recognizable, the invariance of the features with respect to rotation, translation and scale and also the behavior of the classifiers against non-perfect hand segments for example segments including part of the arm or missing part of the palm. A 3D time-of-flight camera named SR4000 has been chosen to develop a new methodology because of its capability to provide in real-time and at high frame rate 3D information on the scene imaged. This sensor has been described and evaluated for its capability for capturing in real-time a moving hand. A new recognition method that uses the 3D information provided by the range camera to recognize hand postures has been proposed. The different steps of this methodology including the segmentation, the tracking, the hand
Full Text Available The paper describes a system of hand gesture recognition by image processing for human robot interaction. The recognition and interpretation of the hand postures acquired through a video camera allow the control of the robotic arm activity: motion - translation and rotation in 3D - and tightening/releasing the clamp. A gesture dictionary was defined and heuristic algorithms for recognition were developed and tested. The system can be used for academic and industrial purposes, especially for those activities where the movements of the robotic arm were not previously scheduled, for training the robot easier than using a remote control. Besides the gesture dictionary, the novelty of the paper consists in a new technique for detecting the relative positions of the fingers in order to recognize the various hand postures, and in the achievement of a robust system for controlling robots by postures of the hands.
Nayan M. Kakoty
Full Text Available This paper presents classification of grasp types based on surface electromyographic signals. Classification is through radial basis function kernel support vector machine using sum of wavelet decomposition coefficients of the EMG signals. In a study involving six subjects, we achieved an average recognition rate of 86%. The electromyographic grasp recognition together with a 8-bit microcontroller has been employed to control a fivefingered robotic hand to emulate six grasp types used during 70% daily living activities.
Full Text Available The task of human hand trajectory tracking and gesture trajectory recognition based on synchronized color and depth video is considered. Toward this end, in the facet of hand tracking, a joint observation model with the hand cues of skin saliency, motion and depth is integrated into particle filter in order to move particles to local peak in the likelihood. The proposed hand tracking method, namely, salient skin, motion, and depth based particle filter (SSMD-PF, is capable of improving the tracking accuracy considerably, in the context of the signer performing the gesture toward the camera device and in front of moving, cluttered backgrounds. In the facet of gesture recognition, a shape-order context descriptor on the basis of shape context is introduced, which can describe the gesture in spatiotemporal domain. The efficient shape-order context descriptor can reveal the shape relationship and embed gesture sequence order information into descriptor. Moreover, the shape-order context leads to a robust score for gesture invariant. Our approach is complemented with experimental results on the settings of the challenging hand-signed digits datasets and American sign language dataset, which corroborate the performance of the novel techniques.
Lv, Xiong; Wang, Shuang; Li, Xiangyang; Jiang, Shuqiang
Object recognition has wide applications in the area of human-machine interaction and multimedia retrieval. However, due to the problem of visual polysemous and concept polymorphism, it is still a great challenge to obtain reliable recognition result for the 2D images. Recently, with the emergence and easy availability of RGB-D equipment such as Kinect, this challenge could be relieved because the depth channel could bring more information. A very special and important case of object recognition is hand-held object recognition, as hand is a straight and natural way for both human-human interaction and human-machine interaction. In this paper, we study the problem of 3D object recognition by combining heterogenous features with different modalities and extraction techniques. For hand-craft feature, although it reserves the low-level information such as shape and color, it has shown weakness in representing hiconvolutionalgh-level semantic information compared with the automatic learned feature, especially deep feature. Deep feature has shown its great advantages in large scale dataset recognition but is not always robust to rotation or scale variance compared with hand-craft feature. In this paper, we propose a method to combine hand-craft point cloud features and deep learned features in RGB and depth channle. First, hand-held object segmentation is implemented by using depth cues and human skeleton information. Second, we combine the extracted hetegerogenous 3D features in different stages using linear concatenation and multiple kernel learning (MKL). Then a training model is used to recognize 3D handheld objects. Experimental results validate the effectiveness and gerneralization ability of the proposed method.
De Laurentis, Kathryn J; Mavroidis, Constantinos
This paper presents the mechanical design for a new five fingered, twenty degree-of-freedom dexterous hand patterned after human anatomy and actuated by Shape Memory Alloy artificial muscles. Two experimental prototypes of a finger, one fabricated by traditional means and another fabricated by rapid prototyping techniques, are described and used to evaluate the design. An important aspect of the Rapid Prototype technique used here is that this multi-articulated hand will be fabricated in one step, without requiring assembly, while maintaining its desired mobility. The use of Shape Memory Alloy actuators combined with the rapid fabrication of the non-assembly type hand, reduce considerably its weight and fabrication time. Therefore, the focus of this paper is the mechanical design of a dexterous hand that combines Rapid Prototype techniques and smart actuators. The type of robotic hand described in this paper can be utilized for applications requiring low weight, compactness, and dexterity such as prosthetic devices, space and planetary exploration.
Full Text Available Computers and computerized machines have tremendously penetrated all aspects of our lives. This raises the importance of Human-Computer Interface (HCI. The common HCI techniques still rely on simple devices such as keyboard, mice, and joysticks, which are not enough to convoy the latest technology. Hand gesture has become one of the most important attractive alternatives to existing traditional HCI techniques. This paper proposes a new hand gesture detection system for Human-Computer Interaction using real-time video streaming. This is achieved by removing the background using average background algorithm and the 1$ algorithm for hand’s template matching. Then every hand gesture is translated to commands that can be used to control robot movements. The simulation results show that the proposed algorithm can achieve high detection rate and small recognition time under different light changes, scales, rotation, and background.
Full Text Available This paper was conceived to present the ideology of utilizing advanced actuators to design and develop innovative, lightweight, powerful, compact, and as much as possible dexterous robotic hands. The key to satisfying these objectives is the use of Shape Memory Alloys (SMAs to power the joints of the robotic hand. The mechanical design of a dexterous robotic hand, which utilizes non-classical types of actuation and information obtained from the study of biological systems, is presented in this paper. The type of robotic hand described in this paper will be utilized for applications requiring low weight, power, compactness, and dexterity.
Allan P Lameira
Full Text Available We investigated the influence of hand posture in handedness recognition, while varying the spatial correspondence between stimulus and response in a modified Simon task. Drawings of the left and right hands were displayed either in a back or palm view while participants discriminated stimulus handedness by pressing left/right keys with their hands resting either in a prone or supine posture. As a control, subjects performed a regular Simon task using simple geometric shapes as stimuli. Results showed that when hands were in a prone posture, the spatially corresponding trials (i.e., stimulus and response located on the same side were faster than the non-corresponding trials (i.e., stimulus and response on opposite sides. In contrast, for the supine posture, there was no difference between corresponding and non-corresponding trials. The control experiment with the regular Simon task showed that the posture of the responding hand had no influence on performance. When the stimulus is the drawing of a hand, however, the posture of the responding hand affects the spatial correspondence effect because response location is coded based on multiple reference points, including the body of the hand.
Full Text Available To cope with the everyday challenges that they encounter in their evolutionary niche, crayfish are considered to rely mainly on chemical information or, alternatively, on tactile information, but not much on vision. Hence, research has focused on chemical communication, whereas crayfish visual abilities remain poorly understood and investigated. To fill in this gap, we tested whether crayfish (Procambarus clarkii can distinguish between two different visual shapes matched in terms of luminance. To this aim, we measured both the habituation response to a repeated presentation of a given shape, a downright Y, and the response recovery when a novel shape was presented. The novel shape could be either a Möbius or the same Y-shape but upright rotated. Our results demonstrate that, after habituation to the downright Y, crayfish showed a significantly higher response recovery to the Möbius as compared to the upright rotated Y. Hence, besides relying on chemo-haptic information, we found that crayfish can use sight alone to discriminate between different abstract geometrical shapes when macroscopically different. Failure to discriminate between the downright Y and its inversion or a generalization from the presence of a shape with three points creating a simple category, are both likely parsimonious explanations that should be investigated systematically in further studies. A future challenge will be understanding whether crayfish are capable of generalized shape recognition.
Full Text Available information to improve the initial shape recognition results. We propose an initial system which performs shape recognition using the euclidean distances of Fourier descriptors. To improve upon these results we build multinomial and Gaussian probabilistic...
Conson, Massimiliano; Volpicella, Francesco; De Bellis, Francesco; Orefice, Agnese; Trojano, Luigi
A key point in motor imagery literature is that judging hands in palm view recruits sensory-motor information to a higher extent than judging hands in back view, due to the greater biomechanical complexity implied in rotating hands depicted from palm than from back. We took advantage from this solid evidence to test the nature of a phenomenon known as self-advantage, i.e. the advantage in implicitly recognizing self vs. others' hand images. The self-advantage has been actually found when implicitly but not explicitly judging self-hands, likely due to dissociation between implicit and explicit body representations. However, such a finding might be related to the extent to which motor imagery is recruited during implicit and explicit processing of hand images. We tested this hypothesis in two behavioural experiments. In Experiment 1, right-handed participants judged laterality of either self or others' hands, whereas in Experiment 2, an explicit recognition of one's own hands was required. Crucially, in both experiments participants were randomly presented with hand images viewed from back or from palm. The main result of both experiments was the self-advantage when participants judged hands from palm view. This novel finding demonstrate that increasing the "motor imagery load" during processing of self vs. others' hands can elicit a self-advantage in explicit recognition tasks as well. Future studies testing the possible dissociation between implicit and explicit visual body representations should take into account the modulatory effect of motor imagery load on self-hand processing. Copyright © 2017. Published by Elsevier B.V.
Full Text Available The natural user interface (NUI is used for the natural motion interface without using device or tool such as mice, keyboards, pens and markers. In this paper, we develop natural user interface framework based on two recognition module. First module is real-time head pose estimation module using random forests and second module is hand gesture recognition module, named Hand gesture Key Emulation Toolkit (HandGKET. Using the head pose estimation module, we can know where the user is looking and what the user’s focus of attention is. Moreover, using the hand gesture recognition module, we can also control the computer using the user’s hand gesture without mouse and keyboard. In proposed framework, the user’s head direction and hand gesture are mapped into mouse and keyboard event, respectively.
Full Text Available For controlling the prosthetic hand by only electroencephalogram (EEG, it has become the hot spot in robotics research to set up a direct communication and control channel between human brain and prosthetic hand. In this paper, the EEG signal is analyzed based on multi-complicated hand activities. And then, two methods of EEG pattern recognition are investigated, a neural prosthesis hand system driven by BCI is set up, which can complete four kinds of actions (arm’s free state, arm movement, hand crawl, hand open. Through several times of off-line and on-line experiments, the result shows that the neural prosthesis hand system driven by BCI is reasonable and feasible, the C-support vector classifiers-based method is better than BP neural network on the EEG pattern recognition for multi-complicated hand activities.
Chew, Lin Hou; Teo, Jason; Mountstephens, James
Recognition and identification of aesthetic preference is indispensable in industrial design. Humans tend to pursue products with aesthetic values and make buying decisions based on their aesthetic preferences. The existence of neuromarketing is to understand consumer responses toward marketing stimuli by using imaging techniques and recognition of physiological parameters. Numerous studies have been done to understand the relationship between human, art and aesthetics. In this paper, we present a novel preference-based measurement of user aesthetics using electroencephalogram (EEG) signals for virtual 3D shapes with motion. The 3D shapes are designed to appear like bracelets, which is generated by using the Gielis superformula. EEG signals were collected by using a medical grade device, the B-Alert X10 from advance brain monitoring, with a sampling frequency of 256 Hz and resolution of 16 bits. The signals obtained when viewing 3D bracelet shapes were decomposed into alpha, beta, theta, gamma and delta rhythm by using time-frequency analysis, then classified into two classes, namely like and dislike by using support vector machines and K-nearest neighbors (KNN) classifiers respectively. Classification accuracy of up to 80 % was obtained by using KNN with the alpha, theta and delta rhythms as the features extracted from frontal channels, Fz, F3 and F4 to classify two classes, like and dislike.
González-Sosa, Ester; Vera-Rodríguez, Rubén; Fiérrez, Julián; Ortega-García, Javier
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Hu, Neng-Chung; Yu, Kuo-Kan; Hsu, Yung-Li
To deal with such a problem as object recognition of position, scale, and rotation invariance (PSRI), we utilize some PSRI properties of images obtained from objects, for example, the centroid of the image. The corresponding position of the centroid to the boundary of the image is invariant in spite of rotation, scale, and translation of the image. To obtain the information of the image, we use the technique similar to Radon transform, called the oriented-polar representation of a 2D image. In this representation, two specific points, the centroid and the weighted mean point, are selected to form an initial ray, then the image is sampled with N angularly equispaced rays departing from the initial rays. Each ray contains a number of intersections and the distance information obtained from the centroid to the intersections. The shape recognition algorithm is based on the least total error of these two items of information. Together with a simple noise removal and a typical backpropagation neural network, this algorithm is simple, but the PSRI is achieved with a high recognition rate.
Escalera, Sergio; Fornés, Alicia; Pujol, Oriol; Lladós, Josep; Radeva, Petia
In this paper, we propose a circular blurred shape model descriptor to deal with the problem of symbol detection and classification as a particular case of object recognition. The feature extraction is performed by capturing the spatial arrangement of significant object characteristics in a correlogram structure. The shape information from objects is shared among correlogram regions, where a prior blurring degree defines the level of distortion allowed in the symbol, making the descriptor tolerant to irregular deformations. Moreover, the descriptor is rotation invariant by definition. We validate the effectiveness of the proposed descriptor in both the multiclass symbol recognition and symbol detection domains. In order to perform the symbol detection, the descriptors are learned using a cascade of classifiers. In the case of multiclass categorization, the new feature space is learned using a set of binary classifiers which are embedded in an error-correcting output code design. The results over four symbol data sets show the significant improvements of the proposed descriptor compared to the state-of-the-art descriptors. In particular, the results are even more significant in those cases where the symbols suffer from elastic deformations.
Full Text Available This paper describes an algorithm for a visual human-machine interface that infers a person’s intention from the motion of the hand. Work in progress shows a proof of concept tested on static images. The context for which this solution is intended...
Adewuyi, Adenike A; Hargrove, Levi J; Kuiken, Todd A
Pattern recognition control combined with surface electromyography (EMG) from the extrinsic hand muscles has shown great promise for control of multiple prosthetic functions for transradial amputees. There is, however, a need to adapt this control method when implemented for partial-hand amputees, who possess both a functional wrist and information-rich residual intrinsic hand muscles. We demonstrate that combining EMG data from both intrinsic and extrinsic hand muscles to classify hand grasps and finger motions allows up to 19 classes of hand grasps and individual finger motions to be decoded, with an accuracy of 96% for non-amputees and 85% for partial-hand amputees. We evaluated real-time pattern recognition control of three hand motions in seven different wrist positions. We found that a system trained with both intrinsic and extrinsic muscle EMG data, collected while statically and dynamically varying wrist position increased completion rates from 73% to 96% for partial-hand amputees and from 88% to 100% for non-amputees when compared to a system trained with only extrinsic muscle EMG data collected in a neutral wrist position. Our study shows that incorporating intrinsic muscle EMG data and wrist motion can significantly improve the robustness of pattern recognition control for application to partial-hand prosthetic control.
Olgiati, Elena; Maravita, Angelo; Spandri, Viviana; Casati, Roberta; Ferraro, Francesco; Tedesco, Lucia; Agostoni, Elio Clemente; Bolognini, Nadia
The alien hand syndrome (AHS) is a rare neuropsychological disorder characterized by involuntary, yet purposeful, hand movements. Patients with the AHS typically complain about a loss of agency associated with a feeling of estrangement for actions performed by the affected limb. The present study explores the integrity of the body representation in AHS, focusing on 2 main processes: multisensory integration and visual self-recognition of body parts. Three patients affected by AHS following a right-hemisphere stroke, with clinical symptoms akin to the posterior variant of AHS, were tested and their performance was compared with that of 18 age-matched healthy controls. AHS patients and controls underwent 2 experimental tasks: a same-different visual matching task for body postures, which assessed the ability of using your own body schema for encoding others' body postural changes (Experiment 1), and an explicit self-hand recognition task, which assessed the ability to visually recognize your own hands (Experiment 2). As compared to controls, all AHS patients were unable to access a reliable multisensory representation of their alien hand and use it for decoding others' postural changes; however, they could rely on an efficient multisensory representation of their intact (ipsilesional) hand. Two AHS patients also presented with a specific impairment in the visual self-recognition of their alien hand, but normal recognition of their intact hand. This evidence suggests that the AHS following a right-hemisphere stroke may involve a disruption of the multisensory representation of the alien limb; instead, self-hand recognition mechanisms may be spared. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Favorskaya, M.; Nosov, A.; Popov, A.
Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin detector, normalized skeleton representation of one or two hands, and motion history representing by motion vectors normalized through predetermined directions (8 and 16 in our case). Each dynamic gesture is separated into a set of sub-gestures in order to predict a trajectory and remove those samples of gestures, which do not satisfy to current trajectory. The posture classifiers involve the normalized skeleton representation of palm and fingers and relative finger positions using fingertips. The min-max criterion is used for trajectory recognition, and the decision tree technique was applied for posture recognition of sub-gestures. For experiments, a dataset "Multi-modal Gesture Recognition Challenge 2013: Dataset and Results" including 393 dynamic hand-gestures was chosen. The proposed method yielded 84-91% recognition accuracy, in average, for restricted set of dynamic gestures.
Full Text Available Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin detector, normalized skeleton representation of one or two hands, and motion history representing by motion vectors normalized through predetermined directions (8 and 16 in our case. Each dynamic gesture is separated into a set of sub-gestures in order to predict a trajectory and remove those samples of gestures, which do not satisfy to current trajectory. The posture classifiers involve the normalized skeleton representation of palm and fingers and relative finger positions using fingertips. The min-max criterion is used for trajectory recognition, and the decision tree technique was applied for posture recognition of sub-gestures. For experiments, a dataset “Multi-modal Gesture Recognition Challenge 2013: Dataset and Results” including 393 dynamic hand-gestures was chosen. The proposed method yielded 84–91% recognition accuracy, in average, for restricted set of dynamic gestures.
This paper introduces a new Chinese Sign Language recognition (CSLR) system and a method of real-time tracking face and hand applied in the system. In the method, an improved agent algorithm is used to extract the region of face and hand and track them. Kalman filter is introduced to forecast the position and rectangle of search, and self-adapting of target color is designed to counteract the effect of illumination.
M. Favorskaya; A. Nosov; A. Popov
Generally, the dynamic hand gestures are captured in continuous video sequences, and a gesture recognition system ought to extract the robust features automatically. This task involves the highly challenging spatio-temporal variations of dynamic hand gestures. The proposed method is based on two-level manifold classifiers including the trajectory classifiers in any time instants and the posture classifiers of sub-gestures in selected time instants. The trajectory classifiers contain skin dete...
Earley, Eric J; Adewuyi, Adenike A; Hargrove, Levi J
Partial-hand amputees often retain good residual wrist motion, which is essential for functional activities involving use of the hand. Thus, a crucial design criterion for a myoelectric, partial-hand prosthesis control scheme is that it allows the user to retain residual wrist motion. Pattern recognition (PR) of electromyographic (EMG) signals is a well-studied method of controlling myoelectric prostheses. However, wrist motion degrades a PR system's ability to correctly predict hand-grasp patterns. We studied the effects of (1) window length and number of hand-grasps, (2) static and dynamic wrist motion, and (3) EMG muscle source on the ability of a PR-based control scheme to classify functional hand-grasp patterns. Our results show that training PR classifiers with both extrinsic and intrinsic muscle EMG yields a lower error rate than training with either group by itself (pgrasps available to the classifier significantly decrease classification error (pgrasp.
Peterson, Mary A.; Gibson, Bradley S.
Three experiments with 29 college students and 8 members of a university community demonstrate that shape recognition processes influence perceived figure-ground relationships in 3-dimensional displays when the edge between 2 potential figural regions is both a luminance contrast edge and a disparity edge. Implications for shape recognition and…
Tomporowski, Phillip D.; Albrecht, Chelesa; Pendleton, Daniel M.
Purpose: The purpose of this study was to determine if physical arousal produced by isometric hand-dynamometer contraction performed during word-list learning affects young adults' free recall or recognition memory. Method: Twenty-four young adults (12 female; M[subscript age] = 22 years) were presented with 4 20-item word lists. Moderate arousal…
Lu, Zhiyuan; Chen, Xiang; Zhang, Xu; Tong, Kay-Yu; Zhou, Ping
Robot-assisted training provides an effective approach to neurological injury rehabilitation. To meet the challenge of hand rehabilitation after neurological injuries, this study presents an advanced myoelectric pattern recognition scheme for real-time intention-driven control of a hand exoskeleton. The developed scheme detects and recognizes user's intention of six different hand motions using four channels of surface electromyography (EMG) signals acquired from the forearm and hand muscles, and then drives the exoskeleton to assist the user accomplish the intended motion. The system was tested with eight neurologically intact subjects and two individuals with spinal cord injury (SCI). The overall control accuracy was [Formula: see text] for the neurologically intact subjects and [Formula: see text] for the SCI subjects. The total lag of the system was approximately 250[Formula: see text]ms including data acquisition, transmission and processing. One SCI subject also participated in training sessions in his second and third visits. Both the control accuracy and efficiency tended to improve. These results show great potential for applying the advanced myoelectric pattern recognition control of the wearable robotic hand system toward improving hand function after neurological injuries.
Nikolaev, E. I.; Dvoryaninov, P. V.; Lensky, Y. Y.; Drozdovsky, N. S.
Deep learning has shown real promise for the classification efficiency for hand gesture recognition problems. In this paper, the authors present experimental results for a deeply-trained model for hand gesture recognition through the use of hand images. The authors have trained two deep convolutional neural networks. The first architecture produces the hand position as a 2D-vector by input hand image. The second one predicts the hand gesture class for the input image. The first proposed architecture produces state of the art results with an accuracy rate of 89% and the second architecture with split input produces accuracy rate of 85.2%. In this paper, the authors also propose using virtual data for training a supervised deep model. Such technique is aimed to avoid using original labelled images in the training process. The interest of this method in data preparation is motivated by the need to overcome one of the main challenges of deep supervised learning: using a copious amount of labelled data during training.
Shirkhodaie, Amir; Chan, Alex; Hu, Shuowen
Human activity detection and recognition capabilities have broad applications for military and homeland security. These tasks are very complicated, however, especially when multiple persons are performing concurrent activities in confined spaces that impose significant obstruction, occultation, and observability uncertainty. In this paper, our primary contribution is to present a dedicated taxonomy and kinematic ontology that are developed for in-vehicle group human activities (IVGA). Secondly, we describe a set of hand-observable patterns that represents certain IVGA examples. Thirdly, we propose two classifiers for hand gesture recognition and compare their performance individually and jointly. Finally, we present a variant of Hidden Markov Model for Bayesian tracking, recognition, and annotation of hand motions, which enables spatiotemporal inference to human group activity perception and understanding. To validate our approach, synthetic (graphical data from virtual environment) and real physical environment video imagery are employed to verify the performance of these hand gesture classifiers, while measuring their efficiency and effectiveness based on the proposed Hidden Markov Model for tracking and interpreting dynamic spatiotemporal IVGA scenarios.
Chen, Xinjian; Udupa, Jayaram K; Alavi, Abass; Torigian, Drew A
This paper studies the feasibility of developing an automatic anatomy recognition (AAR) system in clinical radiology and demonstrates its operation on clinical 2D images. The anatomy recognition method described here consists of two main components: (a) multiobject generalization of OASM and (b) object recognition strategies. The OASM algorithm is generalized to multiple objects by including a model for each object and assigning a cost structure specific to each object in the spirit of live wire. The delineation of multiobject boundaries is done in MOASM via a three level dynamic programming algorithm, wherein the first level is at pixel level which aims to find optimal oriented boundary segments between successive landmarks, the second level is at landmark level which aims to find optimal location for the landmarks, and the third level is at the object level which aims to find optimal arrangement of object boundaries over all objects. The object recognition strategy attempts to find that pose vector (consisting of translation, rotation, and scale component) for the multiobject model that yields the smallest total boundary cost for all objects. The delineation and recognition accuracies were evaluated separately utilizing routine clinical chest CT, abdominal CT, and foot MRI data sets. The delineation accuracy was evaluated in terms of true and false positive volume fractions (TPVF and FPVF). The recognition accuracy was assessed (1) in terms of the size of the space of the pose vectors for the model assembly that yielded high delineation accuracy, (2) as a function of the number of objects and objects' distribution and size in the model, (3) in terms of the interdependence between delineation and recognition, and (4) in terms of the closeness of the optimum recognition result to the global optimum. When multiple objects are included in the model, the delineation accuracy in terms of TPVF can be improved to 97%-98% with a low FPVF of 0.1%-0.2%. Typically, a
Amesz, Sarah; Tessari, Alessia; Ottoboni, Giovanni; Marsden, Jon
To explore the relationship between laterality recognition after stroke and impairments in attention, 3D object rotation and functional ability. Observational cross-sectional study. Acute care teaching hospital. Thirty-two acute and sub-acute people with stroke and 36 healthy, age-matched controls. Laterality recognition, attention and mental rotation of objects. Within the stroke group, the relationship between laterality recognition and functional ability, neglect, hemianopia and dyspraxia were further explored. People with stroke were significantly less accurate (69% vs 80%) and showed delayed reaction times (3.0 vs 1.9 seconds) when determining the laterality of a pictured hand. Deficits either in accuracy or reaction times were seen in 53% of people with stroke. The accuracy of laterality recognition was associated with reduced functional ability (R(2) = 0.21), less accurate mental rotation of objects (R(2) = 0.20) and dyspraxia (p = 0.03). Implicit motor imagery is affected in a significant number of patients after stroke with these deficits related to lesions to the motor networks as well as other deficits seen after stroke. This research provides new insights into how laterality recognition is related to a number of other deficits after stroke, including the mental rotation of 3D objects, attention and dyspraxia. Further research is required to determine if treatment programmes can improve deficits in laterality recognition and impact functional outcomes after stroke.
Full Text Available Finger knuckle print is considered as one of the emerging hand biometric traits due to its potentiality toward the identification of individuals. This paper contributes a new method for personal recognition using finger knuckle print based on two approaches namely, geometric and texture analyses. In the first approach, the shape oriented features of the finger knuckle print are extracted by means of angular geometric analysis and then integrated to achieve better precision rate. Whereas, the knuckle texture feature analysis is carried out by means of multi-resolution transform known as Curvelet transform. This Curvelet transform has the ability to approximate curved singularities with minimum number of Curvelet coefficients. Since, finger knuckle patterns mainly consist of lines and curves, Curvelet transform is highly suitable for its representation. Further, the Curvelet transform decomposes the finger knuckle image into Curvelet sub-bands which are termed as ‘Curvelet knuckle’. Finally, principle component analysis is applied on each Curvelet knuckle for extracting its feature vector through the covariance matrix derived from their Curvelet coefficients. Extensive experiments were conducted using PolyU database and IIT finger knuckle database. The experimental results confirm that, our proposed method shows a high recognition rate of 98.72% with lower false acceptance rate of 0.06%.
Benatti, Simone; Milosevic, Bojan; Farella, Elisabetta; Gruppioni, Emanuele; Benini, Luca
Poliarticulated prosthetic hands represent a powerful tool to restore functionality and improve quality of life for upper limb amputees. Such devices offer, on the same wearable node, sensing and actuation capabilities, which are not equally supported by natural interaction and control strategies. The control in state-of-the-art solutions is still performed mainly through complex encoding of gestures in bursts of contractions of the residual forearm muscles, resulting in a non-intuitive Human-Machine Interface (HMI). Recent research efforts explore the use of myoelectric gesture recognition for innovative interaction solutions, however there persists a considerable gap between research evaluation and implementation into successful complete systems. In this paper, we present the design of a wearable prosthetic hand controller, based on intuitive gesture recognition and a custom control strategy. The wearable node directly actuates a poliarticulated hand and wirelessly interacts with a personal gateway (i.e., a smartphone) for the training and personalization of the recognition algorithm. Through the whole system development, we address the challenge of integrating an efficient embedded gesture classifier with a control strategy tailored for an intuitive interaction between the user and the prosthesis. We demonstrate that this combined approach outperforms systems based on mere pattern recognition, since they target the accuracy of a classification algorithm rather than the control of a gesture. The system was fully implemented, tested on healthy and amputee subjects and compared against benchmark repositories. The proposed approach achieves an error rate of 1.6% in the end-to-end real time control of commonly used hand gestures, while complying with the power and performance budget of a low-cost microcontroller.
Iqtait, M.; Mohamad, F. S.; Mamat, M.
Biometric is a pattern recognition system which is used for automatic recognition of persons based on characteristics and features of an individual. Face recognition with high recognition rate is still a challenging task and usually accomplished in three phases consisting of face detection, feature extraction, and expression classification. Precise and strong location of trait point is a complicated and difficult issue in face recognition. Cootes proposed a Multi Resolution Active Shape Models (ASM) algorithm, which could extract specified shape accurately and efficiently. Furthermore, as the improvement of ASM, Active Appearance Models algorithm (AAM) is proposed to extracts both shape and texture of specified object simultaneously. In this paper we give more details about the two algorithms and give the results of experiments, testing their performance on one dataset of faces. We found that the ASM is faster and gains more accurate trait point location than the AAM, but the AAM gains a better match to the texture.
Sato, K; Kamiyama, K; Kawakami, N; Tachi, S
It is believed that the use of haptic sensors to measure the magnitude, direction, and distribution of a force will enable a robotic hand to perform dexterous operations. Therefore, we develop a new type of finger-shaped haptic sensor using GelForce technology. GelForce is a vision-based sensor that can be used to measure the distribution of force vectors, or surface traction fields. The simple structure of the GelForce enables us to develop a compact finger-shaped GelForce for the robotic hand. GelForce that is developed on the basis of an elastic theory can be used to calculate surface traction fields using a conversion equation. However, this conversion equation cannot be analytically solved when the elastic body of the sensor has a complicated shape such as the shape of a finger. Therefore, we propose an observational method and construct a prototype of the finger-shaped GelForce. By using this prototype, we evaluate the basic performance of the finger-shaped GelForce. Then, we conduct a field test by performing grasping operations using a robotic hand. The results of this test show that using the observational method, the finger-shaped GelForce can be successfully used in a robotic hand.
Mudhsh, Mohammed; Almodfer, Rolla; Duan, Pengfei; Xiong, Shengwu
In the handwriting recognition field, designing good descriptors are substantial to obtain rich information of the data. However, the handwriting recognition research of a good descriptor is still an open issue due to unlimited variation in human handwriting. We introduce a "character context descriptor" that efficiently dealt with the structural characteristics of Arabic handwritten characters. First, the character image is smoothed and normalized, then the character context descriptor of 32 feature bins is built based on the proposed "distance function." Finally, a multilayer perceptron with regularization is used as a classifier. On experimentation with a handwritten Arabic characters database, the proposed method achieved a state-of-the-art performance with recognition rate equal to 98.93% and 99.06% for the 66 and 24 classes, respectively.
Stoll, Chloé; Palluel-Germain, Richard; Caldara, Roberto; Lao, Junpeng; Dye, Matthew W. G.; Aptel, Florent; Pascalis, Olivier
Previous research has suggested that early deaf signers differ in face processing. Which aspects of face processing are changed and the role that sign language may have played in that change are however unclear. Here, we compared face categorization (human/non-human) and human face recognition performance in early profoundly deaf signers, hearing…
Han, Eun Jung; Kang, Byung Jun; Park, Kang Ryoung; Lee, Sangyoun
Facial expression recognition can be widely used for various applications, such as emotion-based human-machine interaction, intelligent robot interfaces, face recognition robust to expression variation, etc. Previous studies have been classified as either shape- or appearance-based recognition. The shape-based method has the disadvantage that the individual variance of facial feature points exists irrespective of similar expressions, which can cause a reduction of the recognition accuracy. The appearance-based method has a limitation in that the textural information of the face is very sensitive to variations in illumination. To overcome these problems, a new facial-expression recognition method is proposed, which combines both shape and appearance information, based on the support vector machine (SVM). This research is novel in the following three ways as compared to previous works. First, the facial feature points are automatically detected by using an active appearance model. From these, the shape-based recognition is performed by using the ratios between the facial feature points based on the facial-action coding system. Second, the SVM, which is trained to recognize the same and different expression classes, is proposed to combine two matching scores obtained from the shape- and appearance-based recognitions. Finally, a single SVM is trained to discriminate four different expressions, such as neutral, a smile, anger, and a scream. By determining the expression of the input facial image whose SVM output is at a minimum, the accuracy of the expression recognition is much enhanced. The experimental results showed that the recognition accuracy of the proposed method was better than previous researches and other fusion methods.
Bambach, Sven; Crandall, David J; Yu, Chen
Wearable devices are becoming part of everyday life, from first-person cameras (GoPro, Google Glass), to smart watches (Apple Watch), to activity trackers (FitBit). These devices are often equipped with advanced sensors that gather data about the wearer and the environment. These sensors enable new ways of recognizing and analyzing the wearer's everyday personal activities, which could be used for intelligent human-computer interfaces and other applications. We explore one possible application by investigating how egocentric video data collected from head-mounted cameras can be used to recognize social activities between two interacting partners (e.g. playing chess or cards). In particular, we demonstrate that just the positions and poses of hands within the first-person view are highly informative for activity recognition, and present a computer vision approach that detects hands to automatically estimate activities. While hand pose detection is imperfect, we show that combining evidence across first-person views from the two social partners significantly improves activity recognition accuracy. This result highlights how integrating weak but complimentary sources of evidence from social partners engaged in the same task can help to recognize the nature of their interaction.
Andrews, Timothy J; Baseler, Heidi; Jenkins, Rob; Burton, A Mike; Young, Andrew W
A full understanding of face recognition will involve identifying the visual information that is used to discriminate different identities and how this is represented in the brain. The aim of this study was to explore the importance of shape and surface properties in the recognition and neural representation of familiar faces. We used image morphing techniques to generate hybrid faces that mixed shape properties (more specifically, second order spatial configural information as defined by feature positions in the 2D-image) from one identity and surface properties from a different identity. Behavioural responses showed that recognition and matching of these hybrid faces was primarily based on their surface properties. These behavioural findings contrasted with neural responses recorded using a block design fMRI adaptation paradigm to test the sensitivity of Haxby et al.'s (2000) core face-selective regions in the human brain to the shape or surface properties of the face. The fusiform face area (FFA) and occipital face area (OFA) showed a lower response (adaptation) to repeated images of the same face (same shape, same surface) compared to different faces (different shapes, different surfaces). From the behavioural data indicating the critical contribution of surface properties to the recognition of identity, we predicted that brain regions responsible for familiar face recognition should continue to adapt to faces that vary in shape but not surface properties, but show a release from adaptation to faces that vary in surface properties but not shape. However, we found that the FFA and OFA showed an equivalent release from adaptation to changes in both shape and surface properties. The dissociation between the neural and perceptual responses suggests that, although they may play a role in the process, these core face regions are not solely responsible for the recognition of facial identity. Copyright © 2016 Elsevier Ltd. All rights reserved.
Borovicka, J.; Stoyanov, S.D.; Paunov, V.N.
We have engineered a class of colloids which can recognize the shape and size of targeted microbial cells and selectively bind to their surfaces. These imprinted colloid particles, which we called "colloid antibodies", were fabricated by partial fragmentation of silica shells obtained by templating
Lopes, Oscar; Reyes, Miguel; Escalera, Sergio; Gonzàlez, Jordi
The use of depth maps is of increasing interest after the advent of cheap multisensor devices based on structured light, such as Kinect. In this context, there is a strong need of powerful 3-D shape descriptors able to generate rich object representations. Although several 3-D descriptors have been already proposed in the literature, the research of discriminative and computationally efficient descriptors is still an open issue. In this paper, we propose a novel point cloud descriptor called spherical blurred shape model (SBSM) that successfully encodes the structure density and local variabilities of an object based on shape voxel distances and a neighborhood propagation strategy. The proposed SBSM is proven to be rotation and scale invariant, robust to noise and occlusions, highly discriminative for multiple categories of complex objects like the human hand, and computationally efficient since the SBSM complexity is linear to the number of object voxels. Experimental evaluation in public depth multiclass object data, 3-D facial expressions data, and a novel hand poses data sets show significant performance improvements in relation to state-of-the-art approaches. Moreover, the effectiveness of the proposal is also proved for object spotting in 3-D scenes and for real-time automatic hand pose recognition in human computer interaction scenarios.
Conson, Massimiliano; Errico, Domenico; Mazzarella, Elisabetta; De Bellis, Francesco; Grossi, Dario; Trojano, Luigi
Judgments on laterality of hand stimuli are faster and more accurate when dealing with one's own than others' hand, i.e. the self-advantage. This advantage seems to be related to activation of a sensorimotor mechanism while implicitly processing one's own hands, but not during explicit one's own hand recognition. Here, we specifically tested the influence of proprioceptive information on the self-hand advantage by manipulating participants' body posture during self and others' hand processing. In Experiment 1, right-handed healthy participants judged laterality of either self or others' hands, whereas in Experiment 2, an explicit recognition of one's own hands was required. In both experiments, the participants performed the task while holding their left or right arm flexed with their hand in direct contact with their chest ("flexed self-touch posture") or with their hand placed on a wooden smooth surface in correspondence with their chest ("flexed proprioceptive-only posture"). In an "extended control posture", both arms were extended and in contact with thighs. In Experiment 1 (hand laterality judgment), we confirmed the self-advantage and demonstrated that it was enhanced when the subjects judged left-hand stimuli at 270° orientation while keeping their left arm in the flexed proprioceptive-only posture. In Experiment 2 (explicit self-hand recognition), instead, we found an advantage for others' hand ("self-disadvantage") independently from posture manipulation. Thus, position-related proprioceptive information from left non-dominant arm can enhance sensorimotor one's own body representation selectively favouring implicit self-hands processing.
Gunasekaran, Prasad; Grandison, Scott; Cowtan, Kevin; Mak, Lora; Lawson, David M.; Morris, Richard J.
We present a novel approach to crystallographic ligand density interpretation based on Zernike shape descriptors. Electron density for a bound ligand is expanded in an orthogonal polynomial series (3D Zernike polynomials) and the coefficients from this expansion are employed to construct rotation-invariant descriptors. These descriptors can be compared highly efficiently against large databases of descriptors computed from other molecules. In this manuscript we describe this process and show initial results from an electron density interpretation study on a dataset containing over a hundred OMIT maps. We could identify the correct ligand as the first hit in about 30 % of the cases, within the top five in a further 30 % of the cases, and giving rise to an 80 % probability of getting the correct ligand within the top ten matches. In all but a few examples, the top hit was highly similar to the correct ligand in both shape and chemistry. Further extensions and intrinsic limitations of the method are discussed.
Yang, Ruiduo; Sarkar, Sudeep; Loeding, Barbara
We consider two crucial problems in continuous sign language recognition from unaided video sequences. At the sentence level, we consider the movement epenthesis (me) problem and at the feature level, we consider the problem of hand segmentation and grouping. We construct a framework that can handle both of these problems based on an enhanced, nested version of the dynamic programming approach. To address movement epenthesis, a dynamic programming (DP) process employs a virtual me option that does not need explicit models. We call this the enhanced level building (eLB) algorithm. This formulation also allows the incorporation of grammar models. Nested within this eLB is another DP that handles the problem of selecting among multiple hand candidates. We demonstrate our ideas on four American Sign Language data sets with simple background, with the signer wearing short sleeves, with complex background, and across signers. We compared the performance with Conditional Random Fields (CRF) and Latent Dynamic-CRF-based approaches. The experiments show more than 40 percent improvement over CRF or LDCRF approaches in terms of the frame labeling rate. We show the flexibility of our approach when handling a changing context. We also find a 70 percent improvement in sign recognition rate over the unenhanced DP matching algorithm that does not accommodate the me effect.
Gao, Jun; Bao, Jie; Chen, Dingguo; Yang, Youqing; Yang, Xuedong
This paper presents a novel optical-electronic shape recognition system based on synergetic associative memory. Our shape recognition system is composed of two parts: the first one is feature extraction system; the second is synergetic pattern recognition system. Hough transform is proposed for feature extraction of unrecognized object, with the effects of reducing dimensions and filtering for object distortion and noise, synergetic neural network is proposed for realizing associative memory in order to eliminate spurious states. Then we adopt an approach of optical- electronic realization to our system that can satisfy the demands of real time, high speed and parallelism. In order to realize fast algorithm, we replace the dynamic evolution circuit with adjudge circuit according to the relationship between attention parameters and order parameters, then implement the recognition of some simple images and its validity is proved.
Elleuch, Hanene; Wali, Ali; Samet, Anis; Alimi, Adel M.
Two systems of eyes and hand gestures recognition are used to control mobile devices. Based on a real-time video streaming captured from the device's camera, the first system recognizes the motion of user's eyes and the second one detects the static hand gestures. To avoid any confusion between natural and intentional movements we developed a system to fuse the decision coming from eyes and hands gesture recognition systems. The phase of fusion was based on decision tree approach. We conducted a study on 5 volunteers and the results that our system is robust and competitive.
Sormaz, Mladen; Young, Andrew W; Andrews, Timothy J
Theoretical accounts of face processing often emphasise feature shapes as the primary visual cue to the recognition of facial expressions. However, changes in facial expression also affect the surface properties of the face. In this study, we investigated whether this surface information can also be used in the recognition of facial expression. First, participants identified facial expressions (fear, anger, disgust, sadness, happiness) from images that were manipulated such that they varied mainly in shape or mainly in surface properties. We found that the categorization of facial expression is possible in either type of image, but that different expressions are relatively dependent on surface or shape properties. Next, we investigated the relative contributions of shape and surface information to the categorization of facial expressions. This employed a complementary method that involved combining the surface properties of one expression with the shape properties from a different expression. Our results showed that the categorization of facial expressions in these hybrid images was equally dependent on the surface and shape properties of the image. Together, these findings provide a direct demonstration that both feature shape and surface information make significant contributions to the recognition of facial expressions. Copyright © 2016 Elsevier Ltd. All rights reserved.
Travieso, Carlos M; Briceño, Juan Carlos; Alonso, Jesús B
The present work presents a biometric identification system for hand shape identification. The different contours have been coded based on angular descriptions forming a Markov chain descriptor. Discrete Hidden Markov Models (DHMM), each representing a target identification class, have been trained with such chains. Features have been calculated from a kernel based on the HMM parameter descriptors. Finally, supervised Support Vector Machines were used to classify parameters from the DHMM kernel. First, the system was modelled using 60 users to tune the DHMM and DHMM_kernel+SVM configuration parameters and finally, the system was checked with the whole database (GPDS database, 144 users with 10 samples per class). Our experiments have obtained similar results in both cases, demonstrating a scalable, stable and robust system. Our experiments have achieved an upper success rate of 99.87% for the GPDS database using three hand samples per class in training mode, and seven hand samples in test mode. Secondly, the authors have verified their algorithms using another independent and public database (the UST database). Our approach has reached 100% and 99.92% success for right and left hand, respectively; showing the robustness and independence of our algorithms. This success was found using as features the transformation of 100 points hand shape with our DHMM kernel, and as classifier Support Vector Machines with linear separating functions, with similar success.
Jesús B. Alonso
Full Text Available The present work presents a biometric identification system for hand shape identification. The different contours have been coded based on angular descriptions forming a Markov chain descriptor. Discrete Hidden Markov Models (DHMM, each representing a target identification class, have been trained with such chains. Features have been calculated from a kernel based on the HMM parameter descriptors. Finally, supervised Support Vector Machines were used to classify parameters from the DHMM kernel. First, the system was modelled using 60 users to tune the DHMM and DHMM_kernel+SVM configuration parameters and finally, the system was checked with the whole database (GPDS database, 144 users with 10 samples per class. Our experiments have obtained similar results in both cases, demonstrating a scalable, stable and robust system. Our experiments have achieved an upper success rate of 99.87% for the GPDS database using three hand samples per class in training mode, and seven hand samples in test mode. Secondly, the authors have verified their algorithms using another independent and public database (the UST database. Our approach has reached 100% and 99.92% success for right and left hand, respectively; showing the robustness and independence of our algorithms. This success was found using as features the transformation of 100 points hand shape with our DHMM kernel, and as classifier Support Vector Machines with linear separating functions, with similar success.
Full Text Available Gesture recognition is essential for human and robot collaboration. Within an industrial hybrid assembly cell, the performance of such a system significantly affects the safety of human workers. This work presents an approach to recognizing hand gestures accurately during an assembly task while in collaboration with a robot co-worker. We have designed and developed a sensor system for measuring natural human-robot interactions. The position and rotation information of a human worker's hands and fingertips are tracked in 3D space while completing a task. A modified chain-code method is proposed to describe the motion trajectory of the measured hands and fingertips. The Hidden Markov Model (HMM method is adopted to recognize patterns via data streams and identify workers' gesture patterns and assembly intentions. The effectiveness of the proposed system is verified by experimental results. The outcome demonstrates that the proposed system is able to automatically segment the data streams and recognize the gesture patterns thus represented with a reasonable accuracy ratio.
Full Text Available Emotion recognition from speech may play a crucial role in many applications related to human–computer interaction or understanding the affective state of users in certain tasks, where other modalities such as video or physiological parameters are unavailable. In general, a human’s emotions may be recognized using several modalities such as analyzing facial expressions, speech, physiological parameters (e.g., electroencephalograms, electrocardiograms etc. However, measuring of these modalities may be difficult, obtrusive or require expensive hardware. In that context, speech may be the best alternative modality in many practical applications. In this work we present an approach that uses a Convolutional Neural Network (CNN functioning as a visual feature extractor and trained using raw speech information. In contrast to traditional machine learning approaches, CNNs are responsible for identifying the important features of the input thus, making the need of hand-crafted feature engineering optional in many tasks. In this paper no extra features are required other than the spectrogram representations and hand-crafted features were only extracted for validation purposes of our method. Moreover, it does not require any linguistic model and is not specific to any particular language. We compare the proposed approach using cross-language datasets and demonstrate that it is able to provide superior results vs. traditional ones that use hand-crafted features.
Full Text Available Various humanoid robots have been developed and multifunction robot hands which are able to attach those robots like human hand is needed. But a useful robot hand has not been depeveloped, because there are a lot of problems such as control method of many degrees of freedom and processing method of enormous sensor outputs. Realizing such robot hand, we have developed five-finger robot hand. In this paper, the detailed structure of developed robot hand is described. The robot hand we developed has five fingers of multi-joint that is equipped with joint torque sensors and tactile sensors. We report experimental results of a stiffness control with the developed robot hand. Those results show that it is possible to change the stiffness of joints. Moreover we propose an object recognition method with the tactile sensor. The validity of that method is assured by experimental results.
A system was developed to recognize if the shape of a signal x(t) is similar (or identical) to the one of an element yi(t) of an ensemble S composed by N known signals, that are memorised. x(t) is a time limited T 2 ) give the similarity measure of two signals. To solve the problem of the digital recording of the signals x(t) two devices were realized: a digital-to-analog converter which permits the recording of fast transient signals (band pass>1GHz, sampling-frequency approximately 100GHz, resolution: 9 bits, 576 samples); an automatic attenuator which scales the signal x(t) before the digitalization (the band pass is 70MHz at -1dB). A theoretical analysis permits to determine what must be the resolution of the digital-to-analog converter as a fonction of the signal-caracteristics and of the wanted precision for the calculus of rho 2 [fr
Dalawis, Rando C.; Olayao, Kenneth Deniel R.; Ramos, Evan Geoffrey I.; Samonte, Mary Jane C.
A different approach of sign language recognition of static and dynamic hand movements was developed in this study using normalized correlation algorithm. The goal of this research was to translate fingerspelling sign language into text using MATLAB and Microsoft Kinect. Digital input image captured by Kinect devices are matched from template samples stored in a database. This Human Computer Interaction (HCI) prototype was developed to help people with communication disability to express their thoughts with ease. Frame segmentation and feature extraction was used to give meaning to the captured images. Sequential and random testing was used to test both static and dynamic fingerspelling gestures. The researchers explained some factors they encountered causing some misclassification of signs.
Oikonomopoulos, A.; Patras, I.; Pantic, Maja
In this paper we address the problem of localisation and recognition of human activities in unsegmented image sequences. The main contribution of the proposed method is the use of an implicit representation of the spatiotemporal shape of the activity which relies on the spatiotemporal localization
Full Text Available The arising of domestic robots in smart infrastructure has raised demands for intuitive and natural interaction between humans and robots. To address this problem, a wearable wrist-worn camera (WwwCam is proposed in this paper. With the capability of recognizing human hand gestures in real-time, it enables services such as controlling mopping robots, mobile manipulators, or appliances in smart-home scenarios. The recognition is based on finger segmentation and template matching. Distance transformation algorithm is adopted and adapted to robustly segment fingers from the hand. Based on fingers’ angles relative to the wrist, a finger angle prediction algorithm and a template matching metric are proposed. All possible gesture types of the captured image are first predicted, and then evaluated and compared to the template image to achieve the classification. Unlike other template matching methods relying highly on large training set, this scheme possesses high flexibility since it requires only one image as the template, and can classify gestures formed by different combinations of fingers. In the experiment, it successfully recognized ten finger gestures from number zero to nine defined by American Sign Language with an accuracy up to 99.38%. Its performance was further demonstrated by manipulating a robot arm using the implemented algorithms and WwwCam to transport and pile up wooden building blocks.
Raffin, Estelle; Pellegrino, Giovanni; Di Lazzaro, Vincenzo
Motor representations express some degree of somatotopy in human primary motor hand area (M1HAND), but within-M1HAND corticomotor somatotopy has been difficult to study with transcranial magnetic stimulation (TMS). Here we introduce a “linear” TMS mapping approach based on the individual shape...... of the central sulcus to obtain mediolateral corticomotor excitability profiles of the abductor digiti minimi (ADM) and first dorsal interosseus (FDI) muscles. In thirteen young volunteers, we used stereotactic neuronavigation to stimulate the right M1HAND with a small eight-shaped coil at 120% of FDI resting...
Hargreaves, Ian S; Pexman, Penny M; Zdrazilova, Lenka; Sargious, Peter
Competitive Scrabble is an activity that involves extraordinary word recognition experience. We investigated whether that experience is associated with exceptional behavior in the laboratory in a classic visual word recognition paradigm: the lexical decision task (LDT). We used a version of the LDT that involved horizontal and vertical presentation and a concreteness manipulation. In Experiment 1, we presented this task to a group of undergraduates, as these participants are the typical sample in word recognition studies. In Experiment 2, we compared the performance of a group of competitive Scrabble players with a group of age-matched nonexpert control participants. The results of a series of cognitive assessments showed that the Scrabble players and control participants differed only in Scrabble-specific skills (e.g., anagramming). Scrabble expertise was associated with two specific effects (as compared to controls): vertical fluency (relatively less difficulty judging lexicality for words presented in the vertical orientation) and semantic deemphasis (smaller concreteness effects for word responses). These results suggest that visual word recognition is shaped by experience, and that with experience there are efficiencies to be had even in the adult word recognition system.
Juday, Richard D. (Editor)
The present conference discusses topics in pattern-recognition correlator architectures, digital stereo systems, geometric image transformations and their applications, topics in pattern recognition, filter algorithms, object detection and classification, shape representation techniques, and model-based object recognition methods. Attention is given to edge-enhancement preprocessing using liquid crystal TVs, massively-parallel optical data base management, three-dimensional sensing with polar exponential sensor arrays, the optical processing of imaging spectrometer data, hybrid associative memories and metric data models, the representation of shape primitives in neural networks, and the Monte Carlo estimation of moment invariants for pattern recognition.
Fallahi, Ali Asghar; Jadidian, Ali Akbar
It has been suggested that athletes with longer fingers and larger hand surfaces enjoy stronger grip power. Therefore, some researchers have examined a number of factors and anthropometric variables that explain this issue. To our knowledge, the data is scarce. Thus, the aim of this study was to investigate the effect of hand dimensions, hand shape and some anthropometric characteristics on handgrip strength in male grip athletes and non-athletes. 80 subjects aged between 19 and 29 participated in this study in two groups including: national and collegian grip athletes (n=40), and non-athletes (n=40). Body height and mass were measured to calculate body mass index. The shape of the dominant hand was drawn on a piece of paper with a thin marker so that finger spans, finger lengths, and perimeters of the hand could be measured. The hand shape was estimated as the ratio of the hand width to hand length. Handgrip strength was measured in the dominant and non-dominant hand using a standard dynamometer. Descriptive statistics were used for each variable and independent t test was used to analyze the differences between the two groups. The Pearson correlation coefficient test was used to evaluate the correlation between studied variables. Also, to predict important variables in handgrip strength, the linear trend was assessed using a linear regression analysis. There was a significant difference between the two groups in absolute handgrip strength (p0.05) were significantly different between the groups (ptalent identification in handgrip-related sports and in clinical settings as well. PMID:23486361
Soriano-Heras, Enrique; Blaya-Haro, Fernando; Molino, Carlos; de Agustín Del Burgo, José María
The purpose of this article is to develop a new concept of modular and operative prosthetic hand based on rapid prototyping and a novel shape-memory-alloy (SMA) actuator, thus minimizing the manufacturing costs. An underactuated mechanism was needed for the design of the prosthesis to use only one input source. Taking into account the state of the art, an underactuated mechanism prosthetic hand was chosen so as to implement the modifications required for including the external SMA actuator. A modular design of a new prosthesis was developed which incorporated a novel SMA actuator for the index finger movement. The primary objective of the prosthesis is achieved, obtaining a modular and functional low-cost prosthesis based on additive manufacturing executed by a novel SMA actuator. The external SMA actuator provides a modular system which allows implementing it in different systems. This paper combines rapid prototyping and a novel SMA actuator to develop a new concept of modular and operative low-cost prosthetic hand.
Humans have always used sketches to explain the visual world. It is a simple and straight- forward mean to communicate new ideas and designs. Consequently, as in almost every aspect of our modern life, the relatively recent major developments in computer science have highly contributed to enhancing individual sketching experience. The literature of sketch related research has witnessed seminal advancements and a large body of interest- ing work. Following up with this rich literature, this dissertation provides a holistic study on sketches through three proposed novel models including sketch analysis, transfer, and geometric representation. The first part of the dissertation targets sketch authorship recognition and analysis of sketches. It provides answers to the following questions: Are simple strokes unique to the artist or designer who renders them? If so, can this idea be used to identify authorship or to classify artistic drawings? The proposed stroke authorship recognition approach is a novel method that distinguishes the authorship of 2D digitized drawings. This method converts a drawing into a histogram of stroke attributes that is discriminative of authorship. Extensive classification experiments on a large variety of datasets are conducted to validate the ability of the proposed techniques to distinguish unique authorship of artists and designers. The second part of the dissertation is concerned with sketch style transfer from one free- hand drawing to another. The proposed method exploits techniques from multi-disciplinary areas including geometrical modeling and image processing. It consists of two methods of transfer: stroke-style and brush-style transfer. (1) Stroke-style transfer aims to transfer the style of the input sketch at the stroke level to the style encountered in other sketches by other artists. This is done by modifying all the parametric stroke segments in the input, so as to minimize a global stroke-level distance between the input and
Peterson, M A; Harvey, E M; Weidenbacher, H J
Observers viewed upright and inverted versions of figure-ground stimuli, in which Gestalt variables specified that the center was figure. In upright versions, the surround was high in denotivity, in that most viewers agreed it depicted the same shape; in inverted versions, the surround was low in denotivity. The surround was maintained as figure longer and was more likely to be obtained as figure when the stimuli were upright rather than inverted. In four experiments, these effects reflected inputs to figure-ground computations from orientation-specific shape representations only. To account for these findings, a nonratiomorphic mechanism is proposed that enables shape recognition processes before figure-ground relationships are determined.
Tu, Ming-Gene; Chen, San-Yue; Huang, Heng-Li; Tsai, Chi-Cheng
Preparing a continuous tapering conical shape and maintaining the original shape of a canal are obligatory in root canal preparation. The purpose of this study was to compare the shaping performance in simulated curved canal resin blocks of the same novice dental students using hand-prepared and engine-driven nickel–titanium (NiTi) rotary ProTaper instruments in an endodontic laboratory class. Methods: Twenty-three fourth-year dental students attending China Medical University Dental Schoo...
Fallahpour, Mojtaba Behzad; Dehghani, Hamid; Jabbar Rashidi, Ali; Sheikhi, Abbas
Target recognition is one of the most important issues in the interpretation of the synthetic aperture radar (SAR) images. Modelling, analysis, and recognition of the effects of influential parameters in the SAR can provide a better understanding of the SAR imaging systems, and therefore facilitates the interpretation of the produced images. Influential parameters in SAR images can be divided into five general categories of radar, radar platform, channel, imaging region, and processing section, each of which has different physical, structural, hardware, and software sub-parameters with clear roles in the finally formed images. In this paper, for the first time, a behaviour library that includes the effects of polarisation, incidence angle, and shape of targets, as radar and imaging region sub-parameters, in the SAR images are extracted. This library shows that the created pattern for each of cylindrical, conical, and cubic shapes is unique, and due to their unique properties these types of shapes can be recognised in the SAR images. This capability is applied to data acquired with the Canadian RADARSAT1 satellite.
Nook, Erik C; Lindquist, Kristen A; Zaki, Jamil
Decades ago, the "New Look" movement challenged how scientists thought about vision by suggesting that conceptual processes shape visual perceptions. Currently, affective scientists are likewise debating the role of concepts in emotion perception. Here, we utilized a repetition-priming paradigm in conjunction with signal detection and individual difference analyses to examine how providing emotion labels-which correspond to discrete emotion concepts-affects emotion recognition. In Study 1, pairing emotional faces with emotion labels (e.g., "sad") increased individuals' speed and sensitivity in recognizing emotions. Additionally, individuals with alexithymia-who have difficulty labeling their own emotions-struggled to recognize emotions based on visual cues alone, but not when emotion labels were provided. Study 2 replicated these findings and further demonstrated that emotion concepts can shape perceptions of facial expressions. Together, these results suggest that emotion perception involves conceptual processing. We discuss the implications of these findings for affective, social, and clinical psychology. (c) 2015 APA, all rights reserved).
Full Text Available We report on the synthesis and characterization of novel shape-persistent, optically active arylamide macrocycles, which can be obtained using a one-pot methodology. Resolved, axially chiral binol scaffolds, which incorporate either methoxy or acetoxy functionalities in the 2,2' positions and carboxylic functionalities in the external 3,3' positions, were used as the source of chirality. Two of these binaphthyls are joined through amidation reactions using rigid diaryl amines of differing shapes, to give homochiral tetraamidic macrocycles. The recognition properties of these supramolecular receptors have been analyzed, and the results indicate a modulation of binding affinities towards dicarboxylate anions, with a drastic change of binding mode depending on the steric and electronic features of the functional groups in the 2,2' positions.
Khayat, Omid; Afarideh, Hossein
Track counting algorithms as one of the fundamental principles of nuclear science have been emphasized in the recent years. Accurate measurement of nuclear tracks on solid-state nuclear track detectors is the aim of track counting systems. Commonly track counting systems comprise a hardware system for the task of imaging and software for analysing the track images. In this paper, a track recognition algorithm based on 12 defined textual and shape-based features and a neuro-fuzzy classifier is proposed. Features are defined so as to discern the tracks from the background and small objects. Then, according to the defined features, tracks are detected using a trained neuro-fuzzy system. Features and the classifier are finally validated via 100 Alpha track images and 40 training samples. It is shown that principle textual and shape-based features concomitantly yield a high rate of track detection compared with the single-feature based methods.
Lu, Zhiyuan; Tong, Kai-Yu; Shin, Henry; Stampas, Argyrios; Zhou, Ping
A 51-year-old man with an incomplete C6 spinal cord injury sustained 26 yrs ago attended twenty 2-hr visits over 10 wks for robot-assisted hand training driven by myoelectric pattern recognition. In each visit, his right hand was assisted to perform motions by an exoskeleton robot, while the robot was triggered by his own motion intentions. The hand robot was designed for this study, which can perform six kinds of motions, including hand closing/opening; thumb, index finger, and middle finger closing/opening; and middle, ring, and little fingers closing/opening. After the training, his grip force increased from 13.5 to 19.6 kg, his pinch force remained the same (5.0 kg), his score of Box and Block test increased from 32 to 39, and his score from the Graded Redefined Assessment of Strength, Sensibility, and Prehension test Part 4.B increased from 22 to 24. He accomplished the tasks in the Graded Redefined Assessment of Strength, Sensibility, and Prehension test Part 4.B 28.8% faster on average. The results demonstrate the feasibility and effectiveness of robot-assisted training driven by myoelectric pattern recognition after spinal cord injury.
Tu, Ming-Gene; Chen, San-Yue; Huang, Heng-Li; Tsai, Chi-Cheng
Preparing a continuous tapering conical shape and maintaining the original shape of a canal are obligatory in root canal preparation. The purpose of this study was to compare the shaping performance in simulated curved canal resin blocks of the same novice dental students using hand-prepared and engine-driven nickel-titanium (NiTi) rotary ProTaper instruments in an endodontic laboratory class. Twenty-three fourth-year dental students attending China Medical University Dental School prepared 46 simulated curved canals in resin blocks with two types of NiTi rotary systems: hand and motor ProTaper files. Composite images were prepared for estimation. Material removed, canal width and canal deviation were measured at five levels in the apical 4 mm of the simulated curved canals using AutoCAD 2004 software. Data were analyzed using Wilcoxon's rank-sum test. The hand ProTaper group cut significantly wider than the motor rotary ProTaper group in the outer wall, except for the apical 0 mm point. The total canal width was cut significantly larger in the hand group than in the motor group. There was no significant difference between the two groups in centering canal shape, except at the 3 mm level. These findings show that the novice students prepared the simulated curved canal that deviated more outwardly from apical 1 mm to 4 mm using the hand ProTaper. The ability to maintain the original curvature was better in the motor rotary ProTaper group than in the hand ProTaper group. Undergraduate students, if following the preparation sequence carefully, could successfully perform canal shaping by motor ProTaper files and achieve better root canal geometry than by using hand ProTaper files within the same teaching and practicing sessions.
Baydoun, Mohamad; Betancourt, Alejandro; Morerio, Pietro; Marcenaro, Lucio; Rauterberg, Matthias; Regazzoni, Carlo
© 2017 IEEE. With the growing availability of wearable technology, video recording devices have become so intimately tied to individuals, that they are able to record the movements of users' hands, making hand-based applications one the most explored area in First Person Vision (FPV). In particular,
Lee, Jin Hyuck; Kim, Dae Hyun
Ultrasonic inspection robot systems have been widely researched and developed for the real-time monitoring of structures such as power plants. However, an inspection robot that is operated in a simple pattern has limitations in its application to various structures in a plant facility because of the diverse and complicated shapes of the inspection objects. Therefore, accurate control of the robot is required to inspect complicated objects with high-precision results. This paper presents the idea that the shape and movement information of an ultrasonic inspector's hand could be profitably utilized for the accurate control of robot. In this study, a polymer flex sensor was applied to monitor the shape of a human hand. This application was designed to intuitively control an ultrasonic inspection robot. The movement and shape of the hand were estimated by applying multiple sensors. Moreover, it was successfully shown that a test robot could be intuitively controlled based on the shape of a human hand estimated using polymer flex sensors.
Lee, Jin Hyuck; Kim, Dae Hyun [Seoul National University of Technology, Seoul (Korea, Republic of)
Ultrasonic inspection robot systems have been widely researched and developed for the real-time monitoring of structures such as power plants. However, an inspection robot that is operated in a simple pattern has limitations in its application to various structures in a plant facility because of the diverse and complicated shapes of the inspection objects. Therefore, accurate control of the robot is required to inspect complicated objects with high-precision results. This paper presents the idea that the shape and movement information of an ultrasonic inspector's hand could be profitably utilized for the accurate control of robot. In this study, a polymer flex sensor was applied to monitor the shape of a human hand. This application was designed to intuitively control an ultrasonic inspection robot. The movement and shape of the hand were estimated by applying multiple sensors. Moreover, it was successfully shown that a test robot could be intuitively controlled based on the shape of a human hand estimated using polymer flex sensors.
Ashraf, Farhad Bin; Alam, Touhidul; Islam, Mohammad Tariqul
A Xi-shaped meta structure, has been introduced in this paper. A modified split-ring resonator (MSRR) and a capacitive loaded strip (CLS) were used to achieve the left-handed property of the metamaterial. The structure was printed using silver metallic nanoparticle ink, using a very low-cost photo paper as a substrate material. Resonators were inkjet-printed using silver nanoparticle metallic ink on paper to make this metamaterial flexible. It is also free from any kind of chemical waste, which makes it eco-friendly. A double negative region from 8.72 GHz to 10.91 GHz (bandwidth of 2.19 GHz) in the X-band microwave spectra was been found. Figure of merit was also obtained to measure any loss in the double negative region. The simulated result was verified by the performance of the fabricated prototype. The total dimensions of the proposed structure were 0.29 λ × 0.29 λ × 0.007 λ . It is a promising unit cell because of its simplicity, cost-effectiveness, and easy fabrication process.
Raghavan, Preeti; Santello, Marco; Gordon, Andrew M.; Krakauer, John W.
Efficient grasping requires planned and accurate coordination of finger movements to approximate the shape of an object before contact. In healthy subjects, hand shaping is known to occur early in reach under predominantly feedforward control. In patients with hemiparesis after stroke, execution of coordinated digit motion during grasping is impaired as a result of damage to the corticospinal tract. The question addressed here is whether patients with hemiparesis are able to compensate for th...
Conclusion: These findings show that the novice students prepared the simulated curved canal that deviated more outwardly from apical 1 mm to 4 mm using the hand ProTaper. The ability to maintain the original curvature was better in the motor rotary ProTaper group than in the hand ProTaper group. Undergraduate students, if following the preparation sequence carefully, could successfully perform canal shaping by motor ProTaper files and achieve better root canal geometry than by using hand ProTaper files within the same teaching and practicing sessions.
Linkenauger, Sally A; Leyrer, Markus; Bülthoff, Heinrich H; Mohler, Betty J
The notion of body-based scaling suggests that our body and its action capabilities are used to scale the spatial layout of the environment. Here we present four studies supporting this perspective by showing that the hand acts as a metric which individuals use to scale the apparent sizes of objects in the environment. However to test this, one must be able to manipulate the size and/or dimensions of the perceiver's hand which is difficult in the real world due to impliability of hand dimensions. To overcome this limitation, we used virtual reality to manipulate dimensions of participants' fully-tracked, virtual hands to investigate its influence on the perceived size and shape of virtual objects. In a series of experiments, using several measures, we show that individuals' estimations of the sizes of virtual objects differ depending on the size of their virtual hand in the direction consistent with the body-based scaling hypothesis. Additionally, we found that these effects were specific to participants' virtual hands rather than another avatar's hands or a salient familiar-sized object. While these studies provide support for a body-based approach to the scaling of the spatial layout, they also demonstrate the influence of virtual bodies on perception of virtual environments.
Sally A Linkenauger
Full Text Available The notion of body-based scaling suggests that our body and its action capabilities are used to scale the spatial layout of the environment. Here we present four studies supporting this perspective by showing that the hand acts as a metric which individuals use to scale the apparent sizes of objects in the environment. However to test this, one must be able to manipulate the size and/or dimensions of the perceiver's hand which is difficult in the real world due to impliability of hand dimensions. To overcome this limitation, we used virtual reality to manipulate dimensions of participants' fully-tracked, virtual hands to investigate its influence on the perceived size and shape of virtual objects. In a series of experiments, using several measures, we show that individuals' estimations of the sizes of virtual objects differ depending on the size of their virtual hand in the direction consistent with the body-based scaling hypothesis. Additionally, we found that these effects were specific to participants' virtual hands rather than another avatar's hands or a salient familiar-sized object. While these studies provide support for a body-based approach to the scaling of the spatial layout, they also demonstrate the influence of virtual bodies on perception of virtual environments.
Hellemans, J; Coucke, PJ; Giedion, A; De Paepe, A; Kramer, P; Beemer, F; Mortier, GR
Acrocapitofemoral dysplasia is a recently delineated autosomal recessive skeletal dysplasia, characterized clinically by short stature with short limbs and radiographically by cone-shaped epiphyses, mainly in hands and hips. Genome-wide homozygosity mapping in two consanguineous families linked the
When judging whether a relationship partner can be counted on to "be there" when needed, people may draw upon knowledge structures to process relevant information. We examined one such knowledge structure using the prototype methodology: indicators of a partner who is likely to be there when needed. In the first study (N = 91), the structure, content, and reliability of the prototype of indicators were examined. Then, using a false recognition study (N = 77), we demonstrated that once activated, the prototype of indicators of a partner who is likely to be there when needed affects information processing. Thus, the prototype of indicators may shape how people process support-relevant information in everyday life, affecting relationship outcomes. Using this knowledge structure may help a person process relevant information quickly and with cognitive economy. However, it may also lead to biases in judgments in certain situations.
Raghavan, Preeti; Santello, Marco; Gordon, Andrew M; Krakauer, John W
Efficient grasping requires planned and accurate coordination of finger movements to approximate the shape of an object before contact. In healthy subjects, hand shaping is known to occur early in reach under predominantly feedforward control. In patients with hemiparesis after stroke, execution of coordinated digit motion during grasping is impaired as a result of damage to the corticospinal tract. The question addressed here is whether patients with hemiparesis are able to compensate for their execution deficit with a qualitatively different grasp strategy that still allows them to differentiate hand posture to object shape. Subjects grasped a rectangular, concave, and convex object while wearing an instrumented glove. Reach-to-grasp was divided into three phases based on wrist kinematics: reach acceleration (reach onset to peak horizontal wrist velocity), reach deceleration (peak horizontal wrist velocity to reach offset), and grasp (reach offset to lift-off). Patients showed reduced finger abduction, proximal interphalangeal joint (PIP) flexion, and metacarpophalangeal joint (MCP) extension at object grasp across all three shapes compared with controls; however, they were able to partially differentiate hand posture for the convex and concave shapes using a compensatory strategy that involved increased MCP flexion rather than the PIP flexion seen in controls. Interestingly, shape-specific hand postures did not unfold initially during reach acceleration as seen in controls, but instead evolved later during reach deceleration, which suggests increased reliance on sensory feedback. These results indicate that kinematic analysis can identify and quantify within-limb compensatory motor control strategies after stroke. From a clinical perspective, quantitative study of compensation is important to better understand the process of recovery from brain injury. From a motor control perspective, compensation can be considered a model for how joint redundancy is exploited
Louzolo, Anaïs; Kalckert, Andreas; Petrovic, Predrag
Psychotic patients have problems with bodily self-recognition such as the experience of self-produced actions (sense of agency) and the perception of the body as their own (sense of ownership). While it has been shown that such impairments in psychotic patients can be explained by hypersalient processing of external sensory input it has also been suggested that they lack normal efference copy in voluntary action. However, it is not known how problems with motor predictions like efference copy contribute to impaired sense of agency and ownership in psychosis or psychosis-related states. We used a rubber hand illusion based on finger movements and measured sense of agency and ownership to compute a bodily self-recognition score in delusion-proneness (indexed by Peters' Delusion Inventory - PDI). A group of healthy subjects (n=71) experienced active movements (involving motor predictions) or passive movements (lacking motor predictions). We observed a highly significant correlation between delusion-proneness and self-recognition in the passive conditions, while no such effect was observed in the active conditions. This was seen for both ownership and agency scores. The result suggests that delusion-proneness is associated with hypersalient external input in passive conditions, resulting in an abnormal experience of the illusion. We hypothesize that this effect is not present in the active condition because deficient motor predictions counteract hypersalience in psychosis proneness.
Werner, Annette; Stürzl, Wolfgang; Zanker, Johannes
Honeybees (Apis mellifera) discriminate multiple object features such as colour, pattern and 2D shape, but it remains unknown whether and how bees recover three-dimensional shape. Here we show that bees can recognize objects by their three-dimensional form, whereby they employ an active strategy to uncover the depth profiles. We trained individual, free flying honeybees to collect sugar water from small three-dimensional objects made of styrofoam (sphere, cylinder, cuboids) or folded paper (convex, concave, planar) and found that bees can easily discriminate between these stimuli. We also tested possible strategies employed by the bees to uncover the depth profiles. For the card stimuli, we excluded overall shape and pictorial features (shading, texture gradients) as cues for discrimination. Lacking sufficient stereo vision, bees are known to use speed gradients in optic flow to detect edges; could the bees apply this strategy also to recover the fine details of a surface depth profile? Analysing the bees' flight tracks in front of the stimuli revealed specific combinations of flight maneuvers (lateral translations in combination with yaw rotations), which are particularly suitable to extract depth cues from motion parallax. We modelled the generated optic flow and found characteristic patterns of angular displacement corresponding to the depth profiles of our stimuli: optic flow patterns from pure translations successfully recovered depth relations from the magnitude of angular displacements, additional rotation provided robust depth information based on the direction of the displacements; thus, the bees flight maneuvers may reflect an optimized visuo-motor strategy to extract depth structure from motion signals. The robustness and simplicity of this strategy offers an efficient solution for 3D-object-recognition without stereo vision, and could be employed by other flying insects, or mobile robots.
Communication symbols for students with severe intellectual disabilities often take the form of computer-generated line drawings. This study investigated the effects of the match between color and shape of line drawings and the objects they represented on drawing recognition and use. The match or non-match between color and shape of the objects and drawings did not have an effect on participants' ability to match drawings to objects, or to use drawings to make choices.
Seif, Mujan; Beck, Matthew
Hands-on experiences are excellent tools for increasing retention of first year engineering students. They also encourage interdisciplinary collaboration, a critical skill for modern engineers. In this paper, we describe and evaluate a joint Chemical and Materials Engineering hands-on lab that explores cross-linking and glass transition in…
Palermo, Francesca; Cognolato, Matteo; Gijsberts, Arjan; Muller, Henning; Caputo, Barbara; Atzori, Manfredo
Control methods based on sEMG obtained promising results for hand prosthetics. Control system robustness is still often inadequate and does not allow the amputees to perform a large number of movements useful for everyday life. Only few studies analyzed the repeatability of sEMG classification of hand grasps. The main goals of this paper are to explore repeatability in sEMG data and to release a repeatability database with the recorded experiments. The data are recorded from 10 intact subjects repeating 7 grasps 12 times, twice a day for 5 days. The data are publicly available on the Ninapro web page. The analysis for the repeatability is based on the comparison of movement classification accuracy in several data acquisitions and for different subjects. The analysis is performed using mean absolute value and waveform length features and a Random Forest classifier. The accuracy obtained by training and testing on acquisitions at different times is on average 27.03% lower than training and testing on the same acquisition. The results obtained by training and testing on different acquisitions suggest that previous acquisitions can be used to train the classification algorithms. The inter-subject variability is remarkable, suggesting that specific characteristics of the subjects can affect repeatibility and sEMG classification accuracy. In conclusion, the results of this paper can contribute to develop more robust control systems for hand prostheses, while the presented data allows researchers to test repeatability in further analyses.
John Jairo Villarejo Mayor
Full Text Available Abstract Introduction Intuitive prosthesis control is one of the most important challenges in order to reduce the user effort in learning how to use an artificial hand. This work presents the development of a novel method for pattern recognition of sEMG signals able to discriminate, in a very accurate way, dexterous hand and fingers movements using a reduced number of electrodes, which implies more confidence and usability for amputees. Methods The system was evaluated for ten forearm amputees and the results were compared with the performance of able-bodied subjects. Multiple sEMG features based on fractal analysis (detrended fluctuation analysis and Higuchi’s fractal dimension combined with traditional magnitude-based features were analyzed. Genetic algorithms and sequential forward selection were used to select the best set of features. Support vector machine (SVM, K-nearest neighbors (KNN and linear discriminant analysis (LDA were analyzed to classify individual finger flexion, hand gestures and different grasps using four electrodes, performing contractions in a natural way to accomplish these tasks. Statistical significance was computed for all the methods using different set of features, for both groups of subjects (able-bodied and amputees. Results The results showed average accuracy up to 99.2% for able-bodied subjects and 98.94% for amputees using SVM, followed very closely by KNN. However, KNN also produces a good performance, as it has a lower computational complexity, which implies an advantage for real-time applications. Conclusion The results show that the method proposed is promising for accurately controlling dexterous prosthetic hands, providing more functionality and better acceptance for amputees.
Minami, Mamoru; Nishimura, Kenta; Sunami, Yusuke; Yanou, Akira; Yu, Cui; Yamashita, Manabu; Ishiyama, Shintaro
New robotic system that uses three dimensional measurement with solid object recognition —3D-MOS (Three Dimensional Move on Sensing)— based on visual servoing technology was designed and the on-board hand-eye-dual-cameras robot system has been developed to reduce risks of radiation exposure during decontamination processes by filter press machine that solidifies and reduces the volume of irradiation contaminated soil. The feature of 3D-MoS includes; (1) the both hand-eye-dual-cameras take the images of target object near the intersection of both lenses' centerlines, (2) the observation at intersection enables both cameras can see target object almost at the center of both images, (3) then it brings benefits as reducing the effect of lens aberration and improving the detection accuracy of three dimensional position. In this study, accuracy validation test of interdigitation of the robot's hand into filter cloth rod of the filter press —the task is crucial for the robot to remove the contaminated cloth from the filter press machine automatically and for preventing workers from exposing to radiation—, was performed. Then the following results were derived; (1) the 3D-MoS controlled robot could recognize the rod at arbitrary position within designated space, and all of insertion test were carried out successfully and, (2) test results also demonstrated that the proposed control guarantees that interdigitation clearance between the rod and robot hand can be kept within 1.875[mm] with standard deviation being 0.6[mm] or less. (author)
Schmid, Volker R.; Bader, Gerhard; Lueder, Ernst H.
We present a hybrid shape recognition system with an optical Hough transform processor. The features of the Hough space offer a separate cancellation of distortions caused by translations and rotations. Scale invariance is also provided by suitable normalization. The proposed system extends the capabilities of Hough transform based detection from only straight lines to areas bounded by edges. A very compact optical design is achieved by a microlens array processor accepting incoherent light as direct optical input and realizing the computationally expensive connections massively parallel. Our newly developed algorithm extracts rotation and translation invariant normalized patterns of bright spots on a 2D grid. A neural network classifier maps the 2D features via a nonlinear hidden layer onto the classification output vector. We propose initialization of the connection weights according to regions of activity specifically assigned to each neuron in the hidden layer using a competitive network. The presented system is designed for industry inspection applications. Presently we have demonstrated detection of six different machined parts in real-time. Our method yields very promising detection results of more than 96% correctly classified parts.
Granert, Oliver; Peller, Martin; Gaser, Christian
which was designed to improve handwriting-associated dystonia. Initially the dystonic hand was immobilized for 4 weeks with the intention to reverse faulty plasticity. After immobilization, patients accomplished a motor re-training for 8 weeks. T1-weighted MRIs of the whole brain and single-pulse TMS...
Ihsan Abdulhussein Baqer firstname.lastname@example.org
Full Text Available In this paper, the Artificial Neural Network (ANN is trained on the patterns of the normal component to tangential component ratios at the time of slippage occurrence, so that it can be able to distinguish the slippage occurrence under different type of load (quasi-static and dynamic loads, and then generates a feedback signal used as an input signal to run the actuator. This process is executed without the need for any information about the characteristics of the grasped object, such as weight, surface texture, shape, coefficient of the friction and the type of the load exerted on the grasped object. For fulfillment this approach, a new fingertip design has been proposed in order to detect the slippage in multi-direction between the grasped object and the artificial fingertips. This design is composed of two under-actuated fingers with an actuation system which includes flexible parts (compressive springs. These springs operate as a compensator for the grasping force at the time of slippage occurrence in spite of the actuator is in stopped situation. The contact force component ratios can be calculated via a conventional sensor (Flexiforce sensor after processed the force data using Matlab/Simulink program through a specific mathematical model which is derived according to the mechanism of the artificial finger.
Full Text Available This paper presents a performance analysis and comparison of several pre-processing methods used in a hand gesture recognition system. The pre-processing methods are based on the combinations of several image processing operations, namely edge detection, low pass filtering, histogram equalization, thresholding and desaturation. The hand gesture recognition system is designed to classify an input image into one of six possible classes. The input images are taken with various background conditions. Our experiments showed that the best result is achieved when the pre-processing method consists of only a desaturation operation, achieving a classification accuracy of up to 83.15%.
In this article, I shall examine the cognitive, heuristic and theoretical functions of the concept of recognition. To evaluate both the explanatory power and the limitations of a sociological concept, the theory construction must be analysed and its actual productivity for sociological theory mus...
Xu He-Xiu; Wang Guang-Ming; Yang Zi-Mu; Wang Jia-Fu
A method of fabricating dual-band left-handed metematerials (LHMs) is investigated numerically and experimentally by single-sided tree-like fractals. The resulting structure features multiband magnetic resonances and two electric resonances. By appropriately adjusting the dimensions, two left-handed (LH) bands with simultaneous negative permittivity and permeability are engineered and are validated by full-wave eigenmode analysis and measurement as well in the microwave frequency range. To study the multi-resonant mechanism in depth, the LHM is analysed from three different perspectives of field distribution analysis, circuit model analysis, and geometrical parameters evaluation. The derived formulae are consistent with all simulated results and resulting electromagnetic phenomena, indicating the effectiveness of the established theory. The method provides an alternative to the design of multi-band LHM and has the advantage of not requiring two individual resonant particles and electrically continuous wires, which in turn facilitates planar design and considerably simplifies the fabrication. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)
Full Text Available One emerging biometric identification method is the use of human footprint. However, in the previous research, there were some limitations resulting from the spatial resolution of sensors. One possible method to overcome this limitation is through the use additional information such as dynamic walking information in sequential walking footprint. In this study, we suggest a new person recognition scheme based on both overlapped foot shape and COP (Center Of Pressure trajectory during one-step walking. And, we show the usefulness of the suggested method, obtaining a 98.6% recognition rate in our experiment with eleven people. In addition, we show an application of the suggested method, automatic door-opening system for intelligent residential space.
Full Text Available This paper presents a performance analysis and comparison of several pre-processing methods used in a hand gesture recognition system. The preprocessing methods are based on the combinations ofseveral image processing operations, namely edge detection, low pass filtering, histogram equalization, thresholding and desaturation. The hand gesture recognition system is designed to classify an input image into one of six possibleclasses. The input images are taken with various background conditions. Our experiments showed that the best result is achieved when the pre-processing method consists of only a desaturation operation, achieving a classification accuracy of up to 83.15%.
Full Text Available The present study investigates the role that shape and color play in the representation of animate (i.e. animals and inanimate manipulable entities (i.e. fruits, and how the importance of these features is modulated by different tasks. Across three experiments participants were shown either images of entities (e.g., a sheep or a pineapple or images of the same entities modified in color (e.g. a blue pineapple or in shape (e.g. an elongated pineapple. In Experiment 1 we asked participants to categorize the entities as fruit or animal. Results showed that with animals color does not matter, while shape modifications determined a deterioration of the performance - stronger for fruit than for animals. To better understand the findings, in Experiment 2 participants were asked to judge if entities were graspable (manipulation evaluation task. Participants were faster with manipulable entities (fruit than with animals; moreover alterations in shape affected the response latencies more for animals than for fruit. In Experiment 3 (motion evaluation task, we replicated the disadvantage for shape-altered animals, while with fruits shape and color modifications produced no effect. By contrasting shape- and color- alterations the present findings provide information on shape/color relative weight, suggesting that the action based property of shape is more crucial than color for fruit categorization, while with animals it is critical for both manipulation and motion tasks. This contextual dependency is further revealed by explicit judgments on similarity - between the altered entities and the prototypical ones - provided after the different tasks. These results extend current literature on affordances and biofunctionally embodied understanding, revealing the relative robustness of biofunctional activity compared to intellectual one.
Tomizuka, Chiaki; Takeuchi, Yutaka
In a nuclear facility, the maintenance and repair activities must be done remotely in a radioactive environment. Fuji Electric Systems Co., Ltd. has developed a remote handling system based on 3-D recognition technique. The system recognizes the pose and position of the target to manipulate, and visualizes the scene with the target in 3-D, enabling an operator to handle it easily. This paper introduces the concept and the key features of this system. (author)
Baumle, Amanda K
Lawyers who practice family law for LGBT clients are key players in the tenuous and evolving legal environment surrounding same-sex marriage recognition. Building on prior research on factors shaping the professional identities of lawyers generally, and activist lawyers specifically, I examine how practice within a rapidly changing, patchwork legal environment shapes professional identity for this group of lawyers. I draw on interviews with 21 LGBT family lawyers to analyze how the unique features of LGBT family law shape their professional identities and practice, as well as their predictions about the development of the practice in a post-Obergefell world. Findings reveal that the professional identities and practice of LGBT family lawyers are shaped by uncertainty, characteristics of activist lawyering, community membership, and community service. Individual motivations and institutional forces work to generate a professional identity that is resilient and dynamic, characterized by skepticism and distrust coupled with flexibility and creativity. These features are likely to play a role in the evolution of the LGBT family lawyer professional identity post-marriage equality.
White, Hannah; Jubran, Rachel; Heck, Alison; Chroust, Alyson; Bhatt, Ramesh S
In this study we sought to determine whether infants, like adults, utilize previous experience to guide figure/ground processing. After familiarization to a shape, 5-month-olds preferentially attended to the side of an ambiguous figure/ground test stimulus corresponding to that shape, suggesting that they were viewing that portion as the figure. Infants' failure to exhibit this preference in a control condition in which both sides of the test stimulus were displayed as figures indicated that the results in the experimental condition were not due to a preference between two figure shapes. These findings demonstrate for the first time that figure/ground processing in infancy is sensitive to top-down influence. Thus, a critical aspect of figure/ground processing is functional early in life.
Bresciani, Anne Gøther; Paul, Sinu; Schommer, Nina
or allergen with the conservation of its sequence in the human proteome or the healthy human microbiome. Indeed, performing such comparisons on large sets of validated T-cell epitopes, we found that epitopes that are similar with self-antigens above a certain threshold showed lower immunogenicity, presumably...... as a result of negative selection of T cells capable of recognizing such peptides. Moreover, we also found a reduced level of immune recognition for epitopes conserved in the commensal microbiome, presumably as a result of peripheral tolerance. These findings indicate that the existence (and potentially...
Franco, Patrick; Ogier, Jean-Marc; Loonis, Pierre; Mullot, Rémy
Recently we have developed a model for shape description and matching. Based on minimum spanning trees construction and specifics stages like the mixture, it seems to have many desirable properties. Recognition invariance in front shift, rotated and noisy shape was checked through median scale tests related to GREC symbol reference database. Even if extracting the topology of a shape by mapping the shortest path connecting all the pixels seems to be powerful, the construction of graph induces an expensive algorithmic cost. In this article we discuss on the ways to reduce time computing. An alternative solution based on image compression concepts is provided and evaluated. The model no longer operates in the image space but in a compact space, namely the Discrete Cosine space. The use of block discrete cosine transform is discussed and justified. The experimental results led on the GREC2003 database show that the proposed method is characterized by a good discrimination power, a real robustness to noise with an acceptable time computing.
Novák, Václav; Landa, Michal; Šittner, Petr
Roč. 112, - (2003), s. 593-596 ISSN 1155-4339 R&D Projects: GA AV ČR IAA1048107; GA ČR GA106/01/0396 Institutional research plan: CEZ:AV0Z1010914 Keywords : shape memory alloys(SMA) * Cu-based SMA * Martensitic phase transformation * acoustic emission Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 0.319, year: 2003
Principal component analysis (PCA) is a popular tool for linear dimensionality reduction and feature extraction. Kernel PCA is the nonlinear form of PCA, which better exploits the complicated spatial structure of high-dimensional features. In this paper, we first review the basic ideas of PCA and kernel PCA. Then we focus on the reconstruction of pre-images for kernel PCA. We also give an introduction on how PCA is used in active shape models (ASMs), and discuss how kernel PCA can be applied ...
Tamaru, Yoshiki; Naito, Yasuo; Nishikawa, Takashi
Elderly people are less able to manipulate objects skilfully than young adults. Although previous studies have examined age-related deterioration of hand movements with a focus on the phase after grasping objects, the changes in the reaching phase have not been studied thus far. We aimed to examine whether changes in hand shape patterns during the reaching phase of grasping movements differ between young adults and the elderly. Ten healthy elderly adults and 10 healthy young adults were examined using the Simple Test for Evaluating Hand Functions and kinetic analysis of hand pre-shaping reach-to-grasp tasks. The results were then compared between the two groups. For kinetic analysis, we measured the time of peak tangential velocity of the wrist and the inter-fingertip distance (the distance between the tips of the thumb and index finger) at different time points. The results showed that the elderly group's performance on the Simple Test for Evaluating Hand Functions was significantly lower than that of the young adult group, irrespective of whether the dominant or non-dominant hand was used, indicating deterioration of hand movement in the elderly. The peak tangential velocity of the wrist in either hand appeared significantly earlier in the elderly group than in the young adult group. The elderly group also showed larger inter-fingertip distances with arch-like fingertip trajectories compared to the young adult group for all object sizes. To perform accurate prehension, elderly people have an earlier peak tangential velocity point than young adults. This allows for a longer adjustment time for reaching and grasping movements and for reducing errors in object prehension by opening the hand and fingers wider. Elderly individuals gradually modify their strategy based on previous successes and failures during daily living to compensate for their decline in dexterity and operational capabilities. © 2017 Japanese Psychogeriatric Society.
De Winter, François-Laurent; Timmers, Dorien; de Gelder, Beatrice; Van Orshoven, Marc; Vieren, Marleen; Bouckaert, Miriam; Cypers, Gert; Caekebeke, Jo; Van de Vliet, Laura; Goffin, Karolien; Van Laere, Koen; Sunaert, Stefan; Vandenberghe, Rik; Vandenbulcke, Mathieu; Van den Stock, Jan
Deficits in face processing have been described in the behavioral variant of fronto-temporal dementia (bvFTD), primarily regarding the recognition of facial expressions. Less is known about face shape and face identity processing. Here we used a hierarchical strategy targeting face shape and face identity recognition in bvFTD and matched healthy controls. Participants performed 3 psychophysical experiments targeting face shape detection (Experiment 1), unfamiliar face identity matching (Experiment 2), familiarity categorization and famous face-name matching (Experiment 3). The results revealed group differences only in Experiment 3, with a deficit in the bvFTD group for both familiarity categorization and famous face-name matching. Voxel-based morphometry regression analyses in the bvFTD group revealed an association between grey matter volume of the left ventral anterior temporal lobe and familiarity recognition, while face-name matching correlated with grey matter volume of the bilateral ventral anterior temporal lobes. Subsequently, we quantified familiarity-specific and name-specific recognition deficits as the sum of the celebrities of which respectively only the name or only the familiarity was accurately recognized. Both indices were associated with grey matter volume of the bilateral anterior temporal cortices. These findings extent previous results by documenting the involvement of the left anterior temporal lobe (ATL) in familiarity detection and the right ATL in name recognition deficits in fronto-temporal lobar degeneration.
Full Text Available Aim: This study aims to evaluate and compare the incidence of dentinal defects induced by Hand Files, HyFlex CM, ProTaper Next (PTN, and One Shape during canal preparation. Materials and Methods: One hundred and fifty extracted mandibular premolar teeth with single root canal were selected. Specimens were then divided into five groups with thirty specimens each. Group I: Specimens were prepared with hand instruments. Group II: Specimens were prepared with HyFlex CM rotary files (Coltene using a crown-down technique according to the manufacturer's instructions. Group III: Specimens were prepared with PTN rotary files (Dentsply using a crown-down technique according to the manufacturer's instructions. Group IV: Specimens were prepared with One Shape Single file rotary system (MicroMega using a crown-down technique according to the manufacturer's instructions. Group V: Specimens were used as a control and left unprepared. All roots were cut horizontally at 3, 6, and 9 mm from the apex. Sections were then viewed under stereomicroscope and dentinal defects were registered as “no defect,” “fracture,” and “other defects.” Statistical Analysis: Results of the study were subjected to Chi-square test. Results: Results were expressed as the number and percentage of defected, partially defected and roots with no defects in each groups. Conclusion: Hand files and One Shape file system caused less root defects compared to PTN and HyFlex file systems.
Full Text Available Most nuclear receptors (NRs bind DNA as dimers, either as hetero- or as homodimers on DNA sequences organized as two half-sites with specific orientation and spacing. The dimerization of NRs on their cognate response elements (REs involves specific protein–DNA and protein–protein interactions. The estrogen-related receptor (ERR belongs to the steroid hormone nuclear receptor (SHR family and shares strong similarity in its DNA-binding domain (DBD with that of the estrogen receptor (ER. In vitro, ERR binds with high affinity inverted repeat REs with a 3-bps spacing (IR3, but in vivo, it preferentially binds to single half-site REs extended at the 5′-end by 3 bp [estrogen-related response element (ERREs], thus explaining why ERR was often inferred as a purely monomeric receptor. Since its C-terminal ligand-binding domain is known to homodimerize with a strong dimer interface, we investigated the binding behavior of the isolated DBDs to different REs using electrophoretic migration, multi-angle static laser light scattering (MALLS, non-denaturing mass spectrometry, and nuclear magnetic resonance. In contrast to ER DBD, ERR DBD binds as a monomer to EREs (IR3, such as the tff1 ERE-IR3, but we identified a DNA sequence composed of an extended half-site embedded within an IR3 element (embedded ERRE/IR3, where stable dimer binding is observed. Using a series of chimera and mutant DNA sequences of ERREs and IR3 REs, we have found the key determinants for the binding of ERR DBD as a dimer. Our results suggest that the sequence-directed DNA shape is more important than the exact nucleotide sequence for the binding of ERR DBD to DNA as a dimer. Our work underlines the importance of the shape-driven DNA readout mechanisms based on minor groove recognition and electrostatic potential. These conclusions may apply not only to ERR but also to other members of the SHR family, such as androgen or glucocorticoid, for which a strong well-conserved half
Ahlberg, Johan; Lendaro, Eva; Hermansson, Liselotte; Håkansson, Bo; Ortiz-Catalan, Max
The functionality of upper limb prostheses can be improved by intuitive control strategies that use bioelectric signals measured at the stump level. One such strategy is the decoding of motor volition via myoelectric pattern recognition (MPR), which has shown promising results in controlled environments and more recently in clinical practice. Moreover, not much has been reported about daily life implementation and real-time accuracy of these decoding algorithms. This paper introduces an alternative approach in which MPR allows intuitive control of four different grips and open/close in a multifunctional prosthetic hand. We conducted a clinical proof-of-concept in activities of daily life by constructing a self-contained, MPR-controlled, transradial prosthetic system provided with a novel user interface meant to log errors during real-time operation. The system was used for five days by a unilateral dysmelia subject whose hand had never developed, and who nevertheless learned to generate patterns of myoelectric activity, reported as intuitive, for multi-functional prosthetic control. The subject was instructed to manually log errors when they occurred via the user interface mounted on the prosthesis. This allowed the collection of information about prosthesis usage and real-time classification accuracy. The assessment of capacity for myoelectric control test was used to compare the proposed approach to the conventional prosthetic control approach, direct control. Regarding the MPR approach, the subject reported a more intuitive control when selecting the different grips, but also a higher uncertainty during proportional continuous movements. This paper represents an alternative to the conventional use of MPR, and this alternative may be particularly suitable for a certain type of amputee patients. Moreover, it represents a further validation of MPR with dysmelia cases. PMID:29637030
Xia, Ling-yun; Leng, Wei-dong; Mao, Min; Yang, Guo-biao; Xiang, Yong-gang; Chen, Xin-mei
To observe the formation of canal aberrations in S-shaped root canals prepared by every file of hand-used ProTaper. Fifteen S-shaped simulated resin root canals were selected. Each root canal was prepared by every file of hand-used ProTaper following the manufacturer instruction. The images of canals prepared by S1, S2, F1, F2 and F3 were taken and stored, which were divided into group S1, S2, F1, F2 and F3. One image of canal unprepared was superposed with the images of the same root canal in these five groups respectively to observe the types and number of canal aberrations, which included unprepared area, danger zone, ledge, elbow, zip and perforation. SPSS12.0 software pakage was used for Fisher's exact probabilities in 2x2 table. Unprepared area decreased following preparation by every file of ProTaper, but it still existed when the canal preparation was finished. The incidence of danger zone, elbow and zip in group F1 was 15/15, 11/15, 4/15, respectively, which was significantly higher than that in group S2(2/15,0,0) (PProTaper.The presence of unprepared area suggests that it is essential to rinse canal abundantly during complicated canal preparation and canal antisepsis after preparation.
Aguiar, Carlos M; Câmara, Andréa C
This study evaluated, by means of the radiography examination, the occurrence of deviations in the apical third of root canals shaped with hand and rotary instruments. Sixty mandibular human molars were divided into three groups. The root canals in group 1 were instrumented with ProTaper (Dentsply/Maillefer, Ballaigues, Switzerland) for hand use, group 2 with ProTaper and group 3 with RaCe. The images obtained by double superimposition of the pre- and postoperative radiographs were evaluated by two endodontists with the aid of a magnifier-viewer and a fivefold magnifier. Statistical analysis was performed using the Fisher-Freeman-Halton. The instrumentation using the ProTaper for hand use showed 25% of the canals with a deviation in the apical third, as did the ProTaper, while the corresponding figure for the RaCe (FKG Dentaire, La-Chaux-de-Fonds, Switzerland) was 20%, but these results were not statistically significant. There was no correlation between the occurrence of deviations in the apical third and the systems used.
Megherbi, Dalila B.; Lodhi, S. M.; Boulenouar, A. J.
This work is in the field of automated document processing. This work addresses the problem of representation and recognition of Urdu characters using Fourier representation and a Neural Network architecture. In particular, we show that a two-stage Neural Network scheme is used here to make classification of 36 Urdu characters into seven sub-classes namely subclasses characterized by seven proposed and defined fuzzy features specifically related to Urdu characters. We show that here Fourier Descriptors and Neural Network provide a remarkably simple way to draw definite conclusions from vague, ambiguous, noisy or imprecise information. In particular, we illustrate the concept of interest regions and describe a framing method that provides a way to make the proposed technique for Urdu characters recognition robust and invariant to scaling and translation. We also show that a given character rotation is dealt with by using the Hotelling transform. This transform is based upon the eigenvalue decomposition of the covariance matrix of an image, providing a method of determining the orientation of the major axis of an object within an image. Finally experimental results are presented to show the power and robustness of the proposed two-stage Neural Network based technique for Urdu character recognition, its fault tolerance, and high recognition accuracy.
provide efficiency and effectively manufacture or inventory items. The industries that benefit from Cognex technology are automotive, food and beverage ...recognition tedmology, Tedmology Readiness Level, PAGES Cost Benefit Analysis, Tedmology Commercialization, Technology Transition 139 16. PRICE CODE 17...Technology Development & Transition Strategy Guidebook xvii UD Ultimate Disposal U.S. United States USAF United States Air Force xviii THIS
Fong, Simon; Zhuang, Yan; Fister, Iztok; Fister, Iztok
A novel hand biometric authentication method based on measurements of the user's stationary hand gesture of hand sign language is proposed. The measurement of hand gestures could be sequentially acquired by a low-cost video camera. There could possibly be another level of contextual information, associated with these hand signs to be used in biometric authentication. As an analogue, instead of typing a password 'iloveu' in text which is relatively vulnerable over a communication network, a signer can encode a biometric password using a sequence of hand signs, 'i' , 'l' , 'o' , 'v' , 'e' , and 'u'. Subsequently the features from the hand gesture images are extracted which are integrally fuzzy in nature, to be recognized by a classification model for telling if this signer is who he claimed himself to be, by examining over his hand shape and the postures in doing those signs. It is believed that everybody has certain slight but unique behavioral characteristics in sign language, so are the different hand shape compositions. Simple and efficient image processing algorithms are used in hand sign recognition, including intensity profiling, color histogram and dimensionality analysis, coupled with several popular machine learning algorithms. Computer simulation is conducted for investigating the efficacy of this novel biometric authentication model which shows up to 93.75% recognition accuracy.
Ana L. Ibáñez
Full Text Available Fish scale shape was used to identify geographic variants among Lutjanidae (Lutjanus argentiventris, L. guttatus and L. peru. Specimens were collected from three different geographic areas, north to south of the tropical Pacific coast of Mexico: Puerto Vallarta (PV, Manzanillo (MA and Caleta de Campos (CC. Configuration of landmark coordinates of fish scales were scaled, translated and rotated using generalized procrustes analysis, followed by principal components analysis of resulting shape coordinates. Principal component scores were submitted to cross-validated discriminant analysis to determine the efficacy of scale landmarks for discrimination by geographic variants. This was done with shape and form (shape plus size. PV and MA were recognized as one population different from the CC sampling area. Using only shape (without size, identification rates predicted geographic variant membership much better than chance (91.3%, 70.6% and 85.4% for L. argentiventris, L. guttatus and L. peru, respectively, and taking size into account, classification is somewhat improved (90.6%, 80.1% and 87.5% for L. argentiventris, L. guttatus and L. peru, respectively. Consistency of the two populations for the three species shows non-fortuitous events. Population discrimination confirmed previous genetic studies that show a zoogeographic barrier between the North Equatorial Current and the California Current. The method is non-destructive, fast and less expensive than genetic analysis, thus allowing screening of many individuals for traceability of fish.
Balsamo, Maddalena; Trojano, Luigi; Giamundo, Arcangelo; Grossi, Dario
We report a patient with a hemorrhagic lesion encroaching upon the posterior third of the corpus callosum but sparing the splenium. She showed marked difficulties in recognizing objects and shapes perceived through her left hand, while she could appreciate elementary sensorial features of items tactually presented to the same hand flawlessly. This picture, corresponding to classical descriptions of unilateral associative tactile agnosia, was associated with finger agnosia of the left hand. This very unusual case report can be interpreted as an instance of disconnection syndrome, and allows a discussion of mechanisms involved in tactile object recognition.
Miyagawa, Masamichi; Ichinose, Wataru; Yamaguchi, Masahiko
Chiral silica nanoparticles (70 nm) grafted with (P)-helicene recognized the molecular shape of double helix and random coil (P)-ethynylhelicene oligomers in solution. A mixture of the (P)-nanoparticles and double helix precipitated much faster than a mixture of the (P)-nanoparticles and random coil, and the precipitate contained only the double helix. The mixture of the (P)-nanoparticles and (P)-ethynylhelicene pentamer reversibly dispersed in trifluoromethylbenzene upon heating at 70 °C and precipitated upon cooling at 25 °C. When a 10:90 equilibrium mixture of the double helix and random coil in solution was treated with the (P)-nanoparticles, the double helix was precipitated in 53% yield and was accompanied by equilibrium shift. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
John F. McEvoy
Full Text Available The use of unmanned aerial vehicles (UAVs for ecological research has grown rapidly in recent years, but few studies have assessed the disturbance impacts of these tools on focal subjects, particularly when observing easily disturbed species such as waterfowl. In this study we assessed the level of disturbance that a range of UAV shapes and sizes had on free-living, non-breeding waterfowl surveyed in two sites in eastern Australia between March and May 2015, as well as the capability of airborne digital imaging systems to provide adequate resolution for unambiguous species identification of these taxa. We found little or no obvious disturbance effects on wild, mixed-species flocks of waterfowl when UAVs were flown at least 60m above the water level (fixed wing models or 40m above individuals (multirotor models. Disturbance in the form of swimming away from the UAV through to leaving the water surface and flying away from the UAV was visible at lower altitudes and when fixed-wing UAVs either approached subjects directly or rapidly changed altitude and/or direction near animals. Using tangential approach flight paths that did not cause disturbance, commercially available onboard optical equipment was able to capture images of sufficient quality to identify waterfowl and even much smaller taxa such as swallows. Our results show that with proper planning of take-off and landing sites, flight paths and careful UAV model selection, UAVs can provide an excellent tool for accurately surveying wild waterfowl populations and provide archival data with fewer logistical issues than traditional methods such as manned aerial surveys.
Choi, Junyeong; Park, Jungsik; Park, Hanhoon; Park, Jong-Il
The performance of mobile phones has rapidly improved, and they are emerging as a powerful platform. In many vision-based applications, human hands play a key role in natural interaction. However, relatively little attention has been paid to the interaction between human hands and the mobile phone. Thus, we propose a vision- and hand gesture-based interface in which the user holds a mobile phone in one hand but sees the other hand's palm through a built-in camera. The virtual contents are faithfully rendered on the user's palm through palm pose estimation, and reaction with hand and finger movements is achieved that is recognized by hand shape recognition. Since the proposed interface is based on hand gestures familiar to humans and does not require any additional sensors or markers, the user can freely interact with virtual contents anytime and anywhere without any training. We demonstrate that the proposed interface works at over 15 fps on a commercial mobile phone with a 1.2-GHz dual core processor and 1 GB RAM.
A method for recognizing both the three-dimensional object shapes and their sizes by grasping them with an antropomorphic five-finger artificial hand is described. The hand is equipped with position sensing elements in the joints of the fingers and with a tactile transducer net on the palm surface. The linguistic method uses formal grammars and languages for the pattern description. The recognition is hierarchically arranged, every level being different from the others by a formal language which has been used. On every level the pattern description is generated and verified from the symmetrical and semantical points of view. The results of the implementation of the recognition of cones, pyramides, spheres, prisms and cylinders are presented and discussed. 8 references.
Miguel A. Ferrer
Full Text Available Personal recognition through hand-based biometrics has attracted the interest of many researchers in the last twenty years. A significant number of proposals based on different procedures and acquisition devices have been published in the literature. However, comparisons between devices and their interoperability have not been thoroughly studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric schemes. The experiments were conducted on a database made up of 8,320 hand images acquired from six different hand biometric schemes, including a flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices. Acquisitions on both sides of the hand were included. Our experiment includes four feature extraction methods which determine the best performance among the different scenarios for two of the most popular hand biometrics: hand shape and palm print. We propose smoothing techniques at the image and feature levels to reduce interdevice variability. Results suggest that comparative hand shape offers better performance in terms of interoperability than palm prints, but palm prints can be more effective when using similar sensors.
Morales, Aythami; González, Ester; Ferrer, Miguel A
Personal recognition through hand-based biometrics has attracted the interest of many researchers in the last twenty years. A significant number of proposals based on different procedures and acquisition devices have been published in the literature. However, comparisons between devices and their interoperability have not been thoroughly studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric schemes. The experiments were conducted on a database made up of 8,320 hand images acquired from six different hand biometric schemes, including a flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices. Acquisitions on both sides of the hand were included. Our experiment includes four feature extraction methods which determine the best performance among the different scenarios for two of the most popular hand biometrics: hand shape and palm print. We propose smoothing techniques at the image and feature levels to reduce interdevice variability. Results suggest that comparative hand shape offers better performance in terms of interoperability than palm prints, but palm prints can be more effective when using similar sensors.
Morales, Aythami; González, Ester; Ferrer, Miguel A.
Personal recognition through hand-based biometrics has attracted the interest of many researchers in the last twenty years. A significant number of proposals based on different procedures and acquisition devices have been published in the literature. However, comparisons between devices and their interoperability have not been thoroughly studied. This paper tries to fill this gap by proposing procedures to improve the interoperability among different hand biometric schemes. The experiments were conducted on a database made up of 8,320 hand images acquired from six different hand biometric schemes, including a flat scanner, webcams at different wavelengths, high quality cameras, and contactless devices. Acquisitions on both sides of the hand were included. Our experiment includes four feature extraction methods which determine the best performance among the different scenarios for two of the most popular hand biometrics: hand shape and palm print. We propose smoothing techniques at the image and feature levels to reduce interdevice variability. Results suggest that comparative hand shape offers better performance in terms of interoperability than palm prints, but palm prints can be more effective when using similar sensors. PMID:22438714
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Full Text Available OBJETIVOS: Assim como a imagética motora, o reconhecimento de partes do corpo aciona representações somatosensoriais específicas. Essas representações são ativadas implicitamente para comparar o corpo com o estímulo. No presente estudo, investigou-se a influência da informação proprioceptiva da postura no reconhecimento de partes do corpo (mãos e propõe-se a utilização dessa tarefa na reabilitação de pacientes neurológicos. MATERIAIS E MÉTODOS: Dez voluntários destros participaram do experimento. A tarefa era reconhecer a lateralidade de figuras da mão apresentada, em várias perspectivas e em vários ângulos de orientação. Para a figura da mão direita, o voluntário pressionava a tecla direita e para a figura da mão esquerda, a tecla esquerda. Os voluntários realizavam duas sessões: uma com as mãos na postura prona e outra com as mãos na postura supina. RESULTADOS: Os tempos de reação manual (TRM eram maiores para as vistas e orientações, nas quais é difícil realizar o movimento real, mostrando que durante a tarefa, existe um acionamento de representações motoras para comparar o corpo com o estímulo. Além disso, existe uma influência da postura do sujeito em vistas e ângulos específicos. CONCLUSÕES: Estes resultados mostram que representações motoras são ativadas para comparar o corpo com o estímulo e que a postura da mão influencia esta ressonância entre estímulo e parte do corpo.OBJECTIVE: Recognition of body parts activates specific somatosensory representations in a way that is similar to motor imagery. These representations are implicitly activated to compare the body with the stimulus. In the present study, we investigate the influence of proprioceptive information relating to body posture on the recognition of body parts (hands. It proposes that this task could be used for rehabilitation of neurological patients. METHODS: Ten right-handed volunteers participated in this experiment. The
Halim, Zahid; Abbas, Ghulam
Sign language provides hearing and speech impaired individuals with an interface to communicate with other members of the society. Unfortunately, sign language is not understood by most of the common people. For this, a gadget based on image processing and pattern recognition can provide with a vital aid for detecting and translating sign language into a vocal language. This work presents a system for detecting and understanding the sign language gestures by a custom built software tool and later translating the gesture into a vocal language. For the purpose of recognizing a particular gesture, the system employs a Dynamic Time Warping (DTW) algorithm and an off-the-shelf software tool is employed for vocal language generation. Microsoft(®) Kinect is the primary tool used to capture video stream of a user. The proposed method is capable of successfully detecting gestures stored in the dictionary with an accuracy of 91%. The proposed system has the ability to define and add custom made gestures. Based on an experiment in which 10 individuals with impairments used the system to communicate with 5 people with no disability, 87% agreed that the system was useful.
Hugo Cezar Palhares Ferreira
Full Text Available Abstract The binding of information in visual short-term memory may occur incidentally when irrelevant information for the task at hand is stored together with relevant information. We investigated the process of the incidental conjunction of color and shape (Exp1 and its potential association with the selection of relevant information to the memory task (Exp2. The results in Exp1 show that color and shape are incidentally and asymmetrically conjugated: color interferes with the recognition of shape; however, shape does not interfere with the recognition of color. In Exp2, we investigated whether an increase in perceptual load would eliminate the processing of irrelevant information. The results of this experiment show that even with a high perceptual load, the incidental conjunction is not affected, and color remains to interfere with shape recognition, suggesting that the incidental conjunction is an automatic process.
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Minagawa, Akihiro; Fan, Wei; Katsuyama, Yutaka; Takebe, Hiroaki; Ozawa, Noriaki; Hotta, Yoshinobu; Sun, Jun
In recent years, various gesture recognition systems have been studied for use in television and video games. In such systems, motion areas ranging from 1 to 3 meters deep have been evaluated. However, with the burgeoning popularity of small mobile displays, gesture recognition systems capable of operating at much shorter ranges have become necessary. The problems related to such systems are exacerbated by the fact that the camera's field of view is unknown to the user during operation, which imposes several restrictions on his/her actions. To overcome the restrictions generated from such mobile camera devices, and to create a more flexible gesture recognition interface, we propose a hybrid hand gesture system, in which two types of gesture recognition modules are prepared and with which the most appropriate recognition module is selected by a dedicated switching module. The two recognition modules of this system are shape analysis using a boosting approach (detection-based approach) and motion analysis using image frame differences (motion-based approach)(for example, see). We evaluated this system using sample users and classified the resulting errors into three categories: errors that depend on the recognition module, errors caused by incorrect module identification, and errors resulting from user actions. In this paper, we show the results of our investigations and explain the problems related to short-range gesture recognition systems.
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Solís, José F.; Toxqui, Carina; Padilla, Alfonso; Santiago, César
A frame work for static sign language recognition using descriptors which represents 2D images in 1D data and artificial neural networks is presented in this work. The 1D descriptors were computed by two methods, first one consists in a correlation rotational operator.1 and second is based on contour analysis of hand shape. One of the main problems in sign language recognition is segmentation; most of papers report a special color in gloves or background for hand shape analysis. In order to avoid the use of gloves or special clothing, a thermal imaging camera was used to capture images. Static signs were picked up from 1 to 9 digits of American Sign Language, a multilayer perceptron reached 100% recognition with cross-validation.
Hand osteoarthritis (OA) is a common chronic disorder causing pain and limitation of mobility of affected joints. The prevalence of hand OA increases with age and more often affects females. Clinical signs obviously do not correlate with radiographic findings - symptomatic hand OA affects approximately 26 % of adult subjects, but radiographic changes can be found in up to two thirds of females and half of males older than 55 years.Disease course differ among individual patients. Hand OA is a heterogeneous disease. Nodal hand OA is the most common subtype affecting interphalangeal joints, thumb base OA affects first carpometacarpal joint. Erosive OA represents a specific subtype of hand OA, which is associated with joint inflammation, more pain, functional limitation and erosive findings on radiographs.Treatment of OA is limited. Analgesics and nonsteroidal anti-inflammatory drugs are the only agents reducing symptoms. New insights into the pathogenesis of disease should contribute to the development of novel effective treatment of hand OA.
Cavalli, Fabio; Lusnig, Luca; Trentin, Edmondo
Sex determination on skeletal remains is one of the most important diagnosis in forensic cases and in demographic studies on ancient populations. Our purpose is to realize an automatic operator-independent method to determine the sex from the bone shape and to test an intelligent, automatic pattern recognition system in an anthropological domain. Our multiple-classifier system is based exclusively on the morphological variants of a curve that represents the sagittal profile of the calvarium, modeled via artificial neural networks, and yields an accuracy higher than 80 %. The application of this system to other bone profiles is expected to further improve the sensibility of the methodology.
Full Text Available Objectives The purpose of this study was to determine the optimal master apical file size with minimal transportation and optimal efficiency in removing infected dentin. We evaluated the transportation of the canal center and the change in untouched areas after sequential preparation with a #25 to #40 file using 3 different instruments: stainless steel K-type (SS K-file hand file, ProFile and LightSpeed using microcomputed tomography (MCT. Materials and Methods Thirty extracted human mandibular molars with separated orifices and apical foramens on mesial canals were used. Teeth were randomly divided into three groups: SS K-file, Profile, LightSpeed and the root canals were instrumented using corresponding instruments from #20 to #40. All teeth were scanned with MCT before and after instrumentation. Cross section images were used to evaluate canal transportation and untouched area at 1- , 2- , 3- , and 5- mm level from the apex. Data were statistically analyzed according to' repeated nested design'and Mann-Whitney test (p = 0.05. Results In SS K-file group, canal transportation was significantly increased over #30 instrument. In the ProFile group, canal transportation was significantly increased after preparation with the #40 instrument at the 1- and 2- mm levels. LightSpeed group showed better centering ability than ProFile group after preparation with the #40 instrument at the 1 and 2 mm levels. Conclusions SS K-file, Profile, and LightSpeed showed differences in the degree of apical transportation depending on the size of the master apical file.
Full Text Available Sign language is a visual language used by deaf people. One difficulty of sign language recognition is that sign instances of vary in both motion and shape in three-dimensional (3D space. In this research, we use 3D depth information from hand motions, generated from Microsoft’s Kinect sensor and apply a hierarchical conditional random field (CRF that recognizes hand signs from the hand motions. The proposed method uses a hierarchical CRF to detect candidate segments of signs using hand motions, and then a BoostMap embedding method to verify the hand shapes of the segmented signs. Experiments demonstrated that the proposed method could recognize signs from signed sentence data at a rate of 90.4%.
The Omni-Hand was developed by Ross-Hime Designs, Inc. for Marshall Space Flight Center (MSFC) under a Small Business Innovation Research (SBIR) contract. The multiple digit hand has an opposable thumb and a flexible wrist. Electric muscles called Minnacs power wrist joints and the interchangeable digits. Two hands have been delivered to NASA for evaluation for potential use on space missions and the unit is commercially available for applications like hazardous materials handling and manufacturing automation. Previous SBIR contracts resulted in the Omni-Wrist and Omni-Wrist II robotic systems, which are commercially available for spray painting, sealing, ultrasonic testing, as well as other uses.
Santemiz, P.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; van den Biggelaar, Olivier
As a widely used biometrics, face recognition has many advantages such as being non-intrusive, natural and passive. On the other hand, in real-life scenarios with uncontrolled environment, pose variation up to side-view positions makes face recognition a challenging work. In this paper we discuss
Automated Defect Recognition as a Critical Element of a Three Dimensional X-ray Computed Tomography Imaging-Based Smart Non-Destructive Testing Technique in Additive Manufacturing of Near Net-Shape Parts
Full Text Available In this paper, a state of the art automated defect recognition (ADR system is presented that was developed specifically for Non-Destructive Testing (NDT of powder metallurgy (PM parts using three dimensional X-ray Computed Tomography (CT imaging, towards enabling online quality assurance and enhanced integrity confidence. PM parts exhibit typical defects such as microscopic cracks, porosity, and voids, internal to components that without an effective detection system, limit the growth of industrial applications. Compared to typical testing methods (e.g., destructive such as metallography that is based on sampling, cutting, and polishing of parts, CT provides full coverage of defect detection. This paper establishes the importance and advantages of an automated NDT system for the PM industry applications with particular emphasis on image processing procedures for defect recognition. Moreover, the article describes how to establish a reference library based on real 3D X-ray CT images of net-shape parts. The paper follows the development of the ADR system from processing 2D image slices of a measured 3D X-ray image to processing the complete 3D X-ray image as a whole. The introduced technique is successfully integrated into an automated in-line quality control system highly sought by major industry sectors in Oil and Gas, Automotive, and Aerospace.
Pattern recognition is a scientific discipline that is becoming increasingly important in the age of automation and information handling and retrieval. Patter Recognition, 2e covers the entire spectrum of pattern recognition applications, from image analysis to speech recognition and communications. This book presents cutting-edge material on neural networks, - a set of linked microprocessors that can form associations and uses pattern recognition to ""learn"" -and enhances student motivation by approaching pattern recognition from the designer's point of view. A direct result of more than 10
Ibler, K.S.; Jemec, G.B.E.; Flyvholm, M.-A.
Background. Healthcare workers are at increased risk of developing hand eczema. Objectives. To investigate the prevalence and severity of self-reported hand eczema, and to relate the findings to demographic data, occupation, medical speciality, wards, shifts, and working hours. Patients/materials......Background. Healthcare workers are at increased risk of developing hand eczema. Objectives. To investigate the prevalence and severity of self-reported hand eczema, and to relate the findings to demographic data, occupation, medical speciality, wards, shifts, and working hours. Patients...... dermatitis, younger age, male sex (male doctors), and working hours. Eighty nine per cent of subjects reported mild/moderate lesions. Atopic dermatitis was the only factor significantly related to severity. Sick leave was reported by 8% of subjects, and notification to the authorities by 12%. Conclusions...... or severity, but cultural differences between professions with respect to coping with the eczema were significant. Atopic dermatitis was related to increased prevalence and severity, and preventive efforts should be made for healthcare workers with atopic dermatitis....
Full Text Available Background and Aim: Osteoblastoma is one of the rarest primary bone tumors. Although, small bones of the hands and feet are the third most common location for this tumor, the hand involvement is very rare and few case observations were published in the English-language literature. Materials and Methods: In this study, we report five cases of benign osteoblastoma of the hand, 3 in metacarpals and two in phalanxes. The clinical feature is not specific. The severe nocturnal, salicylate-responsive pain is not present in patients with osteoblastoma. The pain is dull, persistent and less localized. The clinical course is usually long and there is often symptoms for months before medical attention are sought. Swelling is a more persistent finding in osteoblastoma of the hand that we found in all of our patients. The radiologic findings are indistinctive, so preoperative diagnosis based on X-ray appearance is difficult. In all of our 5 cases, we fail to consider osteoblastoma as primary diagnosis. Pathologically, osteoblastoma consisting of a well-vascularized connective tissue stroma in which there is active production of osteoid and primitive woven bone. Treatment depends on the stage and localization of the tumor. Curettage and bone grafting is sufficient in stage 1 or stage 2, but in stage 3 wide resection is necessary for prevention of recurrence. Osteosarcoma is the most important differential diagnosis that may lead to inappropriate operation.
Pantic, Maja; Li, S.; Jain, A.
Facial expression recognition is a process performed by humans or computers, which consists of: 1. Locating faces in the scene (e.g., in an image; this step is also referred to as face detection), 2. Extracting facial features from the detected face region (e.g., detecting the shape of facial
Craciunescu, Razvan; Mihovska, Albena Dimitrova; Kyriazakos, Sofoklis
Gesture recognition is a topic in computer science and language technology with the goal of interpreting human gestures via mathematical algorithms. Gestures can originate from any bodily motion or state but commonly originate from the face or hand. Current research focus includes on the emotion...... recognition from the face and hand gesture recognition. Gesture recognition enables humans to communicate with the machine and interact naturally without any mechanical devices. This paper investigates the possibility to use non-audio/video sensors in order to design a low-cost gesture recognition device...
Eede, M. van; Macrini, D.; Telea, A.; Sminchisescu, C.; Dickinson, S.
Skeletal representations of 2-D shape, including shock graphs, have become increasingly popular for shape matching and object recognition. However, it is well known that skeletal structure can be unstable under minor boundary deformation, part articulation, and minor shape deformation (due to, for
Full Text Available Unconstrained hand detection in still images plays an important role in many hand-related vision problems, for example, hand tracking, gesture analysis, human action recognition and human-machine interaction, and sign language recognition. Although hand detection has been extensively studied for decades, it is still a challenging task with many problems to be tackled. The contributing factors for this complexity include heavy occlusion, low resolution, varying illumination conditions, different hand gestures, and the complex interactions between hands and objects or other hands. In this paper, we propose a multiscale deep learning model for unconstrained hand detection in still images. Deep learning models, and deep convolutional neural networks (CNNs in particular, have achieved state-of-the-art performances in many vision benchmarks. Developed from the region-based CNN (R-CNN model, we propose a hand detection scheme based on candidate regions generated by a generic region proposal algorithm, followed by multiscale information fusion from the popular VGG16 model. Two benchmark datasets were applied to validate the proposed method, namely, the Oxford Hand Detection Dataset and the VIVA Hand Detection Challenge. We achieved state-of-the-art results on the Oxford Hand Detection Dataset and had satisfactory performance in the VIVA Hand Detection Challenge.
Zhang, Zonghua; Huang, Shujun; Xu, Yongjia; Chen, Chao; Zhao, Yan; Gao, Nan; Xiao, Yanjun
Palmprint and hand shape, as two kinds of important biometric characteristics, have been widely studied and applied to human identity recognition. The existing research is based mainly on 2D images, which lose the third-dimensional information. The biological features extracted from 2D images are distorted by pressure and rolling, so the subsequent feature matching and recognition are inaccurate. This paper presents a method to acquire accurate 3D shapes of palmprint and hand by projecting full-field composite color sinusoidal fringe patterns and the corresponding color texture information. A 3D imaging system is designed to capture and process the full-field composite color fringe patterns on hand surface. Composite color fringe patterns having the optimum three fringe numbers are generated by software and projected onto the surface of human hand by a digital light processing projector. From another viewpoint, a color CCD camera captures the deformed fringe patterns and saves them for postprocessing. After compensating for the cross talk and chromatic aberration between color channels, three fringe patterns are extracted from three color channels of a captured composite color image. Wrapped phase information can be calculated from the sinusoidal fringe patterns with high precision. At the same time, the absolute phase of each pixel is determined by the optimum three-fringe selection method. After building up the relationship between absolute phase map and 3D shape data, the 3D palmprint and hand are obtained. Color texture information can be directly captured or demodulated from the captured composite fringe pattern images. Experimental results show that the proposed method and system can yield accurate 3D shape and color texture information of the palmprint and hand shape.
Full Text Available Automated person recognition (APR based on biometric signals addresses the process of automatically recognize a person according to his physiological traits (face, voice, iris, fingerprint, ear shape, body odor, electroencephalogram – EEG, electrocardiogram, or hand geometry, or behavioural patterns (gait, signature, hand-grip, lip movement. The paper aims at briefly presenting the current challenges for two specific non-cooperative biometric approaches, namely face and gait biometrics as well as approaches that consider combination of the two in the attempt of a more robust system for accurate APR, in the context of surveillance application. Open problems from both sides are also pointed out.
Full Text Available This paper presents a method of speech recognition by pattern recognition techniques. Learning consists in determining the unique characteristics of a word (cepstral coefficients by eliminating those characteristics that are different from one word to another. For learning and recognition, the system will build a dictionary of words by determining the characteristics of each word to be used in the recognition. Determining the characteristics of an audio signal consists in the following steps: noise removal, sampling it, applying Hamming window, switching to frequency domain through Fourier transform, calculating the magnitude spectrum, filtering data, determining cepstral coefficients.
Daniel B Vatterott
Full Text Available Because items near our hands are often more important than items far from our hands, the brain processes visual items near our hands differently than items far from our hands. Multiple experiments have attributed this processing difference to spatial attention, but the exact mechanism behind how spatial attention near our hands changes is still under investigation. The current experiments sought to differentiate between two of the proposed mechanisms: a prioritization of the space near the hands and a prolonged disengagement of spatial attention near the hands. To differentiate between these two accounts, we used the additional singleton paradigm in which observers searched for a shape singleton among homogenously shaped distractors. On half the trials, one of the distractors was a different color. Both the prioritization and disengagement accounts predict differently colored distractors near the hands will slow target responses more than differently colored distractors far from the hands, but the prioritization account also predicts faster responses to targets near the hands than far from the hands. The disengagement account does not make this prediction, because attention does not need to be disengaged when the target appears near the hand. We found support for the disengagement account: Salient distractors near the hands slowed responses more than those far from the hands, yet observers did not respond faster to targets near the hands.
Büyükbayrak, Hakan; Yanikoglu, Berrin; Erçil, Aytül
We describe a system for recognizing online, handwritten mathematical expressions. The system is designed with a user-interface for writing scientific articles, supporting the recognition of basic mathematical expressions as well as integrals, summations, matrices etc. A feed-forward neural network recognizes symbols which are assumed to be single-stroke and a recursive algorithm parses the expression by combining neural network output and the structure of the expression. Preliminary results show that writer-dependent recognition rates are very high (99.8%) while writer-independent symbol recognition rates are lower (75%). The interface associated with the proposed system integrates the built-in recognition capabilities of the Microsoft's Tablet PC API for recognizing textual input and supports conversion of hand-drawn figures into PNG format. This enables the user to enter text, mathematics and draw figures in a single interface. After recognition, all output is combined into one LATEX code and compiled into a PDF file.
Olsen, Søren I.
An approach to exemplar based recognition of visual shapes is presented. The shape information is described by attributed interest points (keys) detected by an end-stop operator. The attributes describe the statistics of lines and edges local to the interest point, the position of neighboring int...... interest points, and (in the training phase) a list of recognition names. Recognition is made by a simple voting procedure. Preliminary experiments indicate that the recognition is robust to noise, small deformations, background clutter and partial occlusion....
Full Text Available Abstract Background We systematically reviewed etiological factors of Kienböck’s disease (osteonecrosis of the lunate discussed in the literature in order to examine the justification for including Kienböck’s disease (KD in the European Listing of Occupational Diseases. Methods We searched the Ovid/Medline and the Cochrane Library for articles discussing the etiology of osteonecrosis of the lunate published since the first description of KD in 1910 and up until July 2012 in English, French or German. Literature was classified by the level of evidence presented, the etiopathological hypothesis discussed, and the author's conclusion about the role of the etiopathological hypothesis. The causal relationship between KD and hand-arm vibration was elucidated by the Bradford Hill criteria. Results A total of 220 references was found. Of the included 152 articles, 140 (92% reached the evidence level IV (case series. The four most frequently discussed factors were negative ulnar variance (n=72; 47%, primary arterial ischemia of the lunate (n=63; 41%, trauma (n=63; 41% and hand-arm vibration (n=53; 35%. The quality of the cohort studies on hand-arm vibration did not permit a meta-analysis to evaluate the strength of an association to KD. Evidence for the lack of consistency, plausibility and coherence of the 4 most frequently discussed etiopathologies was found. No evidence was found to support any of the nine Bradford Hill criteria for a causal relationship between KD and hand-arm vibration. Conclusions A systematic review of 220 articles on the etiopathology of KD and the application of the Bradford Hill criteria does not provide sufficient scientific evidence to confirm or refute a causal relationship between KD and hand-arm vibration. This currently suggests that, KD does not comply with the criteria of the International Labour Organization determining occupational diseases. However, research with a higher level of evidence is required to
Patel, Vrajeshri; Thukral, Poojita; Burns, Martin K; Florescu, Ionut; Chandramouli, Rajarathnam; Vinjamuri, Ramana
Recently, the need for more secure identity verification systems has driven researchers to explore other sources of biometrics. This includes iris patterns, palm print, hand geometry, facial recognition, and movement patterns (hand motion, gait, and eye movements). Identity verification systems may benefit from the complexity of human movement that integrates multiple levels of control (neural, muscular, and kinematic). Using principal component analysis, we extracted spatiotemporal hand synergies (movement synergies) from an object grasping dataset to explore their use as a potential biometric. These movement synergies are in the form of joint angular velocity profiles of 10 joints. We explored the effect of joint type, digit, number of objects, and grasp type. In its best configuration, movement synergies achieved an equal error rate of 8.19%. While movement synergies can be integrated into an identity verification system with motion capture ability, we also explored a camera-ready version of hand synergies-postural synergies. In this proof of concept system, postural synergies performed well, but only when specific postures were chosen. Based on these results, hand synergies show promise as a potential biometric that can be combined with other hand-based biometrics for improved security.
Full Text Available Recently, the need for more secure identity verification systems has driven researchers to explore other sources of biometrics. This includes iris patterns, palm print, hand geometry, facial recognition, and movement patterns (hand motion, gait, and eye movements. Identity verification systems may benefit from the complexity of human movement that integrates multiple levels of control (neural, muscular, and kinematic. Using principal component analysis, we extracted spatiotemporal hand synergies (movement synergies from an object grasping dataset to explore their use as a potential biometric. These movement synergies are in the form of joint angular velocity profiles of 10 joints. We explored the effect of joint type, digit, number of objects, and grasp type. In its best configuration, movement synergies achieved an equal error rate of 8.19%. While movement synergies can be integrated into an identity verification system with motion capture ability, we also explored a camera-ready version of hand synergies—postural synergies. In this proof of concept system, postural synergies performed well, but only when specific postures were chosen. Based on these results, hand synergies show promise as a potential biometric that can be combined with other hand-based biometrics for improved security.
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S.PON SANGEETHA; DR.M.KARNAN
The security plays an important role in any type of organization in today’s life. Iris recognition is one of the leading automatic biometric systems in the area of security which is used to identify the individual person. Biometric systems include fingerprints, facial features, voice recognition, hand geometry, handwriting, the eye retina and the most secured one presented in this paper, the iris recognition. Biometric systems has become very famous in security systems because it is not possi...
Veronelli, Laura; Ginex, Valeria; Dinacci, Daria; Cappa, Stefano F; Corbo, Massimo
Associative tactile agnosia (TA) is defined as the inability to associate information about object sensory properties derived through tactile modality with previously acquired knowledge about object identity. The impairment is often described after a lesion involving the parietal cortex (Caselli, 1997; Platz, 1996). We report the case of SA, a right-handed 61-year-old man affected by first ever right hemispheric hemorrhagic stroke. The neurological examination was normal, excluding major somaesthetic and motor impairment; a brain magnetic resonance imaging (MRI) confirmed the presence of a right subacute hemorrhagic lesion limited to the post-central and supra-marginal gyri. A comprehensive neuropsychological evaluation detected a selective inability to name objects when handled with the left hand in the absence of other cognitive deficits. A series of experiments were conducted in order to assess each stage of tactile recognition processing using the same stimulus sets: materials, 3D geometrical shapes, real objects and letters. SA and seven matched controls underwent the same experimental tasks during four sessions in consecutive days. Tactile discrimination, recognition, pantomime, drawing after haptic exploration out of vision and tactile-visual matching abilities were assessed. In addition, we looked for the presence of a supra-modal impairment of spatial perception and of specific difficulties in programming exploratory movements during recognition. Tactile discrimination was intact for all the stimuli tested. In contrast, SA was able neither to recognize nor to pantomime real objects manipulated with the left hand out of vision, while he identified them with the right hand without hesitations. Tactile-visual matching was intact. Furthermore, SA was able to grossly reproduce the global shape in drawings but failed to extract details of objects after left-hand manipulation, and he could not identify objects after looking at his own drawings. This case
Full Text Available Analysis of raw volume data generated from different scanning technologies faces a variety of challenges, related to search, pattern recognition, spatial understanding, quantitative estimation, and shape description. In a previous study, we found that the Volume Cracker (VC 3D interaction (3DI technique mitigated some of these problems, but this result was from a tethered glove-based system with users analyzing simulated data. Here, we redesigned the VC by using untethered bare-hand interaction with real volume datasets, with a broader aim of adoption of this technique in research labs. We developed symmetric and asymmetric interfaces for the Bare-Hand Volume Cracker (BHVC through design iterations with a biomechanics scientist. We evaluated our asymmetric BHVC technique against standard 2D and widely used 3D interaction techniques with experts analyzing scanned beetle datasets. We found that our BHVC design significantly outperformed the other two techniques. This study contributes a practical 3DI design for scientists, documents lessons learned while redesigning for bare-hand trackers, and provides evidence suggesting that 3D interaction could improve volume data analysis for a variety of visual analysis tasks. Our contribution is in the realm of 3D user interfaces tightly integrated with visualization, for improving the effectiveness of visual analysis of volume datasets. Based on our experience, we also provide some insights into hardware-agnostic principles for design of effective interaction techniques.
Cheng, Juan; Chen, Xun; Liu, Aiping; Peng, Hu
Sign language recognition (SLR) is an important communication tool between the deaf and the external world. It is highly necessary to develop a worldwide continuous and large-vocabulary-scale SLR system for practical usage. In this paper, we propose a novel phonology- and radical-coded Chinese SLR framework to demonstrate the feasibility of continuous SLR using accelerometer (ACC) and surface electromyography (sEMG) sensors. The continuous Chinese characters, consisting of coded sign gestures, are first segmented into active segments using EMG signals by means of moving average algorithm. Then, features of each component are extracted from both ACC and sEMG signals of active segments (i.e., palm orientation represented by the mean and variance of ACC signals, hand movement represented by the fixed-point ACC sequence, and hand shape represented by both the mean absolute value (MAV) and autoregressive model coefficients (ARs)). Afterwards, palm orientation is first classified, distinguishing "Palm Downward" sign gestures from "Palm Inward" ones. Only the "Palm Inward" gestures are sent for further hand movement and hand shape recognition by dynamic time warping (DTW) algorithm and hidden Markov models (HMM) respectively. Finally, component recognition results are integrated to identify one certain coded gesture. Experimental results demonstrate that the proposed SLR framework with a vocabulary scale of 223 characters can achieve an averaged recognition accuracy of 96.01% ± 0.83% for coded gesture recognition tasks and 92.73% ± 1.47% for character recognition tasks. Besides, it demonstrats that sEMG signals are rather consistent for a given hand shape independent of hand movements. Hence, the number of training samples will not be significantly increased when the vocabulary scale increases, since not only the number of the completely new proposed coded gestures is constant and limited, but also the transition movement which connects successive signs needs no
Hsu, Chih-Bin; Hao, Shu-Sheng; Lee, Jen-Chun
Biometric identification is an emerging technology that can solve security problems in our networked society. A reliable and robust personal verification approach using dorsal hand vein patterns is proposed in this paper. The characteristic of the approach needs less computational and memory requirements and has a higher recognition accuracy. In our work, the near-infrared charge-coupled device (CCD) camera is adopted as an input device for capturing dorsal hand vein images, it has the advantages of the low-cost and noncontact imaging. In the proposed approach, two finger-peaks are automatically selected as the datum points to define the region of interest (ROI) in the dorsal hand vein images. The modified two-directional two-dimensional principal component analysis, which performs an alternate two-dimensional PCA (2DPCA) in the column direction of images in the 2DPCA subspace, is proposed to exploit the correlation of vein features inside the ROI between images. The major advantage of the proposed method is that it requires fewer coefficients for efficient dorsal hand vein image representation and recognition. The experimental results on our large dorsal hand vein database show that the presented schema achieves promising performance (false reject rate: 0.97% and false acceptance rate: 0.05%) and is feasible for dorsal hand vein recognition.
Vivek Shrivastava; Navdeep Sharma
Optical Character Recognition deals in recognition and classification of characters from an image. For the recognition to be accurate, certain topological and geometrical properties are calculated, based on which a character is classified and recognized. Also, the Human psychology perceives characters by its overall shape and features such as strokes, curves, protrusions, enclosures etc. These properties, also called Features are extracted from the image by means of spatial pixel-...
Kam Ho Tin
Machines capable of automatic pattern recognition have many fascinating uses. Algorithms for supervised classification, where one infers a decision boundary from a set of training examples, are at the core of this capability. This book looks at data complexity and its role in shaping the theories and techniques in different disciplines
Mølgaard, Lasse Lohilahti; Jørgensen, Kasper Winther
Speaker recognition is basically divided into speaker identification and speaker verification. Verification is the task of automatically determining if a person really is the person he or she claims to be. This technology can be used as a biometric feature for verifying the identity of a person...
B. El Kessab
In this context we propose a data set for handwritten Tifinagh regions composed of 1600 image (100 Image for each region. The dataset can be used in one hand to test the efficiency of the Tifinagh region recognition system in extraction of characteristics significatives and the correct identification of each region in classification phase in the other hand.
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This book contains thirteen contributions from invited experts of international recognition addressing important issues in shape analysis in medical image analysis, including techniques for image segmentation, registration, modelling and classification, and applications in biology, as well as in cardiac, brain, spine, chest, lung and clinical practice. This volume treats topics such as, anatomic and functional shape representation and matching; shape-based medical image segmentation; shape registration; statistical shape analysis; shape deformation; shape-based abnormity detection; shape tracking and longitudinal shape analysis; machine learning for shape modeling and analysis; shape-based computer-aided-diagnosis; shape-based medical navigation; benchmark and validation of shape representation, analysis and modeling algorithms. This work will be of interest to researchers, students, and manufacturers in the fields of artificial intelligence, bioengineering, biomechanics, computational mechanics, computationa...
Yalachkov, Yavor; Kaiser, Jochen; Doehrmann, Oliver; Naumer, Marcus J
Visuo-haptic integration contributes essentially to object shape recognition. Although there has been a considerable advance in elucidating the neural underpinnings of multisensory perception, it is still unclear whether seeing an object and exploring it with the dominant hand elicits the same brain response as compared to the non-dominant hand. Using fMRI to measure brain activation in right-handed participants, we found that for both left- and right-hand stimulation the left lateral occipital complex (LOC) and anterior cerebellum (aCER) were involved in visuo-haptic integration of familiar objects. These two brain regions were then further investigated in another study, where unfamiliar, novel objects were presented to a different group of right-handers. Here the left LOC and aCER were more strongly activated by bimodal than unimodal stimuli only when the left but not the right hand was used. A direct comparison indicated that the multisensory gain of the fMRI activation was significantly higher for the left than the right hand. These findings are in line with the principle of "inverse effectiveness", implying that processing of bimodally presented stimuli is particularly enhanced when the unimodal stimuli are weak. This applies also when right-handed subjects see and simultaneously touch unfamiliar objects with their non-dominant left hand. Thus, the fMRI signal in the left LOC and aCER induced by visuo-haptic stimulation is dependent on which hand was employed for haptic exploration. Copyright © 2015 Elsevier B.V. All rights reserved.
Full Text Available Abstract Background Landmark based geometric morphometrics (GM allows the quantitative comparison of organismal shapes. When applied to systematics, it is able to score shape changes which often are undetectable by traditional morphological studies and even by classical morphometric approaches. It has thus become a fast and low cost candidate to identify cryptic species. Due to inherent mathematical properties, shape variables derived from one set of coordinates cannot be compared with shape variables derived from another set. Raw coordinates which produce these shape variables could be used for data exchange, however they contain measurement error. The latter may represent a significant obstacle when the objective is to distinguish very similar species. Results We show here that a single user derived dataset produces much less classification error than a multiple one. The question then becomes how to circumvent the lack of exchangeability of shape variables while preserving a single user dataset. A solution to this question could lead to the creation of a relatively fast and inexpensive systematic tool adapted for the recognition of cryptic species. Conclusions To preserve both exchangeability of shape and a single user derived dataset, our suggestion is to create a free access bank of reference images from which one can produce raw coordinates and use them for comparison with external specimens. Thus, we propose an alternative geometric descriptive system that separates 2-D data gathering and analyzes.
Human computer interaction (HCI) plays a vital role in bridging the 'Digital Divide', bringing people closer to consumer electronics control in the 'lounge'. Keyboards and mouse or remotes do alienate old and new generations alike from control interfaces. Hand Gesture Recognition systems bring hope of connecting people with machines in a natural way. This will lead to consumers being able to use their hands naturally to communicate with any electronic equipment in their 'lounge.' This monograph will include the state of the art hand gesture recognition approaches and how they evolved from their inception. The author would also detail his research in this area for the past 8 years and how the future might turn out to be using HCI. This monograph will serve as a valuable guide for researchers (who would endeavour into) in the world of HCI.
Chen, Q.; Dijkstra, J.; Vries, de B.
Object recognition plays a major role in human behaviour research in the built environment. Computer based object recognition techniques using images as input are challenging, but not an adequate representation of human vision. This paper reports on the differences in object shape recognition
Germine, Laura; Cashdollar, Nathan; Düzel, Emrah; Duchaine, Bradley
Studies of developmental deficits in face recognition, or developmental prosopagnosia, have shown that individuals who have not suffered brain damage can show face recognition impairments coupled with normal object recognition (Duchaine and Nakayama, 2005; Duchaine et al., 2006; Nunn et al., 2001). However, no developmental cases with the opposite dissociation - normal face recognition with impaired object recognition - have been reported. The existence of a case of non-face developmental visual agnosia would indicate that the development of normal face recognition mechanisms does not rely on the development of normal object recognition mechanisms. To see whether a developmental variant of non-face visual object agnosia exists, we conducted a series of web-based object and face recognition tests to screen for individuals showing object recognition memory impairments but not face recognition impairments. Through this screening process, we identified AW, an otherwise normal 19-year-old female, who was then tested in the lab on face and object recognition tests. AW's performance was impaired in within-class visual recognition memory across six different visual categories (guns, horses, scenes, tools, doors, and cars). In contrast, she scored normally on seven tests of face recognition, tests of memory for two other object categories (houses and glasses), and tests of recall memory for visual shapes. Testing confirmed that her impairment was not related to a general deficit in lower-level perception, object perception, basic-level recognition, or memory. AW's results provide the first neuropsychological evidence that recognition memory for non-face visual object categories can be selectively impaired in individuals without brain damage or other memory impairment. These results indicate that the development of recognition memory for faces does not depend on intact object recognition memory and provide further evidence for category-specific dissociations in visual
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... All Topics A-Z Videos Infographics Symptom Picker Anatomy Bones Joints Muscles Nerves Vessels Tendons About Hand Surgery What is ... Hand Therapist? Media Find a Hand Surgeon Home Anatomy ... hands, being composed of many types of tissue, including blood vessels, nerves, skin and skin-related tissues, bones, and muscles/tendons/ligaments, may show changes that reflect a ...
Laursen, Hilmar Dyrborg; Nielsen, Birgitte Lund
Som del af det internationale EU finansierede projekt Hand in Hand, der fokuserer på de såkaldte SEI-kompetencer (Social, Emotional, Intercultural), er dansk policy i relation til elevernes sociale, emotionelle og interkulturelle læring kortlagt i denne rapport. Der refereres bl.a. til "elevernes...
Brooks, Brian E.; Cooper, Eric E.
Three divided visual field experiments tested current hypotheses about the types of visual shape representation tasks that recruit the cognitive and neural mechanisms underlying face recognition. Experiment 1 found a right hemisphere advantage for subordinate but not basic-level face recognition. Experiment 2 found a right hemisphere advantage for…
Felzenszwalb, Pedro F.
We consider object detection using a generic model for natural shapes. A common approach for object recognition involves matching object models directly to images. Another approach involves building intermediate representations via a generic grouping processes. We argue that these two processes (model-based recognition and grouping) may use similar computational mechanisms. By defining a generic model for shapes we can use model-based techniques to implement a mid-level vision grouping process.
Karaçizmeli, Cengiz; Çakır, Gökçe; Tükel, Dilek
In this work, the mechatronic based robotic hand is controlled by the position data taken from the glove which has flex sensors mounted to capture finger bending of the human hand. The angular movement of human hand’s fingers are perceived and processed by a microcontroller, and the robotic hand is controlled by actuating servo motors. It has seen that robotic hand can simulate the movement of the human hand that put on the glove, during tests have done. This robotic hand can be used not only...
Matthew R Williams
Full Text Available The loss of a hand can greatly affect quality of life. A prosthetic device that can mimic normal hand function is very important to physical and mental recuperation after hand amputation, but the currently available prosthetics do not fully meet the needs of the amputee community. Most prosthetic hands are not dexterous enough to grasp a variety of shaped objects, and those that are tend to be heavy, leading to discomfort while wearing the device. In order to attempt to better simulate human hand function, a dexterous hand was developed that uses an over-actuated mechanism to form grasp shape using intrinsic joint mounted motors in addition to a finger tendon to produce large flexion force for a tight grip. This novel actuation method allows the hand to use small actuators for grip shape formation, and the tendon to produce high grip strength. The hand was capable of producing fingertip flexion force suitable for most activities of daily living. In addition, it was able to produce a range of grasp shapes with natural, independent finger motion, and appearance similar to that of a human hand. The hand also had a mass distribution more similar to a natural forearm and hand compared to contemporary prosthetics due to the more proximal location of the heavier components of the system. This paper describes the design of the hand and controller, as well as the test results.
Ji Eun eOh
Full Text Available Autophagy is an ancient biological process for maintaining cellular homeostasis by degradation of long-lived cytosolic proteins and organelles. Recent studies demonstrated that autophagy is availed by immune cells to regulate innate immunity. On the one hand, cells exert direct effector function by degrading intracellular pathogens; on the other hand, autophagy modulates pathogen recognition and downstream signaling for innate immune responses. Pathogen recognition via pattern recognition receptors induces autophagy. The function of phagocytic cells is enhanced by recruitment of autophagy-related proteins. Moreover, autophagy acts as a delivery system for viral replication complexes to migrate to the endosomal compartments where virus sensing occurs. In another case, key molecules of the autophagic pathway have been found to negatively regulate immune signaling, thus preventing aberrant activation of cytokine production and consequent immune responses. In this review, we focus on the recent advances in the role of autophagy in pathogen recognition and modulation of innate immune responses.
Full Text Available ... to promote or encourage adherence to CDC hand hygiene recommendations. It is a component of the Clean ... aims to address myths and misperceptions about hand hygiene and empower patients to play a role in ...
Full Text Available ... intended to promote or encourage adherence to CDC hand hygiene recommendations. It is a component of the Clean ... also aims to address myths and misperceptions about hand hygiene and empower patients to play a role in ...
... intended to promote or encourage adherence to CDC hand hygiene recommendations. It is a component of the Clean ... also aims to address myths and misperceptions about hand hygiene and empower patients to play a role in ...
... hand sanitizers might not remove harmful chemicals like pesticides and heavy metals from hands. Be cautious when ... Health Promotion Materials Fact Sheets Podcasts Posters Stickers Videos Web Features Training & Education Our Partners Publications, Data & ...
Yazaji, Eskandar Alex
Hand hygiene is one of the major players in preventing healthcare associated infections. However, healthcare workers compliance with hand hygiene continues to be a challenge. This article will address strategies to help improving hand hygiene compliance. Keywords: hand hygiene; healthcare associated infections; multidisciplinary program; system change; accountability; education; feedback(Published: 18 July 2011)Citation: Journal of Community Hospital Internal Medicine Perspectives 2011, 1: 72...
Fai Chen Chen
Full Text Available In the last few years, the number of projects studying the human hand from the robotic point of view has increased rapidly, due to the growing interest in academic and industrial applications. Nevertheless, the complexity of the human hand given its large number of degrees of freedom (DoF within a significantly reduced space requires an exhaustive analysis, before proposing any applications. The aim of this paper is to provide a complete summary of the kinematic and dynamic characteristics of the human hand as a preliminary step towards the development of hand devices such as prosthetic/robotic hands and exoskeletons imitating the human hand shape and functionality. A collection of data and constraints relevant to hand movements is presented, and the direct and inverse kinematics are solved for all the fingers as well as the dynamics; anthropometric data and dynamics equations allow performing simulations to understand the behavior of the finger.
Wei, Shengjing; Chen, Xiang; Yang, Xidong; Cao, Shuai; Zhang, Xu
Sign language recognition (SLR) can provide a helpful tool for the communication between the deaf and the external world. This paper proposed a component-based vocabulary extensible SLR framework using data from surface electromyographic (sEMG) sensors, accelerometers (ACC), and gyroscopes (GYRO). In this framework, a sign word was considered to be a combination of five common sign components, including hand shape, axis, orientation, rotation, and trajectory, and sign classification was implemented based on the recognition of five components. Especially, the proposed SLR framework consisted of two major parts. The first part was to obtain the component-based form of sign gestures and establish the code table of target sign gesture set using data from a reference subject. In the second part, which was designed for new users, component classifiers were trained using a training set suggested by the reference subject and the classification of unknown gestures was performed with a code matching method. Five subjects participated in this study and recognition experiments under different size of training sets were implemented on a target gesture set consisting of 110 frequently-used Chinese Sign Language (CSL) sign words. The experimental results demonstrated that the proposed framework can realize large-scale gesture set recognition with a small-scale training set. With the smallest training sets (containing about one-third gestures of the target gesture set) suggested by two reference subjects, (82.6 ± 13.2)% and (79.7 ± 13.4)% average recognition accuracy were obtained for 110 words respectively, and the average recognition accuracy climbed up to (88 ± 13.7)% and (86.3 ± 13.7)% when the training set included 50~60 gestures (about half of the target gesture set). The proposed framework can significantly reduce the user's training burden in large-scale gesture recognition, which will facilitate the implementation of a practical SLR system.
Full Text Available Sign language recognition (SLR can provide a helpful tool for the communication between the deaf and the external world. This paper proposed a component-based vocabulary extensible SLR framework using data from surface electromyographic (sEMG sensors, accelerometers (ACC, and gyroscopes (GYRO. In this framework, a sign word was considered to be a combination of five common sign components, including hand shape, axis, orientation, rotation, and trajectory, and sign classification was implemented based on the recognition of five components. Especially, the proposed SLR framework consisted of two major parts. The first part was to obtain the component-based form of sign gestures and establish the code table of target sign gesture set using data from a reference subject. In the second part, which was designed for new users, component classifiers were trained using a training set suggested by the reference subject and the classification of unknown gestures was performed with a code matching method. Five subjects participated in this study and recognition experiments under different size of training sets were implemented on a target gesture set consisting of 110 frequently-used Chinese Sign Language (CSL sign words. The experimental results demonstrated that the proposed framework can realize large-scale gesture set recognition with a small-scale training set. With the smallest training sets (containing about one-third gestures of the target gesture set suggested by two reference subjects, (82.6 ± 13.2% and (79.7 ± 13.4% average recognition accuracy were obtained for 110 words respectively, and the average recognition accuracy climbed up to (88 ± 13.7% and (86.3 ± 13.7% when the training set included 50~60 gestures (about half of the target gesture set. The proposed framework can significantly reduce the user’s training burden in large-scale gesture recognition, which will facilitate the implementation of a practical SLR system.
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Goldberg, Judith L
Performing proper hand hygiene and surgical hand antisepsis is essential to reducing the rates of health care-associated infections, including surgical site infections. The updated AORN "Guideline for hand hygiene" provides guidance on hand hygiene and surgical hand antisepsis, the wearing of fingernail polish and artificial nails, proper skin care to prevent dermatitis, the wearing of jewelry, hand hygiene product selection, and quality assurance and performance improvement considerations. This article focuses on key points of the guideline to help perioperative personnel make informed decisions about hand hygiene and surgical hand antisepsis. The key points address the necessity of keeping fingernails and skin healthy, not wearing jewelry on the hands or wrists in the perioperative area, properly performing hand hygiene and surgical hand antisepsis, and involving patients and visitors in hand hygiene initiatives. Perioperative RNs should review the complete guideline for additional information and for guidance when writing and updating policies and procedures. Copyright © 2017 AORN, Inc. Published by Elsevier Inc. All rights reserved.
Salisbury, Curt Michael; Dullea, Kevin J.
Technologies pertaining to a robotic hand are described herein. The robotic hand includes one or more fingers releasably attached to a robotic hand frame. The fingers can abduct and adduct as well as flex and tense. The fingers are releasably attached to the frame by magnets that allow for the fingers to detach from the frame when excess force is applied to the fingers.
Cao, Frédéric; Morel, Jean-Michel; Musé, Pablo; Sur, Frédéric
Recent years have seen dramatic progress in shape recognition algorithms applied to ever-growing image databases. They have been applied to image stitching, stereo vision, image mosaics, solid object recognition and video or web image retrieval. More fundamentally, the ability of humans and animals to detect and recognize shapes is one of the enigmas of perception. The book describes a complete method that starts from a query image and an image database and yields a list of the images in the database containing shapes present in the query image. A false alarm number is associated to each detection. Many experiments will show that familiar simple shapes or images can reliably be identified with false alarm numbers ranging from 10-5 to less than 10-300. Technically speaking, there are two main issues. The first is extracting invariant shape descriptors from digital images. The second is deciding whether two shape descriptors are identifiable as the same shape or not. A perceptual principle, the Helmholtz princi...
Raju, Chaitanya; Varadarajan, Karthik Mahesh; Krishnamurthi, Niyant; Xu, Shuli; Biederman, Irving; Kelley, Troy
We have developed a framework, Cognitive Object Recognition System (CORS), inspired by current neurocomputational models and psychophysical research in which multiple recognition algorithms (shape based geometric primitives, 'geons,' and non-geometric feature-based algorithms) are integrated to provide a comprehensive solution to object recognition and landmarking. Objects are defined as a combination of geons, corresponding to their simple parts, and the relations among the parts. However, those objects that are not easily decomposable into geons, such as bushes and trees, are recognized by CORS using "feature-based" algorithms. The unique interaction between these algorithms is a novel approach that combines the effectiveness of both algorithms and takes us closer to a generalized approach to object recognition. CORS allows recognition of objects through a larger range of poses using geometric primitives and performs well under heavy occlusion - about 35% of object surface is sufficient. Furthermore, geon composition of an object allows image understanding and reasoning even with novel objects. With reliable landmarking capability, the system improves vision-based robot navigation in GPS-denied environments. Feasibility of the CORS system was demonstrated with real stereo images captured from a Pioneer robot. The system can currently identify doors, door handles, staircases, trashcans and other relevant landmarks in the indoor environment.
Han, Yi; Wang, Guoyin; Yang, Yong; He, Kun
Human emotions could be expressed by many bio-symbols. Speech and facial expression are two of them. They are both regarded as emotional information which is playing an important role in human-computer interaction. Based on our previous studies on emotion recognition, an audiovisual emotion recognition system is developed and represented in this paper. The system is designed for real-time practice, and is guaranteed by some integrated modules. These modules include speech enhancement for eliminating noises, rapid face detection for locating face from background image, example based shape learning for facial feature alignment, and optical flow based tracking algorithm for facial feature tracking. It is known that irrelevant features and high dimensionality of the data can hurt the performance of classifier. Rough set-based feature selection is a good method for dimension reduction. So 13 speech features out of 37 ones and 10 facial features out of 33 ones are selected to represent emotional information, and 52 audiovisual features are selected due to the synchronization when speech and video fused together. The experiment results have demonstrated that this system performs well in real-time practice and has high recognition rate. Our results also show that the work in multimodules fused recognition will become the trend of emotion recognition in the future.
Carvalho, João; Sá, Vítor; Tenreiro de Magalhães, Sérgio; Santos, Henrique
Biometric systems are increasingly being used as a means for authentication to provide system security in modern technologies. The performance of a biometric system depends on the accuracy, the processing speed, the template size, and the time necessary for enrollment. While much research has focused on the first three factors, enrollment time has not received as much attention. In this work, we present the findings of our research focused upon studying user’s behavior when enrolling in...
Marcus, Beth A.; Churchill, Philip J.; Little, Arthur D.
The Dexterous Hand Master (DHM) system is designed to control dexterous robot hands such as the UTAH/MIT and Stanford/JPL hands. It is the first commercially available device which makes it possible to accurately and confortably track the complex motion of the human finger joints. The DHM is adaptable to a wide variety of human hand sizes and shapes, throughout their full range of motion.
Full Text Available Multimodal signal analysis based on sophisticated sensors, efficient communicationsystems and fast parallel processing methods has a rapidly increasing range of multidisciplinaryapplications. The present paper is devoted to pattern recognition, machine learning, and the analysisof sleep stages in the detection of sleep disorders using polysomnography (PSG data, includingelectroencephalography (EEG, breathing (Flow, and electro-oculogram (EOG signals. The proposedmethod is based on the classification of selected features by a neural network system with sigmoidaland softmax transfer functions using Bayesian methods for the evaluation of the probabilities of theseparate classes. The application is devoted to the analysis of the sleep stages of 184 individualswith different diagnoses, using EEG and further PSG signals. Data analysis points to an averageincrease of the length of the Wake stage by 2.7% per 10 years and a decrease of the length of theRapid Eye Movement (REM stages by 0.8% per 10 years. The mean classification accuracy for givensets of records and single EEG and multimodal features is 88.7% ( standard deviation, STD: 2.1 and89.6% (STD:1.9, respectively. The proposed methods enable the use of adaptive learning processesfor the detection and classification of health disorders based on prior specialist experience andman–machine interaction.
Ratta, G.A.; Vega, J.; Pereira, A.; Portas, A.; Luna, E. de la; Dormido-Canto, S.; Farias, G.; Dormido, R.; Sanchez, J.; Duro, N.; Vargas, H.; Santos, M.; Pajares, G.; Murari, A.
Structural pattern recognition techniques allow the identification of plasma behaviours. Physical properties are encoded in the morphological structure of signals. Intelligent access methods have been applied to JET databases to retrieve data according to physical criteria. On the one hand, the structural form of signals has been used to develop general purpose data retrieval systems to search for both similar entire waveforms and similar structural shapes inside waveforms. On the other hand, domain dependent knowledge was added to the structural information of signals to create particular data retrieval methods for specific physical phenomena. The inclusion of explicit knowledge assists in data analysis. The latter has been applied in JET to look for first, cut-offs in ECE heterodyne radiometer signals and, second, L-H transitions
Ratta, G.A. [Asociacion EURATOM/CIEMAT para Fusion (Spain)], E-mail: email@example.com; Vega, J.; Pereira, A.; Portas, A.; Luna, E. de la [Asociacion EURATOM/CIEMAT para Fusion (Spain); Dormido-Canto, S.; Farias, G.; Dormido, R.; Sanchez, J.; Duro, N.; Vargas, H. [Dpto. Informatica y Automatica-UNED, 28040 Madrid (Spain); Santos, M.; Pajares, G. [Dpto. Arquitectura de Computadores y Automatica-UCM, 28040 Madrid (Spain); Murari, A. [Consorzio RFX-Associazione EURATOM ENEA per la Fusione, Padua (Italy)
Structural pattern recognition techniques allow the identification of plasma behaviours. Physical properties are encoded in the morphological structure of signals. Intelligent access methods have been applied to JET databases to retrieve data according to physical criteria. On the one hand, the structural form of signals has been used to develop general purpose data retrieval systems to search for both similar entire waveforms and similar structural shapes inside waveforms. On the other hand, domain dependent knowledge was added to the structural information of signals to create particular data retrieval methods for specific physical phenomena. The inclusion of explicit knowledge assists in data analysis. The latter has been applied in JET to look for first, cut-offs in ECE heterodyne radiometer signals and, second, L-H transitions.
Tschudin-Sutter, Sarah; Pargger, Hans; Widmer, Andreas F
Healthcare-associated infections affect 1.4 million patients at any time worldwide, as estimated by the World Health Organization. In intensive care units, the burden of healthcare-associated infections is greatly increased, causing additional morbidity and mortality. Multidrug-resistant pathogens are commonly involved in such infections and render effective treatment challenging. Proper hand hygiene is the single most important, simplest, and least expensive means of preventing healthcare-associated infections. In addition, it is equally important to stop transmission of multidrug-resistant pathogens. According to the Centers for Disease Control and Prevention and World Health Organization guidelines on hand hygiene in health care, alcohol-based handrub should be used as the preferred means for routine hand antisepsis. Alcohols have excellent in vitro activity against Gram-positive and Gram-negative bacteria, including multidrug-resistant pathogens, such as methicillin-resistant Staphylococcus aureus and vancomycin-resistant enterococci, Mycobacterium tuberculosis, a variety of fungi, and most viruses. Some pathogens, however, such as Clostridium difficile, Bacillus anthracis, and noroviruses, may require special hand hygiene measures. Failure to provide user friendliness of hand hygiene equipment and shortage of staff are predictors for noncompliance, especially in the intensive care unit setting. Therefore, practical approaches to promote hand hygiene in the intensive care unit include provision of a minimal number of handrub dispensers per bed, monitoring of compliance, and choice of the most attractive product. Lack of knowledge of guidelines for hand hygiene, lack of recognition of hand hygiene opportunities during patient care, and lack of awareness of the risk of cross-transmission of pathogens are barriers to good hand hygiene practices. Multidisciplinary programs to promote increased use of alcoholic handrub lead to an increased compliance of healthcare
Jensen, Rune Fisker; Carstensen, Jens Michael
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 distr...
Accidental self-inflicted knife injuries to digits are a common cause of tendon and nerve injury requiring hand surgery. There has been an apparent increase in avocado related hand injuries. Classically, the patients hold the avocado in their non-dominant hand while using a knife to cut\\/peel the fruit with their dominant hand. The mechanism of injury is usually a stabbing injury to the non-dominant hand as the knife slips past the stone, through the soft avocado fruit. Despite their apparent increased incidence, we could not find any cases in the literature which describe the “avocado hand”. We present a case of a 32-year-old woman who sustained a significant hand injury while preparing an avocado. She required exploration and repair of a digital nerve under regional anaesthesia and has since made a full recovery.
Diepgen, T L; Andersen, Klaus Ejner; Brandao, F M
of the disease is rarely evidence based, and a classification system for different subdiagnoses of hand eczema is not agreed upon. Randomized controlled trials investigating the treatment of hand eczema are called for. For this, as well as for clinical purposes, a generally accepted classification system...... A classification system for hand eczema is proposed. Conclusions It is suggested that this classification be used in clinical work and in clinical trials....
Full Text Available This paper describes the structure and performance of the SLARTI sign language recognition system developed at the University of Tasmania. SLARTI uses a modular architecture consisting of multiple feature-recognition neural networks and a nearest-neighbour classifier to recognise Australian sign language (Auslan hand gestures.
This paper describes the structure and performance of the SLARTI sign language recognition system developed at the University of Tasmania. SLARTI uses a modular architecture consisting of multiple feature-recognition neural networks and a nearest-neighbour classifier to recognise Australian sign language (Auslan) hand gestures.
de-Santos-Sierra, Alberto; Sánchez-Ávila, Carmen; Del Pozo, Gonzalo Bailador; Guerra-Casanova, Javier
This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely support vector machines (SVM) and k-nearest neighbour (k-NN). Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices.
Full Text Available This paper presents a hand biometric system for contact-less, platform-free scenarios, proposing innovative methods in feature extraction, template creation and template matching. The evaluation of the proposed method considers both the use of three contact-less publicly available hand databases, and the comparison of the performance to two competitive pattern recognition techniques existing in literature: namely Support Vector Machines (SVM and k-Nearest Neighbour (k-NN. Results highlight the fact that the proposed method outcomes existing approaches in literature in terms of computational cost, accuracy in human identification, number of extracted features and number of samples for template creation. The proposed method is a suitable solution for human identification in contact-less scenarios based on hand biometrics, providing a feasible solution to devices with limited hardware requirements like mobile devices.
Chen, Guangyi; Xie, Wenfang
Moment invariants have received a lot of attention as features for identification and inspection of two-dimensional shapes. In this paper, two sets of novel moments are proposed by using the auto-correlation of wavelet functions and the dual-tree complex wavelet functions. It is well known that the wavelet transform lacks the property of shift invariance. A little shift in the input signal will cause very different output wavelet coefficients. The autocorrelation of wavelet functions and the dual-tree complex wavelet functions, on the other hand, are shift-invariant, which is very important in pattern recognition. Rotation invariance is the major concern in this paper, while translation invariance and scale invariance can be achieved by standard normalization techniques. The Gaussian white noise is added to the noise-free images and the noise levels vary with different signal-to-noise ratios. Experimental results conducted in this paper show that the proposed wavelet-based moments outperform Zernike's moments and the Fourier-wavelet descriptor for pattern recognition under different rotation angles and different noise levels. It can be seen that the proposed wavelet-based moments can do an excellent job even when the noise levels are very high.
Full Text Available ... 585 views 3:10 Wash 'Em - Hand Hygiene Music Video - Duration: 5:46. Jefferson Health 413,097 ... 089,212 views 4:50 Hand hygiene FULL music video - Duration: 2:33. AlfredHealthTV 26,032 views ...
Davidsen, Jacob; Christiansen, Ellen Tove
Apart from touching the screen, what is the role of the hands for children collaborating around touchscreens? Based on embodied and multimodal interaction analysis of 8- and 9-year old pairs collaborating around touchscreens, we conclude that children use their hands to constrain and control acce...
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BHAIRO, NH; NIJSTEN, MWN; VANDALEN, KC; TENDUIS, HJ
We studied the long-term sequelae of hand injuries as a result of playing volleyball. In a retrospective study, 226 patients with injuries of the hand who were seen over a 5-year period at our Trauma Department, were investigated. Females accounted for 66 % of all injuries. The mean age was 26
Full Text Available ... 585 views 3:10 Wash 'Em - Hand Hygiene Music Video - Duration: 5:46. Jefferson Health 412,760 ... 536,963 views 1:46 Hand hygiene FULL music video - Duration: 2:33. AlfredHealthTV 25,574 views ...
Full Text Available ... today; no cure tomorrow - Duration: 3:10. World Health Organization 74,478 views 3:10 Wash 'Em - Hand Hygiene Music Video - Duration: 5:46. Jefferson Health 411,292 views 5:46 Hand Washing Technique - ...
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Full Text Available ... today; no cure tomorrow - Duration: 3:10. World Health Organization 75,362 views 3:10 Wash 'Em - Hand Hygiene Music Video - Duration: 5:46. Jefferson Health 412,404 views 5:46 Hand Washing Technique - ...
Full Text Available ... 585 views 3:10 Wash 'Em - Hand Hygiene Music Video - Duration: 5:46. Jefferson Health 413,097 ... 086,746 views 4:50 Hand hygiene FULL music video - Duration: 2:33. AlfredHealthTV 25,802 views ...
Full Text Available ... 453 views 3:10 Wash 'Em - Hand Hygiene Music Video - Duration: 5:46. Jefferson Health 413,702 ... 28,656 views 3:40 Hand hygiene FULL music video - Duration: 2:33. AlfredHealthTV 26,480 views ...
Full Text Available ... 362 views 3:10 Wash 'Em - Hand Hygiene Music Video - Duration: 5:46. Jefferson Health 412,404 ... 219,427 views 1:27 Hand hygiene FULL music video - Duration: 2:33. AlfredHealthTV 25,194 views ...
Full Text Available ... 03. R Mayer 371,490 views 4:03 The psychological trick behind getting people to say yes - Duration: 8:06. PBS NewsHour 606,671 views 8:06 Should You Really Wash Your Hands? - Duration: 4:51. Gross Science 57,828 views 4:51 Healthcare Worker Hand ...
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Chouk, Mickaël; Vidon, Claire; Deveza, Elise; Verhoeven, Frank; Pelletier, Fabien; Prati, Clément; Wendling, Daniel
Intravenous drug addiction is responsible for many complications, especially cutaneous and infectious. There is a syndrome, rarely observed in rheumatology, resulting in "puffy hands": the puffy hand syndrome. We report two cases of this condition from our rheumatologic consultation. Our two patients had intravenous drug addiction. They presented with an edema of the hands, bilateral, painless, no pitting, occurring in one of our patient during heroin intoxication, and in the other 2 years after stopping injections. In our two patients, additional investigations (biological, radiological, ultrasound) were unremarkable, which helped us, in the context, to put the diagnosis of puffy hand syndrome. The pathophysiology, still unclear, is based in part on a lymphatic toxicity of drugs and their excipients. There is no etiological treatment but elastic compression by night has improved edema of the hands in one of our patients. Copyright © 2016 Société française de rhumatologie. Published by Elsevier SAS. All rights reserved.
Safari, Mohammad Reza; Rowe, Philip; McFadyen, Angus; Buis, Arjan
Residual limb shape capturing (Casting) consistency has a great influence on the quality of socket fit. Magnetic Resonance Imaging was used to establish a reliable reference grid for intercast and intracast shape and volume consistency of two common casting methods, Hands-off and Hands-on. Residual limbs were cast for twelve people with a unilateral below knee amputation and scanned twice for each casting concept. Subsequently, all four volume images of each amputee were semiautomatically segmented and registered to a common coordinate system using the tibia and then the shape and volume differences were calculated. The results show that both casting methods have intra cast volume consistency and there is no significant volume difference between the two methods. Inter- and intracast mean volume differences were not clinically significant based on the volume of one sock criteria. Neither the Hands-off nor the Hands-on method resulted in a consistent residual limb shape as the coefficient of variation of shape differences was high. The resultant shape of the residual limb in the Hands-off casting was variable but the differences were not clinically significant. For the Hands-on casting, shape differences were equal to the maximum acceptable limit for a poor socket fit.
In this paper, the author discusses the regulatory role of the state and legal norms, in market economy, especially in so-called transition countries. Legal policy, and other questions of the state and free market economy are here closely connected, because the state must ensure with legal norms that economic processes are not interrupted: only the state can establish the legal basis for a market economy. The free market’s invisible hand is acting in questions such as: what is to be produced,...
Fisker, Maja H; Ebbehøj, Niels E; Vejlstrup, Søren Grove
Objective Occupational hand eczema has adverse health and socioeconomic impacts for the afflicted individuals and society. Prevention and treatment strategies are needed. This study aimed to assess the effectiveness of an educational intervention on sickness absence, quality of life and severity...... of hand eczema. Methods PREVEX (PreVention of EXema) is an individually randomized, parallel-group superiority trial investigating the pros and cons of one-time, 2-hour, group-based education in skin-protective behavior versus treatment as usual among patients with newly notified occupational hand eczema...
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2015 Annals of Medical and Health Sciences Research | Published by Wolters Kluwer - Medknow. 473. Introduction ... diabetes.[2,3] Tropical diabetic hand syndrome is a terminology .... the importance of seeking medical attention immediately.
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Charness, Neil; Bregman, Albert S.
In a study which required college students to learn to recognize four flexible plastic shapes photographed on different backgrounds from different angles, the importance of a context-rich environment for the learning and recognition of visual patterns was illustrated. (Author)
Full Text Available that is faster and more reliable. We first segment the signs by colour, and then by shape recognition. The sign-type classification is done using a tree search structure that enables the use of iterative contour descriptors like the speeded-up-robust features...
Full Text Available This paper proposes a novel approach to decompose two-person interaction into a Positive Action and a Negative Action for more efficient behavior recognition. A Positive Action plays the decisive role in a two-person exchange. Thus, interaction recognition can be simplified to Positive Action-based recognition, focusing on an action representation of just one person. Recently, a new depth sensor has become widely available, the Microsoft Kinect camera, which provides RGB-D data with 3D spatial information for quantitative analysis. However, there are few publicly accessible test datasets using this camera, to assess two-person interaction recognition approaches. Therefore, we created a new dataset with six types of complex human interactions (i.e., named K3HI, including kicking, pointing, punching, pushing, exchanging an object, and shaking hands. Three types of features were extracted for each Positive Action: joint, plane, and velocity features. We used continuous Hidden Markov Models (HMMs to evaluate the Positive Action-based interaction recognition method and the traditional two-person interaction recognition approach with our test dataset. Experimental results showed that the proposed recognition technique is more accurate than the traditional method, shortens the sample training time, and therefore achieves comprehensive superiority.
Monwar, Md Maruf; Rezaei, Siamak
Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.
May, Zacnicte; Morrill, Adam; Holcombe, Adam; Johnston, Travis; Gallup, Joshua; Fouad, Karim; Schalomon, Melike; Hamilton, Trevor James
The novel object recognition, or novel-object preference (NOP) test is employed to assess recognition memory in a variety of organisms. The subject is exposed to two identical objects, then after a delay, it is placed back in the original environment containing one of the original objects and a novel object. If the subject spends more time exploring one object, this can be interpreted as memory retention. To date, this test has not been fully explored in zebrafish (Danio rerio). Zebrafish possess recognition memory for simple 2- and 3-dimensional geometrical shapes, yet it is unknown if this translates to complex 3-dimensional objects. In this study we evaluated recognition memory in zebrafish using complex objects of different sizes. Contrary to rodents, zebrafish preferentially explored familiar over novel objects. Familiarity preference disappeared after delays of 5 mins. Leopard danios, another strain of D. rerio, also preferred the familiar object after a 1 min delay. Object preference could be re-established in zebra danios by administration of nicotine tartrate salt (50mg/L) prior to stimuli presentation, suggesting a memory-enhancing effect of nicotine. Additionally, exploration biases were present only when the objects were of intermediate size (2 × 5 cm). Our results demonstrate zebra and leopard danios have recognition memory, and that low nicotine doses can improve this memory type in zebra danios. However, exploration biases, from which memory is inferred, depend on object size. These findings suggest zebrafish ecology might influence object preference, as zebrafish neophobia could reflect natural anti-predatory behaviour. Copyright © 2015 Elsevier B.V. All rights reserved.
Over the past few decades, face recognition has become a rapidly growing research topic due to the increasing demands in many applications of our daily life such as airport surveillance, personal identification in law enforcement, surveillance systems, information safety, securing financial transactions, and computer security. The objective of this thesis is to develop a face recognition system capable of recognizing persons with a high recognition capability, low processing time, and under different illumination conditions, and different facial expressions. The thesis presents a study for the performance of the face recognition system using two techniques; the Principal Component Analysis (PCA), and the Zernike Moments (ZM). The performance of the recognition system is evaluated according to several aspects including the recognition rate, and the processing time. Face recognition systems that use visual images are sensitive to variations in the lighting conditions and facial expressions. The performance of these systems may be degraded under poor illumination conditions or for subjects of various skin colors. Several solutions have been proposed to overcome these limitations. One of these solutions is to work in the Infrared (IR) spectrum. IR images have been suggested as an alternative source of information for detection and recognition of faces, when there is little or no control over lighting conditions. This arises from the fact that these images are formed due to thermal emissions from skin, which is an intrinsic property because these emissions depend on the distribution of blood vessels under the skin. On the other hand IR face recognition systems still have limitations with temperature variations and recognition of persons wearing eye glasses. In this thesis we will fuse IR images with visible images to enhance the performance of face recognition systems. Images are fused using the wavelet transform. Simulation results show that the fusion of visible and
Jain, Anil K
This report describes research efforts towards developing algorithms for a robust face recognition system to overcome many of the limitations found in existing two-dimensional facial recognition systems...
Guo, Hansong; Huang, He; Huang, Liusheng; Sun, Yu-E
As the size of smartphone touchscreens has become larger and larger in recent years, operability with a single hand is getting worse, especially for female users. We envision that user experience can be significantly improved if smartphones are able to recognize the current operating hand, detect the hand-changing process and then adjust the user interfaces subsequently. In this paper, we proposed, implemented and evaluated two novel systems. The first one leverages the user-generated touchscreen traces to recognize the current operating hand, and the second one utilizes the accelerometer and gyroscope data of all kinds of activities in the user's daily life to detect the hand-changing process. These two systems are based on two supervised classifiers constructed from a series of refined touchscreen trace, accelerometer and gyroscope features. As opposed to existing solutions that all require users to select the current operating hand or confirm the hand-changing process manually, our systems follow much more convenient and practical methods and allow users to change the operating hand frequently without any harm to the user experience. We conduct extensive experiments on Samsung Galaxy S4 smartphones, and the evaluation results demonstrate that our proposed systems can recognize the current operating hand and detect the hand-changing process with 94.1% and 93.9% precision and 94.1% and 93.7% True Positive Rates (TPR) respectively, when deciding with a single touchscreen trace or accelerometer-gyroscope data segment, and the False Positive Rates (FPR) are as low as 2.6% and 0.7% accordingly. These two systems can either work completely independently and achieve pretty high accuracies or work jointly to further improve the recognition accuracy.
Full Text Available As the size of smartphone touchscreens has become larger and larger in recent years, operability with a single hand is getting worse, especially for female users. We envision that user experience can be significantly improved if smartphones are able to recognize the current operating hand, detect the hand-changing process and then adjust the user interfaces subsequently. In this paper, we proposed, implemented and evaluated two novel systems. The first one leverages the user-generated touchscreen traces to recognize the current operating hand, and the second one utilizes the accelerometer and gyroscope data of all kinds of activities in the user’s daily life to detect the hand-changing process. These two systems are based on two supervised classifiers constructed from a series of refined touchscreen trace, accelerometer and gyroscope features. As opposed to existing solutions that all require users to select the current operating hand or confirm the hand-changing process manually, our systems follow much more convenient and practical methods and allow users to change the operating hand frequently without any harm to the user experience. We conduct extensive experiments on Samsung Galaxy S4 smartphones, and the evaluation results demonstrate that our proposed systems can recognize the current operating hand and detect the hand-changing process with 94.1% and 93.9% precision and 94.1% and 93.7% True Positive Rates (TPR respectively, when deciding with a single touchscreen trace or accelerometer-gyroscope data segment, and the False Positive Rates (FPR are as low as 2.6% and 0.7% accordingly. These two systems can either work completely independently and achieve pretty high accuracies or work jointly to further improve the recognition accuracy.
K.C. , Santosh; Wendling , Laurent
International audience; The chapter focuses on one of the key issues in document image processing i.e., graphical symbol recognition. Graphical symbol recognition is a sub-field of a larger research domain: pattern recognition. The chapter covers several approaches (i.e., statistical, structural and syntactic) and specially designed symbol recognition techniques inspired by real-world industrial problems. It, in general, contains research problems, state-of-the-art methods that convey basic s...
Moore, Geoffrey A
There are two kinds of businesses in the world, says the author. Knowing what they are--and which one your company is--will guide you to the right strategic moves. One kind includes businesses that compete on a complex-systems model. These companies have large enterprises as their primary customers. They seek to grow a customer base in the thousands, with no more than a handful of transactions per customer per year (indeed, in some years there may be none), and the average price per transaction ranges from six to seven figures. In this model, 1,000 enterprises each paying dollar 1 million per year would generate dollar 1 billion in annual revenue. The other kind of business competes on a volume-operations model. Here, vendors seek to acquire millions of customers, with tens or even hundreds of transactions per customer per year, at an average price of relatively few dollars per transaction. Under this model, it would take 10 million customers each spending dollar 8 per month to generate nearly dollar 1 billion in revenue. An examination of both models shows that they could not be further apart in their approach to every step along the classic value chain. The problem, though, is that companies in one camp often attempt to create new value by venturing into the other. In doing so, they fail to realize how their managerial habits have been shaped by the model they've grown up with. By analogy, they have a "handedness"--the equivalent of a person's right- or left-hand dominance--that makes them as adroit in one mode as they are awkward in the other. Unless you are in an industry whose structure forces you to attempt ambidexterity (in which case, special efforts are required to manage the inevitable dropped balls), you'll be far more successful making moves that favor your stronger hand.
Hamid Ehsani-Nia, DO
Full Text Available History of present illness: A 27-year-old female sustained an injury to her left hand after she tripped and fell on a vase. She presented to the emergency department (ED complaining of pain over the laceration. Upon examination, patient presented with multiple small abrasions of the medial aspect of the left 5thdigit that are minimally tender. Additionally, she has one 0.5cm linear laceration of the medial aspect of the 5thmetacarpal with severe tenderness in the area and palpable underlying foreign body. Significant findings: Left hand plain radiography demonstrated a subcutaneous foreign body medial to the 5thmetacarpal that is radiopaque, trapezoidal in shape, and measures approximately 11mm x 3mm. Discussion: Laceration repairs are amongst the most common procedures in the emergency department; however, consideration for foreign body is often underdiagnosed. Imaging is performed in only about 11% of all traumatic wounds in the ED.1 Of those injuries relating to the hand that are subsequently imaged, about 15% are found to have a foreign body.2,3 Additionally, it is estimated that foreign bodies are present in 7% to 8.7% of all wounds caused by glass objects.4,5 Glass is among the most common foreign bodies in lacerations, and fortunately they are radiopaque and relatively well visualized radiographically. It has been demonstrated that 2mm glass foreign bodies have a 99% detection rate with radiography, and 1mm glass foreign bodies an 83% detection rate.6 Patient perception of foreign body has a positive predictive value of 31%, making it a poor source in influencing clinical decision-making to obtain wound radiographs.3 Clinicians should have a high suspicion for foreign body in lacerations, particularly those caused by glass, and utilize close physical examination and imaging for evaluation. Topics: Radiography, glass, foreign body, trauma
Boyer, Doug M; Yapuncich, Gabriel S; Chester, Stephen G B; Bloch, Jonathan I; Godinot, Marc
Questions surrounding the origin and early evolution of primates continue to be the subject of debate. Though anatomy of the skull and inferred dietary shifts are often the focus, detailed studies of postcrania and inferred locomotor capabilities can also provide crucial data that advance understanding of transitions in early primate evolution. In particular, the hand skeleton includes characteristics thought to reflect foraging, locomotion, and posture. Here we review what is known about the early evolution of primate hands from a comparative perspective that incorporates data from the fossil record. Additionally, we provide new comparative data and documentation of skeletal morphology for Paleogene plesiadapiforms, notharctines, cercamoniines, adapines, and omomyiforms. Finally, we discuss implications of these data for understanding locomotor transitions during the origin and early evolutionary history of primates. Known plesiadapiform species cannot be differentiated from extant primates based on either intrinsic hand proportions or hand-to-body size proportions. Nonetheless, the presence of claws and a different metacarpophalangeal [corrected] joint form in plesiadapiforms indicate different grasping mechanics. Notharctines and cercamoniines have intrinsic hand proportions with extremely elongated proximal phalanges and digit rays relative to metacarpals, resembling tarsiers and galagos. But their hand-to-body size proportions are typical of many extant primates (unlike those of tarsiers, and possibly Teilhardina, which have extremely large hands). Non-adapine adapiforms and omomyids exhibit additional carpal features suggesting more limited dorsiflexion, greater ulnar deviation, and a more habitually divergent pollex than observed plesiadapiforms. Together, features differentiating adapiforms and omomyiforms from plesiadapiforms indicate increased reliance on vertical prehensile-clinging and grasp-leaping, possibly in combination with predatory behaviors in
Lu, Shijian; Li, Linlin; Tan, Chew Lim
This paper presents a document retrieval technique that is capable of searching document images without OCR (optical character recognition). The proposed technique retrieves document images by a new word shape coding scheme, which captures the document content through annotating each word image by a word shape code. In particular, we annotate word images by using a set of topological shape features including character ascenders/descenders, character holes, and character water reservoirs. With the annotated word shape codes, document images can be retrieved by either query keywords or a query document image. Experimental results show that the proposed document image retrieval technique is fast, efficient, and tolerant to various types of document degradation.
Liu, Jiamin; Udupa, Jayaram K
Active shape models (ASM) are widely employed for recognizing anatomic structures and for delineating them in medical images. In this paper, a novel strategy called oriented active shape models (OASM) is presented in an attempt to overcome the following five limitations of ASM: 1) lower delineation accuracy, 2) the requirement of a large number of landmarks, 3) sensitivity to search range, 4) sensitivity to initialization, and 5) inability to fully exploit the specific information present in the given image to be segmented. OASM effectively combines the rich statistical shape information embodied in ASM with the boundary orientedness property and the globally optimal delineation capability of the live wire methodology of boundary segmentation. The latter characteristics allow live wire to effectively separate an object boundary from other nonobject boundaries with similar properties especially when they come very close in the image domain. The approach leads to a two-level dynamic programming method, wherein the first level corresponds to boundary recognition and the second level corresponds to boundary delineation, and to an effective automatic initialization method. The method outputs a globally optimal boundary that agrees with the shape model if the recognition step is successful in bringing the model close to the boundary in the image. Extensive evaluation experiments have been conducted by utilizing 40 image (magnetic resonance and computed tomography) data sets in each of five different application areas for segmenting breast, liver, bones of the foot, and cervical vertebrae of the spine. Comparisons are made between OASM and ASM based on precision, accuracy, and efficiency of segmentation. Accuracy is assessed using both region-based false positive and false negative measures and boundary-based distance measures. The results indicate the following: 1) The accuracy of segmentation via OASM is considerably better than that of ASM; 2) The number of landmarks
Full Text Available Eczema, the commonest disorders afflicting the hands, is also the commonest occupational skin disease (OSD. In the dermatology outpatient departments, only the severe cases are diagnosed since patients rarely report with early hand dermatitis. Mild forms are picked up only during occupational screening. Hand eczema (HE can evolve into a chronic condition with persistent disease even after avoiding contact with the incriminated allergen / irritant. The important risk factors for hand eczema are atopy (especially the presence of dermatitis, wet work, and contact allergy. The higher prevalence in women as compared to men in most studies is related to environmental factors and is mainly applicable to younger women in their twenties. Preventive measures play a very important role in therapy as they enable the affected individuals to retain their employment and livelihood. This article reviews established preventive and therapeutic options and newer drugs like alitretinoin in hand eczema with a mention on the etiology and morphology. Identifying the etiological factors is of paramount importance as avoiding or minimizing these factors play an important role in treatment.
Hand Hygiene When and How August 2009 How to handrub? How to handwash? RUB HANDS FOR HAND HYGIENE! WASH HANDS WHEN VISIBLY SOILED Duration of the ... its use. When? YOUR 5 MOMENTS FOR HAND HYGIENE 1 BEFORETOUCHINGA PATIENT 2 B P ECFLOER R ...
Full Text Available New low cost sensors and open free libraries for 3D image processing are making important advances in robot vision applications possible, such as three-dimensional object recognition, semantic mapping, navigation and localization of robots, human detection and/or gesture recognition for human-machine interaction. In this paper, a novel method for recognizing and tracking the fingers of a human hand is presented. This method is based on point clouds from range images captured by a RGBD sensor. It works in real time and it does not require visual marks, camera calibration or previous knowledge of the environment. Moreover, it works successfully even when multiple objects appear in the scene or when the ambient light is changed. Furthermore, this method was designed to develop a human interface to control domestic or industrial devices, remotely. In this paper, the method was tested by operating a robotic hand. Firstly, the human hand was recognized and the fingers were detected. Secondly, the movement of the fingers was analysed and mapped to be imitated by a robotic hand.
Recognition and toleration are ways of relating to the diversity characteristic of multicultural societies. The article concerns the possible meanings of toleration and recognition, and the conflict that is often claimed to exist between these two approaches to diversity. Different forms...... or interpretations of recognition and toleration are considered, confusing and problematic uses of the terms are noted, and the compatibility of toleration and recognition is discussed. The article argues that there is a range of legitimate and importantly different conceptions of both toleration and recognition...
representations. For representing objects, we derive global descriptors encoding shape using viewpoint-invariant features obtained from multiple sensors observing the scene. Objects are also described using color independently. This allows for combining color and shape when it is required for the task. For more...... robust color description, color calibration is performed. The framework was used in three recognition tasks: object instance recognition, object category recognition, and object spatial relationship recognition. For the object instance recognition task, we present a system that utilizes color and scale...
...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 1292.2...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization...
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Lund, Tamara Theresia; Agner, Tove
Hand eczema is a common disease, it affects young people, is often work-related, and the burden of the disease is significant for the individual as well as for society. Factors to be considered when choosing a treatment strategy are, among others, whether the eczema is acute or chronic, the sever...
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This video shows kids how to properly wash their hands, one of the most important steps we can take to avoid getting sick and spreading germs to others. Created: 3/8/2010 by Centers for Disease Control and Prevention (CDC). Date Released: 3/8/2010.
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Full Text Available ... action today; no cure tomorrow - Duration: 3:10. World Health Organization 74,478 views 3:10 Wash your Hands - ... handwash? With soap and water - Duration: 1:27. World Health Organization 215,487 views 1:27 Infection Control Video - ...
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Kauffman, J.A.; Slump, Cornelis H.; Bernelot Moens, H.J.
Biometric verification and identification methods of medical images can be used to find possible inconsistencies in patient records. Such methods may also be useful for forensic research. In this work we present a method for identifying patients by their hand radiographs. We use active appearance
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In this paper we discuss manipulatives and hands-on investigations for Calculus involving volume, arc length, and surface area to motivate and develop formulae which can then be verified using techniques of integration. Pre-service teachers in calculus courses using these activities experience a classroom in which active learning is encouraged and…
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Pankiewicz, Philip R.
Presents five hands-on activities that allow students to detect, measure, reduce, and eliminate moisture. Students make a humidity detector and a hygrometer, examine the effects of moisture on different substances, calculate the percent of water in a given food, and examine the absorption potential of different desiccants. (MDH)
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Weisgarber, Sherry L.; Van Doren, Lisa; Hackathorn, Merrianne; Hannibal, Joseph T.; Hansgen, Richard
This publication is a collection of 13 hands-on activities that focus on earth science-related activities and involve students in learning about growing crystals, tectonics, fossils, rock and minerals, modeling Ohio geology, geologic time, determining true north, and constructing scale-models of the Earth-moon system. Each activity contains…
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Full Text Available ... Gorin 243,451 views 2:57 Hand Hygiene Dance - Duration: 3:15. mohd hafiz 34,146 views ... Language: English Location: United States Restricted Mode: Off History Help Loading... Loading... Loading... About Press Copyright Creators ...
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Mathews, Catherine E.; Monroe, Louise Nelson
A professional school and university collaboration enables elementary students and their teachers to explore hydrology concepts and realize the beneficial functions of wetlands. Hands-on experiences involve young students in determining water quality at field sites after laying the groundwork with activities related to the hydrologic cycle,…
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Kolson, Dennis; Buch, Shilpa
Developing a validated tool for the rapid and efficient assessment of cognitive functioning in HIV-infected patients in a typical outpatient clinical setting has been an unmet goal of HIV research since the recognition of the syndrome of HIV-associated dementia (HAD) nearly 20 years ago. In this issue of JNIP Cross et al. report the application of the International HIV Dementia Scale (IHDS) in a U.S.-based urban outpatient clinic to evaluate its utility as a substitute for the more time- and effort-demanding formalized testing criteria known as the Frascati criteria that was developed in 2007 to define the syndrome of HIV-associated neurocognitive disorders (HAND). In this study an unselected cohort of 507 individuals (68 % African American) that were assessed using the IHDS in a cross-sectional study revealed a 41 % prevalence of cognitive impairment (labeled ‘symptomatic HAND’) that was associated with African American race, older age, unemployment, education level, and depression. While the associations between cognitive impairment and older age, education, unemployment status and depression in HIV-infected patients are not surprising, the association with African American ancestry and cognitive impairment in the setting of HIV infection is a novel finding of this study. This commentary discusses several important issues raised by the study, including the pitfalls of assessing cognitive functioning with rapid screening tools, cognitive testing criteria, normative testing control groups, accounting for HAND co-morbidity factors, considerations for clinical trials assessing HAND, and selective population vulnerability to HAND.
Yu, Francis T. S.; Jutamulia, Suganda
Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.
Fire, heat, cold, electro-magnetic and ionising radiation, electricity, chemicals, impacts, cuts, abrasion, etc. are the common hazards for arms and hands at work. The gloves chosen for protection of the arm and hand should cover those parts adequately and the material of the gloves should be capable of offering protection against the specific hazard involved. Criteria for choosing arm and hand protection equipment will be based on their shape and part of the arm and hand protected. Guide lines for choosing such personal protection equipment for nuclear facilities are given. (M.K.V.). 3 annexures, 1 appendix
Kim, Kwangtaek; Kim, Joongrock; Choi, Jaesung; Kim, Junghyun; Lee, Sangyoun
Vision-based hand gesture interactions are natural and intuitive when interacting with computers, since we naturally exploit gestures to communicate with other people. However, it is agreed that users suffer from discomfort and fatigue when using gesture-controlled interfaces, due to the lack of physical feedback. To solve the problem, we propose a novel complete solution of a hand gesture control system employing immersive tactile feedback to the user's hand. For this goal, we first developed a fast and accurate hand-tracking algorithm with a Kinect sensor using the proposed MLBP (modified local binary pattern) that can efficiently analyze 3D shapes in depth images. The superiority of our tracking method was verified in terms of tracking accuracy and speed by comparing with existing methods, Natural Interaction Technology for End-user (NITE), 3D Hand Tracker and CamShift. As the second step, a new tactile feedback technology with a piezoelectric actuator has been developed and integrated into the developed hand tracking algorithm, including the DTW (dynamic time warping) gesture recognition algorithm for a complete solution of an immersive gesture control system. The quantitative and qualitative evaluations of the integrated system were conducted with human subjects, and the results demonstrate that our gesture control with tactile feedback is a promising technology compared to a vision-based gesture control system that has typically no feedback for the user's gesture inputs. Our study provides researchers and designers with informative guidelines to develop more natural gesture control systems or immersive user interfaces with haptic feedback.
Full Text Available Vision-based hand gesture interactions are natural and intuitive when interacting with computers, since we naturally exploit gestures to communicate with other people. However, it is agreed that users suffer from discomfort and fatigue when using gesture-controlled interfaces, due to the lack of physical feedback. To solve the problem, we propose a novel complete solution of a hand gesture control system employing immersive tactile feedback to the user’s hand. For this goal, we first developed a fast and accurate hand-tracking algorithm with a Kinect sensor using the proposed MLBP (modified local binary pattern that can efficiently analyze 3D shapes in depth images. The superiority of our tracking method was verified in terms of tracking accuracy and speed by comparing with existing methods, Natural Interaction Technology for End-user (NITE, 3D Hand Tracker and CamShift. As the second step, a new tactile feedback technology with a piezoelectric actuator has been developed and integrated into the developed hand tracking algorithm, including the DTW (dynamic time warping gesture recognition algorithm for a complete solution of an immersive gesture control system. The quantitative and qualitative evaluations of the integrated system were conducted with human subjects, and the results demonstrate that our gesture control with tactile feedback is a promising technology compared to a vision-based gesture control system that has typically no feedback for the user’s gesture inputs. Our study provides researchers and designers with informative guidelines to develop more natural gesture control systems or immersive user interfaces with haptic feedback.
This is the first text to provide a unified and self-contained introduction to visual pattern recognition and machine learning. It is useful as a general introduction to artifical intelligence and knowledge engineering, and no previous knowledge of pattern recognition or machine learning is necessary. Basic for various pattern recognition and machine learning methods. Translated from Japanese, the book also features chapter exercises, keywords, and summaries.
Lovchik, Christopher Scott (Inventor); Diftler, Myron A. (Inventor)
A compact robotic hand includes a palm housing, a wrist section, and a forearm section. The palm housing supports a plurality of fingers and one or more movable palm members that cooperate with the fingers to grasp and/or release an object. Each flexible finger comprises a plurality of hingedly connected segments, including a proximal segment pivotally connected to the palm housing. The proximal finger segment includes at least one groove defining first and second cam surfaces for engagement with a cable. A plurality of lead screw assemblies each carried by the palm housing are supplied with power from a flexible shaft rotated by an actuator and output linear motion to a cable move a finger. The cable is secured within a respective groove and enables each finger to move between an opened and closed position. A decoupling assembly pivotally connected to a proximal finger segment enables a cable connected thereto to control movement of an intermediate and distal finger segment independent of movement of the proximal finger segment. The dexterous robotic hand closely resembles the function of a human hand yet is light weight and capable of grasping both heavy and light objects with a high degree of precision.
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Webb, Andrew R
Statistical pattern recognition relates to the use of statistical techniques for analysing data measurements in order to extract information and make justified decisions. It is a very active area of study and research, which has seen many advances in recent years. Applications such as data mining, web searching, multimedia data retrieval, face recognition, and cursive handwriting recognition, all require robust and efficient pattern recognition techniques. This third edition provides an introduction to statistical pattern theory and techniques, with material drawn from a wide range of fields,
Kwon, Ohsung; Lee, Sang-Hee
In previous studies, we showed that the branch length similarity (BLS) entropy profile could be successfully used for the shape recognition such as battle tanks, facial expressions, and butterflies. In the present study, we proposed new descriptors, roundness, symmetry, and surface roughness, for the recognition, which are more accurate and fast in the computation than the previous descriptors. The roundness represents how closely a shape resembles to a circle, the symmetry characterizes how much one shape is similar with another when the shape is moved in flip, and the surface roughness quantifies the degree of vertical deviations of a shape boundary. To evaluate the performance of the descriptors, we used the database of leaf images with 12 species. Each species consisted of 10 - 20 leaf images and the total number of images were 160. The evaluation showed that the new descriptors successfully discriminated the leaf species. We believe that the descriptors can be a useful tool in the field of pattern recognition.
Full Text Available Emotions play a crucial role in person to person interaction. In recent years, there has been a growing interest in improving all aspects of interaction between humans and computers. The ability to understand human emotions is desirable for the computer in several applications especially by observing facial expressions. This paper explores a ways of human-computer interaction that enable the computer to be more aware of the user’s emotional expressions we present a approach for the emotion recognition from a facial expression, hand and body posture. Our model uses multimodal emotion recognition system in which we use two different models for facial expression recognition and for hand and body posture recognition and then combining the result of both classifiers using a third classifier which give the resulting emotion . Multimodal system gives more accurate result than a signal or bimodal system
Rutt, Rebecca Leigh
Abstract This thesis concerns the role of local institutions in fostering development including natural resource management, and how this role is shaped by relations with higher scale institutions such as development agencies and national governments. Specifically, it examines the choice of local...... objective of this thesis was to contribute to understanding processes and outcomes of institutional choice and recognition. It employed mixed methods but primarily semi structured interviews in multiple sites across Nepal. In responding to specific objectives, namely to better understand: i) the rationales...... behind choices of local institutional counterparts, ii) the belonging and citizenship available with local institutions, iii) the dynamics and mutuality of recognition between higher and lower scale institutions, and iv) the social outcomes of choice and recognition, this thesis shows that the way choice...
Carbone, Giuseppe; Rossi, Cesare; Savino, Sergio
This paper describes two robotic hands that have been\\ud developed at University Federico II of Naples and at the\\ud University of Cassino. FEDERICA Hand and LARM Hand\\ud are described in terms of design and operational features.\\ud In particular, careful attention is paid to the differences\\ud between the above-mentioned hands in terms of transmission\\ud systems. FEDERICA Hand uses tendons and pulleys\\ud to drive phalanxes, while LARM Hand uses cross four-bar\\ud linkages. Results of experime...
Linderman, Michael; Lebedev, Mikhail A.; Erlichman, Joseph S.
Handwriting – one of the most important developments in human culture – is also a methodological tool in several scientific disciplines, most importantly handwriting recognition methods, graphology and medical diagnostics. Previous studies have relied largely on the analyses of handwritten traces or kinematic analysis of handwriting; whereas electromyographic (EMG) signals associated with handwriting have received little attention. Here we show for the first time, a method in which EMG signals generated by hand and forearm muscles during handwriting activity are reliably translated into both algorithm-generated handwriting traces and font characters using decoding algorithms. Our results demonstrate the feasibility of recreating handwriting solely from EMG signals – the finding that can be utilized in computer peripherals and myoelectric prosthetic devices. Moreover, this approach may provide a rapid and sensitive method for diagnosing a variety of neurogenerative diseases before other symptoms become clear. PMID:19707562
Studies of signaling theory have traditionally focused on the dyadic link between the sender and receiver of the signal. Within a science‐based perspective this framing has led scholars to investigate how patents and publications of firms function as signals. I explore another important type...... used by various agents in their search for and assessment of products and firms. I conclude by arguing how this second‐hand nature of signals goes beyond a simple dyadic focus on senders and receivers of signals, and thus elucidates the more complex interrelations of the various types of agents...
Frederiksen, Henrik; Gaist, David; Petersen, Hans Christian
in life is a major problem in terms of prevalence, morbidity, functional limitations, and quality of life. It is therefore of interest to find a phenotype reflecting physical functioning which has a relatively high heritability and which can be measured in large samples. Hand grip strength is known......-55%). A powerful design to detect genes associated with a phenotype is obtained using the extreme discordant and concordant sib pairs, of whom 28 and 77 dizygotic twin pairs, respectively, were found in this study. Hence grip strength is a suitable phenotype for identifying genetic variants of importance to mid...
Wood, M.B.; Berquist, T.H.
Trauma is the most common etiologic factor leading to disability in the hand and wrist. Judicious radiographic evaluation is required for accurate assessment in practically all but the most minor of such injuries. Frequently serial radiographic evaluation is essential for directing the course of treatment and for following the healing process. A meaningful radiographic evaluation requires a comprehensive knowledge of the normal radiographic anatomy, an overview of the spectrum of pathology, and an awareness of the usual mechanisms of injury, appropriate treatment options, and relevant array of complications
Mutihac, R.; Mutihac, R.C.
A broad range of approaches has been proposed and applied for the complex and rather difficult task of object recognition that involves the determination of object characteristics and object classification into one of many a priori object types. Our paper revises briefly the three main different paradigms in pattern recognition, namely Bayesian statistics, neural networks, and expert systems. (author)
Rose, Susan A.; Feldman, Judith F.; Jankowski, Jeffery J.
Visual recognition memory is a robust form of memory that is evident from early infancy, shows pronounced developmental change, and is influenced by many of the same factors that affect adult memory; it is surprisingly resistant to decay and interference. Infant visual recognition memory shows (a) modest reliability, (b) good discriminant…
Recognition and toleration are ways of relating to the diversity characteristic of multicultural societies. The article concerns the possible meanings of toleration and recognition, and the conflict that is often claimed to exist between these two approaches to diversity. Different forms or inter...
Nakamura, Kimihiro; Kuo, Wen-Jui; Pegado, Felipe; Cohen, Laurent; Tzeng, Ovid J L; Dehaene, Stanislas
Do the neural circuits for reading vary across culture? Reading of visually complex writing systems such as Chinese has been proposed to rely on areas outside the classical left-hemisphere network for alphabetic reading. Here, however, we show that, once potential confounds in cross-cultural comparisons are controlled for by presenting handwritten stimuli to both Chinese and French readers, the underlying network for visual word recognition may be more universal than previously suspected. Using functional magnetic resonance imaging in a semantic task with words written in cursive font, we demonstrate that two universal circuits, a shape recognition system (reading by eye) and a gesture recognition system (reading by hand), are similarly activated and show identical patterns of activation and repetition priming in the two language groups. These activations cover most of the brain regions previously associated with culture-specific tuning. Our results point to an extended reading network that invariably comprises the occipitotemporal visual word-form system, which is sensitive to well-formed static letter strings, and a distinct left premotor region, Exner's area, which is sensitive to the forward or backward direction with which cursive letters are dynamically presented. These findings suggest that cultural effects in reading merely modulate a fixed set of invariant macroscopic brain circuits, depending on surface features of orthographies.
Health care-associated infections (HAIs) are a significant issue in the United States and throughout the world, but following proper hand hygiene practices is the most effective and least expensive way to prevent HAIs. Hand hygiene is inexpensive and protects patients and health care personnel alike. The four general types of hand hygiene that should be performed in the perioperative environment are washing hands that are visibly soiled, hand hygiene using alcohol-based products, surgical hand scrubs, and surgical hand scrubs using an alcohol-based surgical hand rub product. Barriers to proper hand hygiene may include not thinking about it, forgetting, skin irritation, a lack of role models, or a lack of a safety culture. One strategy for improving hand hygiene practices is monitoring hand hygiene as part of a quality improvement project, but the most important aspect for perioperative team members is to set an example for other team members by following proper hand hygiene practices and reminding each other to perform hand hygiene. Copyright © 2013 AORN, Inc. Published by Elsevier Inc. All rights reserved.
Pauca, V. Paúl; Forkin, Michael; Xu, Xiao; Plemmons, Robert; Ross, Arun A.
Ocular recognition is a new area of biometric investigation targeted at overcoming the limitations of iris recognition performance in the presence of non-ideal data. There are several advantages for increasing the area beyond the iris, yet there are also key issues that must be addressed such as size of the ocular region, factors affecting performance, and appropriate corpora to study these factors in isolation. In this paper, we explore and identify some of these issues with the goal of better defining parameters for ocular recognition. An empirical study is performed where iris recognition methods are contrasted with texture and point operators on existing iris and face datasets. The experimental results show a dramatic recognition performance gain when additional features are considered in the presence of poor quality iris data, offering strong evidence for extending interest beyond the iris. The experiments also highlight the need for the direct collection of additional ocular imagery.
Full Text Available The monkey anterior intraparietal area (AIP) encodes visual information about three-dimensional object shape that is used to shape the hand for grasping. We modeled shape tuning in visual AIP neurons and its relationship with curvature and gradient...
da Costa, R M; Gonzaga, A
The human eye is sensitive to visible light. Increasing illumination on the eye causes the pupil of the eye to contract, while decreasing illumination causes the pupil to dilate. Visible light causes specular reflections inside the iris ring. On the other hand, the human retina is less sensitive to near infra-red (NIR) radiation in the wavelength range from 800 nm to 1400 nm, but iris detail can still be imaged with NIR illumination. In order to measure the dynamic movement of the human pupil and iris while keeping the light-induced reflexes from affecting the quality of the digitalized image, this paper describes a device based on the consensual reflex. This biological phenomenon contracts and dilates the two pupils synchronously when illuminating one of the eyes by visible light. In this paper, we propose to capture images of the pupil of one eye using NIR illumination while illuminating the other eye using a visible-light pulse. This new approach extracts iris features called "dynamic features (DFs)." This innovative methodology proposes the extraction of information about the way the human eye reacts to light, and to use such information for biometric recognition purposes. The results demonstrate that these features are discriminating features, and, even using the Euclidean distance measure, an average accuracy of recognition of 99.1% was obtained. The proposed methodology has the potential to be "fraud-proof," because these DFs can only be extracted from living irises.
Peterson, David; Stofleth, Jerome H.; Saul, Venner W.
Linear shaped charges are described herein. In a general embodiment, the linear shaped charge has an explosive with an elongated arrowhead-shaped profile. The linear shaped charge also has and an elongated v-shaped liner that is inset into a recess of the explosive. Another linear shaped charge includes an explosive that is shaped as a star-shaped prism. Liners are inset into crevices of the explosive, where the explosive acts as a tamper.
Balmashnova, E.; Bruurmijn, L.C.M.; Dissanayake, R.; Duits, R.; Kampmeijer, L.; Noorden, van T.L.; Boon, M.A.A.
A frequently occurring issue in hot rolling of steel is so-called tail pinching. Prominent features of a pinched tail are ripple-like defects and a pointed tail. In this report two algorithms are presented to detect those features accurately in 2D gray scale images of steel strips. The two ripple
Petry, F.; Piepke, A.; Strecker, H.; Klapdor-Kleingrothaus, H.V.; Balysh, A.; Belyaev, S.T.; Demehin, A.; Gurov, A.; Kondratenko, I.; Kotel'nikov, D.; Lebedev, V.I.; Landis, D.; Madden, N.; Pehl, R.H.
A method of event identification that distinguishes single and multiple-site events by determining the number of interactions in a high purity germanium detector is reported. The selectivity of the method has been experimentally verified. (orig.)
Full Text Available Recognition by macrophages is a key process in generating immune response against invading pathogens. Previous studies have focused on recognition of pathogens through surface receptors present on the macrophage's surface. Here, using polymeric particles of different geometries that represent the size and shape range of a variety of bacteria, the importance of target geometry in recognition was investigated. The studies reported here reveal that attachment of particles of different geometries to macrophages exhibits a strong dependence on size and shape. For all sizes and shapes studied, particles possessing the longest dimension in the range of 2-3 microm exhibited highest attachment. This also happens to be the size range of most commonly found bacteria in nature. The surface features of macrophages, in particular the membrane ruffles, might play an important role in this geometry-based target recognition by macrophages. These findings have significant implications in understanding the pathogenicity of bacteria and in designing drug delivery carriers.
Argyriou, Paraskevi; Mohr, Christine; Kita, Sotaro
Research suggests that speech-accompanying gestures influence cognitive processes, but it is not clear whether the gestural benefit is specific to the gesturing hand. Two experiments tested the "(right/left) hand-specificity" hypothesis for self-oriented functions of gestures: gestures with a particular hand enhance cognitive processes…
Musatov, V. Yu.; Pchelintseva, S. V.; Runnova, A. E.; Hramov, A. E.
An approach for the recognition of various cognitive processes in the brain activity in the perception of ambiguous images. On the basis of developed theoretical background and the experimental data, we propose a new classification of oscillating patterns in the human EEG by using an artificial neural network approach. After learning of the artificial neural network reliably identified cube recognition processes, for example, left-handed or right-oriented Necker cube with different intensity of their edges, construct an artificial neural network based on Perceptron architecture and demonstrate its effectiveness in the pattern recognition of the EEG in the experimental.
Tickle, A J; Harvey, P K; Smith, J S; Wu, F
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.
Agner, T; Aalto-Korte, K; Andersen, K E
BACKGROUND: Classification of hand eczema (HE) is mandatory in epidemiological and clinical studies, and also important in clinical work. OBJECTIVES: The aim was to test a recently proposed classification system of HE in clinical practice in a prospective multicentre study. METHODS: Patients were...... recruited from nine different tertiary referral centres. All patients underwent examination by specialists in dermatology and were checked using relevant allergy testing. Patients were classified into one of the six diagnostic subgroups of HE: allergic contact dermatitis, irritant contact dermatitis, atopic...... system investigated in the present study was useful, being able to give an appropriate main diagnosis for 89% of HE patients, and for another 7% when using two main diagnoses. The fact that more than half of the patients had one or more additional diagnoses illustrates that HE is a multifactorial disease....
Anderson, Roger T.; Keating, Karen N.; Doll, Helen A.; Camacho, Fabian
This study describes the development and validation of a brief, patient self-reported questionnaire (the hand-foot skin reaction and quality of life questionnaire) supporting its suitability for use in clinical research to aid in early recognition of symptoms, to evaluate the effectiveness of agents for hand-foot skin reaction (HFSR) or hand-foot syndrome (HFS) treatment within clinical trials, and to evaluate the impact of these treatments on HFS/R-associated patients’ health-related quality...
Lied, Line; Borchgrevink, Grethe E; Finsen, Vilhjalmur
"Wide awake hand surgery", where surgery is performed in local anaesthesia with adrenaline, without sedation or a tourniquet, has become widespread in some countries. It has a number of potential advantages and we wished to evaluate it among our patients. All 122 patients treated by this method during one year were evaluated by the surgeons and the patients on a numerical scale from 0 (best/least) to 10 (worst/most). Theatre time was compared to that recorded for a year when regional or general anaesthesia had been used. The patients' mean score for the general care they had received was 0.1 (SD 0.6), for pain during lidocaine injection 2.4 (SD 2.2), for pain during surgery 0.9 (SD 1.5), and for other discomfort during surgery 0.5 (SD 1.4). Eight reported that they would want general anaesthesia if they were to be operated again. The surgeons' mean evaluation of bleeding during surgery was 1.6 (SD 1.8), oedema during surgery 0.4 (SD 1.1), general disadvantages with the method 1.0 (SD 1.6) and general advantages 6.5 (SD 4.3). The estimation of advantages was 9.9 (DS 0.5) for tendon suture. 28 patients needed intra-operative additional anaesthesia. The proportion was lower among trained hand surgeons and fell significantly during the study period. Non-surgical theatre time was 46 (SD 15) minutes during the study period and 55 (SD 22) minutes during the regional/general period (p theatre.
Peretz, Anne Sofie Rosenborg; Madsen, Ole Rintek; Brogren, Elisabeth
Rheumatoid arthritis results in characteristic deformities of the hand. Medical treatment has undergone a remarkable development. However, not all patients achieve remission or tolerate the treatment. Patients who suffer from deformities and persistent synovitis may be candidates for hand surgery...
Olshausen, Bruno A.
Many recent theories and methods proposed for visual preprocessing and shape representation are summarized. The survey brings together research from the fields of biology, psychology, computer science, electrical engineering, and most recently, neural networks. It was motivated by the need to preprocess images for a sparse distributed memory (SDM), but the techniques presented may also prove useful for applying other associative memories to visual pattern recognition. The material of this survey is divided into three sections: an overview of biological visual processing; methods of preprocessing (extracting parts of shape, texture, motion, and depth); and shape representation and recognition (form invariance, primitives and structural descriptions, and theories of attention).
...; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 292.2...; withdrawal of recognition; accreditation of representatives; roster. (a) Qualifications of organizations. A non-profit religious, charitable, social service, or similar organization established in the United...
Halling-Overgaard, Anne-Sofie; Zachariae, Claus; Thyssen, Jacob P
This article provides an overview of clinical aspects of hand eczema in patients with atopic dermatitis. Hand eczema can be a part of atopic dermatitis itself or a comorbidity, for example, as irritant or allergic contact dermatitis. When managing hand eczema, it is important to first categorize...
... hands frequently can help limit the transfer of bacteria, viruses and other microbes. Always wash your hands before: Preparing food or eating Treating wounds or caring for a sick person Inserting or removing contact lenses Always wash your hands after: Preparing food Using ...
Bongers, Raoul M; Zaal, Frank T J M; Jeannerod, Marc
Although variations in the standard prehensile pattern can be found in the literature, these alternative patterns have never been studied systematically. This was the goal of the current paper. Ten participants picked up objects with a pincer grip. Objects (3, 5, or 7cm in diameter) were placed at 30, 60, 90, or 120cm from the hands' starting location. Usually the hand was opened gradually to a maximum immediately followed by hand closing, called the standard hand opening pattern. In the alternative opening patterns the hand opening was bumpy, or the hand aperture stayed at a plateau before closing started. Two participants in particular delayed the start of grasping with respect to start of reaching, with the delay time increasing with object distance. For larger object distances and smaller object sizes, the bumpy and plateau hand opening patterns were used more often. We tentatively concluded that the alternative hand opening patterns extended the hand opening phase, to arrive at the appropriate hand aperture at the appropriate time to close the hand for grasping the object. Variations in hand opening patterns deserve attention because this might lead to new insights into the coordination of reaching and grasping. Copyright © 2011 Elsevier B.V. All rights reserved.
Gerlach, Christian; Starrfelt, Randi
examine whether global precedence effects, measured by means of non-face stimuli in Navon's paradigm, can also account for individual differences in face recognition and, if so, whether the effect is of similar magnitude for faces and objects. We find evidence that global precedence effects facilitate...... both face and object recognition, and to a similar extent. Our results suggest that both face and object recognition are characterized by a coarse-to-fine temporal dynamic, where global shape information is derived prior to local shape information, and that the efficiency of face and object recognition...
Riello, Marianna; Rusconi, Elena
A structural representation of the hand embedding information about the identity and relative position of fingers is necessary to counting routines. It may also support associations between numbers and allocentric spatial codes that predictably interact with other known numerical spatial representations, such as the mental number line (MNL). In this study, 48 Western participants whose typical counting routine proceeded from thumb-to-little on both hands performed magnitude and parity binary judgments. Response keys were pressed either with the right index and middle fingers or with the left index and middle fingers in separate blocks. 24 participants responded with either hands in prone posture (i.e., palm down) and 24 participants responded with either hands in supine (i.e., palm up) posture. When hands were in prone posture, the counting direction of the left hand conflicted with the direction of the left-right MNL, whereas the counting direction of the right hand was consistent with it. When hands were in supine posture, the opposite was true. If systematic associations existed between relative number magnitude and an allocentric spatial representation of the finger series within each hand, as predicted on the basis of counting habits, interactions would be expected between hand posture and a unimanual version of the spatial-numerical association of response codes (SNARC) effect. Data revealed that with hands in prone posture a unimanual SNARC effect was present for the right hand, and with hands in supine posture a unimanual SNARC effect was present for the left hand. We propose that a posture-invariant body structural representation of the finger series provides a relevant frame of reference, a within-hand directional vector, that is associated to simple number processing. Such frame of reference can significantly interact with stimulus-response correspondence effects, like the SNARC, that have been typically attributed to the mapping of numbers on a left
Full Text Available A structural representation of the hand embedding information about the identity and relative position of fingers is necessary to counting routines. It may also support associations between numbers and allocentric spatial codes that predictably interact with other known numerical spatial representations, such as the mental number line. In this study, 48 Western participants whose typical counting routine proceeded from thumb-to-little on both hands performed magnitude and parity binary judgments. Response keys were pressed either with the right index and middle fingers or with the left index and middle fingers in separate blocks. 24 participants responded with either hands in prone posture (i.e. palm down and 24 participants responded with either hands in supine (i.e. palm up posture. When hands were in prone posture, the counting direction of the left hand conflicted with the direction of the left-right mental number line, whereas the counting direction of the right hand was consistent with it. When hands were in supine posture, the opposite was true. If systematic associations existed between relative number magnitude and an allocentric spatial representation of the finger series within each hand, as predicted on the basis of counting habits, interactions would be expected between hand posture and a unimanual version of the Spatial-Numerical Association of Response Codes (SNARC effect. Data revealed that with hands in prone posture a unimanual SNARC effect was present for the right hand, and with hands in supine posture a unimanual SNARC effect was present for the left hand. We propose that a posture-invariant body structural representation of the finger series provides a relevant frame of reference, a within-hand directional vector, that is associated to simple number processing. Such frame of reference can significantly interact with stimulus-response correspondence effects that have been attributed to the mapping of numbers on a mental
Jørgensen, Jan Guldager; Schröder, Philipp
The present paper examines trade liberalization driven by the coordination of product standards. For oligopolistic firms situated in separate markets that are initially sheltered by national standards, mutual recognition of standards implies entry and reduced profits at home paired with the oppor......The present paper examines trade liberalization driven by the coordination of product standards. For oligopolistic firms situated in separate markets that are initially sheltered by national standards, mutual recognition of standards implies entry and reduced profits at home paired...... countries and three firms, where firms first lobby for the policy coordination regime (harmonization versus mutual recognition), and subsequently, in case of harmonization, the global standard is auctioned among the firms. We discuss welfare effects and conclude with policy implications. In particular......, harmonized standards may fail to harvest the full pro-competitive effects from trade liberalization compared to mutual recognition; moreover, the issue is most pronounced in markets featuring price competition....
A total of 294 schools, colleges, and universities received prizes in this year's CASE Recognition program. Awards were given in: public relations programs, student recruitment, marketing, program pulications, news writing, fund raising, radio programming, school periodicals, etc. (MLW)
The aim of forensic speaker recognition is to establish links between individuals and criminal activities, through audio speech recordings. This field is multidisciplinary, combining predominantly phonetics, linguistics, speech signal processing, and forensic statistics. On these bases, expert-based
We present a method to determine the precise shape of a dynamic object from video. This problem is fundamental to computer vision, and has a number of applications, for example, 3D video/cinema post-production, activity recognition and augmented
Full Text Available Many laboratories have studied persistence of shape information, the goal being to better understand how the visual system mediates recognition of objects. Most have asked for recognition of known shapes, e.g., letters of the alphabet, or recall from an array. Recognition of known shapes requires access to long-term memory, so it is not possible to know whether the experiment is assessing short-term encoding and working memory mechanisms, or has encountered limitations on retrieval from memory stores. Here we have used an inventory of unknown shapes, wherein a string of discrete dots forms the boundary of each shape. Each was displayed as a target only once to a given respondent, with recognition being tested using a matching task. Analysis based on signal detection theory was used to provide an unbiased estimate of the probability of correct decisions about whether comparison shapes matched target shapes. Four experiments were conducted, which found the following: a Shapes were identified with a high probability of being correct with dot densities ranging from 20% to 4%. Performance dropped only about 10% across this density range. b Shape identification levels remained very high with up to 500 milliseconds of target and comparison shape separation. c With one-at-a-time display of target dots, varying the total time for a given display, the proportion of correct decisions dropped only about 10% even with a total display time of 500 milliseconds. d With display of two complementary target subsets, also varying the total time of each display, there was a dramatic decline of proportion correct that reached chance levels by 500 milliseconds. The greater rate of decline for the two-pulse condition may be due to a mechanism that registers when the number of dots is sufficient to create a shape summary. Once a summary is produced, the temporal window that allows shape information to be added may be more limited.
Elsass, Peter; Jensen, Bodil; Mørup, Rikke
Elsass P., Jensen B., Morup R., Thogersen M.H. (2007). The Recognition Of Fatigue: A qualitative study of life-stories from rehabilitation clients. International Journal of Psychosocial Rehabilitation. 11 (2), 75-87......Elsass P., Jensen B., Morup R., Thogersen M.H. (2007). The Recognition Of Fatigue: A qualitative study of life-stories from rehabilitation clients. International Journal of Psychosocial Rehabilitation. 11 (2), 75-87...
Sturm, Bob L.
A fundamental problem with nearly all work in music genre recognition (MGR)is that evaluation lacks validity with respect to the principal goals of MGR. This problem also occurs in the evaluation of music emotion recognition (MER). Standard approaches to evaluation, though easy to implement, do...... not reliably differentiate between recognizing genre or emotion from music, or by virtue of confounding factors in signals (e.g., equalization). We demonstrate such problems for evaluating an MER system, and conclude with recommendations....
Erban, J.; Kleinbauer, K.; Husak, V.; Grigar, O.
The claimed device consists of a scintillation detector mounted in a shielding case consisting of rings. The shielding case is provided with a cavity with an inlet opening lined with polyethylene foil. The cavity shape, shielding and replaceable foil guarantee minimizing the interfering effect of radiation sources in the vicinity and of contamination of the device. Gradually inserting the hand in the cavity or suitably placing the hand can locate contamination of the hand surface. The sensitivity of the device for 125 I and 99 Tc is 200-times higher than that of Geiger-Mueller counter instruments. (M.D.)
Full Text Available Performing tasks with a robot hand often requires a complete knowledge of the manipulated object, including its properties (shape, rigidity, surface texture and its location in the environment, in order to ensure safe and efficient manipulation. While well-established procedures exist for the manipulation of rigid objects, as well as several approaches for the manipulation of linear or planar deformable objects such as ropes or fabric, research addressing the characterization of deformable objects occupying a volume remains relatively limited. The paper proposes an approach for tracking the deformation of non-rigid objects under robot hand manipulation using RGB-D data. The purpose is to automatically classify deformable objects as rigid, elastic, plastic, or elasto-plastic, based on the material they are made of, and to support recognition of the category of such objects through a robotic probing process in order to enhance manipulation capabilities. The proposed approach combines advantageously classical color and depth image processing techniques and proposes a novel combination of the fast level set method with a log-polar mapping of the visual data to robustly detect and track the contour of a deformable object in a RGB-D data stream. Dynamic time warping is employed to characterize the object properties independently from the varying length of the tracked contour as the object deforms. The proposed solution achieves a classification rate over all categories of material of up to 98.3%. When integrated in the control loop of a robot hand, it can contribute to ensure stable grasp, and safe manipulation capability that will preserve the physical integrity of the object.
Charles Leek, E; Patterson, Candy; Paul, Matthew A; Rafal, Robert; Cristino, Filipe
This paper reports the first ever detailed study about eye movement patterns during single object recognition in visual agnosia. Eye movements were recorded in a patient with an integrative agnosic deficit during two recognition tasks: common object naming and novel object recognition memory. The patient showed normal directional biases in saccades and fixation dwell times in both tasks and was as likely as controls to fixate within object bounding contour regardless of recognition accuracy. In contrast, following initial saccades of similar amplitude to controls, the patient showed a bias for short saccades. In object naming, but not in recognition memory, the similarity of the spatial distributions of patient and control fixations was modulated by recognition accuracy. The study provides new evidence about how eye movements can be used to elucidate the functional impairments underlying object recognition deficits. We argue that the results reflect a breakdown in normal functional processes involved in the integration of shape information across object structure during the visual perception of shape. Copyright © 2012 Elsevier Ltd. All rights reserved.
Ben Jmaa, Ahmed; Mahdi, Walid; Ben Jemaa, Yousra; Ben Hamadou, Abdelmajid
We present in this paper a new approach for Arabic sign language (ArSL) alphabet recognition using hand gesture analysis. This analysis consists in extracting a histogram of oriented gradient (HOG) features from a hand image and then using them to generate an SVM Models. Which will be used to recognize the ArSL alphabet in real-time from hand gesture using a Microsoft Kinect camera. Our approach involves three steps: (i) Hand detection and localization using a Microsoft Kinect camera, (ii) hand segmentation and (iii) feature extraction using Arabic alphabet recognition. One each input image first obtained by using a depth sensor, we apply our method based on hand anatomy to segment hand and eliminate all the errors pixels. This approach is invariant to scale, to rotation and to translation of the hand. Some experimental results show the effectiveness of our new approach. Experiment revealed that the proposed ArSL system is able to recognize the ArSL with an accuracy of 90.12%.
Clintin P. Davis-Stober
Full Text Available The Recognition Heuristic (Gigerenzer and Goldstein, 1996; Goldstein and Gigerenzer, 2002 makes the counter-intuitive prediction that a decision maker utilizing less information may do as well as, or outperform, an idealized decision maker utilizing more information. We lay a theoretical foundation for the use of single-variable heuristics such as the Recognition Heuristic as an optimal decision strategy within a linear modeling framework. We identify conditions under which over-weighting a single predictor is a mini-max strategy among a class of a priori chosen weights based on decision heuristics with respect to a measure of statistical lack of fit we call ``risk''. These strategies, in turn, outperform standard multiple regression as long as the amount of data available is limited. We also show that, under related conditions, weighting only one variable and ignoring all others produces the same risk as ignoring the single variable and weighting all others. This approach has the advantage of generalizing beyond the original environment of the Recognition Heuristic to situations with more than two choice options, binary or continuous representations of recognition, and to other single variable heuristics. We analyze the structure of data used in some prior recognition tasks and find that it matches the sufficient conditions for optimality in our results. Rather than being a poor or adequate substitute for a compensatory model, the Recognition Heuristic closely approximates an optimal strategy when a decision maker has finite data about the world.
Saarela, Toni P.; Landy, Michael S.
Summary Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several “cues” (color, luminance, texture etc.), and humans can integrate sensory cues to improve detection and recognition [1–3]. Cortical mechanisms fuse information from multiple cues , and shape-selective neural mechanisms can display cue-invariance by responding to a given shape independent of the visual cue defining it [5–8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information . Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10,11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11,12], imaging [13–16], and single-cell and neural population recordings [17,18]. Besides single features, attention can select whole objects [19–21]. Objects are among the suggested “units” of attention because attention to a single feature of an object causes the selection of all of its features [19–21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near-optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. PMID:25802154
Saarela, Toni P; Landy, Michael S
Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several "cues" (color, luminance, texture, etc.), and humans can integrate sensory cues to improve detection and recognition [1-3]. Cortical mechanisms fuse information from multiple cues , and shape-selective neural mechanisms can display cue invariance by responding to a given shape independent of the visual cue defining it [5-8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information . Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10, 11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11, 12], imaging [13-16], and single-cell and neural population recordings [17, 18]. Besides single features, attention can select whole objects [19-21]. Objects are among the suggested "units" of attention because attention to a single feature of an object causes the selection of all of its features [19-21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. Copyright © 2015 Elsevier Ltd. All rights reserved.
Arata, Jumpei; Hattori, Masashi; Ichikawa, Shohei; Sakaguchi, Masamichi
The rubber hand illusion is a well-known multisensory illusion. In brief, watching a rubber hand being stroked by a paintbrush while one's own unseen hand is synchronously stroked causes the rubber hand to be attributed to one's own body and to "feel like it's my hand." The rubber hand illusion is thought to be triggered by the synchronized tactile stimulation of both the subject's hand and the fake hand. To extend the conventional rubber hand illusion, we introduce robotic technology in the form of a master-slave telemanipulator. The developed one degree-of-freedom master-slave system consists of an exoskeleton master equipped with an optical encoder that is worn on the subject's index finger and a motor-actuated index finger on the rubber hand, which allows the subject to perform unilateral telemanipulation. The moving rubber hand illusion has been studied by several researchers in the past with mechanically connected rigs between the subject's body and the fake limb. The robotic instruments let us investigate the moving rubber hand illusion with less constraints, thus behaving closer to the classic rubber hand illusion. In addition, the temporal delay between the body and the fake limb can be precisely manipulated. The experimental results revealed that the robotic instruments significantly enhance the rubber hand illusion. The time delay is significantly correlated with the effect of the multisensory illusion, and the effect significantly decreased at time delays over 100 ms. These findings can potentially contribute to the investigations of neural mechanisms in the field of neuroscience and of master-slave systems in the field of robotics.
Klokker, Louise; Terwee, Caroline; Wæhrens, Eva Elisabet Ejlersen
INTRODUCTION: There is no consensus about what constitutes the most appropriate patient-reported outcome measurement (PROM) instrument for measuring physical function in patients with rheumatic hand conditions. Existing instruments lack psychometric testing and vary in feasibility...... and their psychometric qualities. We aim to develop a PROM instrument to assess hand-related physical function in rheumatic hand conditions. METHODS AND ANALYSIS: We will perform a systematic search to identify existing PROMs to rheumatic hand conditions, and select items relevant for hand-related physical function...... as well as those items from the Patient Reported Outcomes Measurement Information System (PROMIS) Physical Function (PF) item bank that are relevant to patients with rheumatic hand conditions. Selection will be based on consensus among reviewers. Content validity of selected items will be established...
Klokker, Louise; Terwee, Caroline B; Wæhrens, Eva Ejlersen
as well as those items from the Patient Reported Outcomes Measurement Information System (PROMIS) Physical Function (PF) item bank that are relevant to patients with rheumatic hand conditions. Selection will be based on consensus among reviewers. Content validity of selected items will be established......INTRODUCTION: There is no consensus about what constitutes the most appropriate patient-reported outcome measurement (PROM) instrument for measuring physical function in patients with rheumatic hand conditions. Existing instruments lack psychometric testing and vary in feasibility...... and their psychometric qualities. We aim to develop a PROM instrument to assess hand-related physical function in rheumatic hand conditions. METHODS AND ANALYSIS: We will perform a systematic search to identify existing PROMs to rheumatic hand conditions, and select items relevant for hand-related physical function...
Are all categories of objects recognized in the same manner visually? Evidence from neuropsychology suggests they are not: some brain damaged patients are more impaired in recognizing natural objects than artefacts whereas others show the opposite impairment. Category-effects have also been...... demonstrated in neurologically intact subjects, but the findings are contradictory and there is no agreement as to why category-effects arise. This article presents a Pre-semantic Account of Category Effects (PACE) in visual object recognition. PACE assumes two processing stages: shape configuration (the...... binding of shape elements into elaborate shape descriptions) and selection (among competing representations in visual long-term memory), which are held to be differentially affected by the structural similarity between objects. Drawing on evidence from clinical studies, experimental studies...
This thesis is based on seven published papers. The majority of the papers address two topics in visual object recognition: (i) category-effects at pre-semantic stages, and (ii) the integration of visual elements into elaborate shape descriptions corresponding to whole objects or large object parts...... (shape configuration). In the early writings these two topics were examined more or less independently. In later works, findings concerning category-effects and shape configuration merge into an integrated model, termed RACE, advanced to explain category-effects arising at pre-semantic stages in visual...... in visual long-term memory. In the thesis it is described how this simple model can account for a wide range of findings on category-specificity in both patients with brain damage and normal subjects. Finally, two hypotheses regarding the neural substrates of the model's components - and how activation...
Full Text Available In this paper the author discusses the views and statements of the French football player Thierry Henry he gave after his illegal play during the playoff match between France and the Republic of Ireland to claim one of the final spots in the World Cup 2010 in South Africa. First, by controlling the ball with his hand before passing it on for the goal Henry has shown disregard for the constitutive rules of football. Then, by stating that he is "not a referee" he demonstrated that for some players rules are not inherent to football and that they can be relativized, given that for them winning is the goal of the highest ontological status. Furthermore, he has rejected the rules of sportsmanship, thus expressing his opinion that the opponents are just obstacles which have to be removed in order to achieve your goals. Henry's action has disrupted major moral values, such as justice, honesty, responsibility and beneficence. The rules of fair play have totally been ignored both in Henry's action and in the Football Association of France's unwillingness to comment on whether a replay should take place. They have ignored one of the basic principles stated in the "Declaration of the International Fair Play Committee", according to which, fair play is much more than playing to the rules of the game; it's about the attitude of the sportsperson. It's about respecting your opponent and preserving his or her physical and psychological integrity. Finally, the author believes that the rules, moral values and fair play in football are required for this game to become actually possible to play
Full Text Available In this paper the author discusses the views and statements of the French football player Thierry Henry he gave after his illegal play during the playoff match between France and the Republic of Ireland to claim one of the final spots in the World Cup 2010 in South Africa. First, by controlling the ball with his hand before passing it on for the goal Henry has shown disregard for the constitutive rules of football. Then, by stating that he is "not a referee" he demonstrated that for some players rules are not inherent to football and that they can be relativized, given that for them winning is the goal of the highest ontological status. Furthermore, he has rejected the rules of sportsmanship, thus expressing his opinion that the opponents are just obstacles which have to be removed in order to achieve your goals. Henry's action has disrupted major moral values, such as justice, honesty, responsibility and beneficence. The rules of fair play have totally been ignored both in Henry's action and in the Football Association of France's unwillingness to comment on whether a replay should take place. They have ignored one of the basic principles stated in the "Declaration of the International Fair Play Committee", according to which, fair play is much more than playing to the rules of the game; it's about the attitude of the sportsperson. It's about respecting your opponent and preserving his or her physical and psychological integrity. Finally, the author believes that the rules, moral values and fair play in football are required for this game to become actually possible to play.
Alyuz, Nese; Gökberk, B.; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; Akarun, Lale
Facial occlusions pose significant problems for automatic face recognition systems. In this work, we propose a novel occlusion-resistant three-dimensional (3D) facial identification system. We show that, under extreme occlusions due to hair, hands, and eyeglasses, typical 3D face recognition systems
Russell, Richard; Chatterjee, Garga; Nakayama, Ken
Face recognition by normal subjects depends in roughly equal proportions on shape and surface reflectance cues, while object recognition depends predominantly on shape cues. It is possible that developmental prosopagnosics are deficient not in their ability to recognize faces per se, but rather in their ability to use reflectance cues. Similarly, super-recognizers' exceptional ability with face recognition may be a result of superior surface reflectance perception and memory. We tested this possibility by administering tests of face perception and face recognition in which only shape or reflectance cues are available to developmental prosopagnosics, super-recognizers, and control subjects. Face recognition ability and the relative use of shape and pigmentation were unrelated in all the tests. Subjects who were better at using shape or reflectance cues were also better at using the other type of cue. These results do not support the proposal that variation in surface reflectance perception ability is the underlying cause of variation in face recognition ability. Instead, these findings support the idea that face recognition ability is related to neural circuits using representations that integrate shape and pigmentation information. Copyright © 2011 Elsevier Ltd. All rights reserved.
Full Text Available It has been shown that mental rotation of objects and human body parts is processed differently in the human brain. But what about body parts belonging to other primates? Does our brain process this information like any other object or does it instead maximize the structural similarities with our homologous body parts? We tried to answer this question by measuring the manual reaction time (MRT of human participants discriminating the handedness of drawings representing the hands of four anthropoid primates (orangutan, chimpanzee, gorilla, and human. Twenty-four right-handed volunteers (13 males and 11 females were instructed to judge the handedness of a hand drawing in palm view by pressing a left/right key. The orientation of hand drawings varied from 0º (fingers upwards to 90º lateral (fingers pointing away from the midline, 180º (fingers downwards and 90º medial (finger towards the midline. The results showed an effect of rotation angle (F(3, 69 = 19.57, P < 0.001, but not of hand identity, on MRTs. Moreover, for all hand drawings, a medial rotation elicited shorter MRTs than a lateral rotation (960 and 1169 ms, respectively, P < 0.05. This result has been previously observed for drawings of the human hand and related to biomechanical constraints of movement performance. Our findings indicate that anthropoid hands are essentially equivalent stimuli for handedness recognition. Since the task involves mentally simulating the posture and rotation of the hands, we wondered if "mirror neurons" could be involved in establishing the motor equivalence between the stimuli and the participants' own hands.
Tsakiris, M.; Haggard, P.; Franck, N.; Mainy, N.; Sirigu, A.
We investigated the specific contribution of efferent information in a self-recognition task. Subjects experienced a passive extension of the right index finger, either as an effect of moving their left hand via a lever ('self-generated action'), or imposed externally by the experimenter ('externally-generated action'). The visual feedback was…
Rosa, Christine; Lassonde, Maryse; Pinard, Claudine; Keenan, Julian Paul; Belin, Pascal
Three experiments investigated functional asymmetries related to self-recognition in the domain of voices. In Experiment 1, participants were asked to identify one of three presented voices (self, familiar or unknown) by responding with either the right or the left-hand. In Experiment 2, participants were presented with auditory morphs between the…
Selmeczy, Diana; Dobbins, Ian G.
The Remember/Know procedure, developed by Tulving (1985) to capture the distinction between the conscious correlates of episodic and semantic retrieval, has spawned considerable research and debate. However, only a handful of reports have examined the recognition content beyond this dichotomous simplification. To address this, we collected…
In our work the verification performance of a biometric recognition system based on grip patterns, as part of a smart gun for use by the police ocers, has been investigated. The biometric features are extracted from a two-dimensional pattern of the pressure, exerted on the grip of a gun by the hand
No milestone has proven as elusive as the always-approaching "year of the LAN," but the "year of the scanner" might claim the silver medal. Desktop scanners have been around almost as long as personal computers. And everyone thinks they are used for obvious desktop-publishing and business tasks like scanning business documents, magazine articles and other pages, and translating those words into files your computer understands. But, until now, the reality fell far short of the promise. Because it's true that scanners deliver an accurate image of the page to your computer, but the software to recognize this text has been woefully disappointing. Old optical-character recognition (OCR) software recognized such a limited range of pages as to be virtually useless to real users. (For example, one OCR vendor specified 12-point Courier font from an IBM Selectric typewriter: the same font in 10-point, or from a Diablo printer, was unrecognizable!) Computer dealers have told me the chasm between OCR expectations and reality is so broad and deep that nine out of ten prospects leave their stores in disgust when they learn the limitations. And this is a very important, very unfortunate gap. Because the promise of recognition -- what people want it to do -- carries with it tremendous improvements in our productivity and ability to get tons of written documents into our computers where we can do real work with it. The good news is that a revolutionary new development effort has led to the new technology of "page recognition," which actually does deliver the promise we've always wanted from OCR. I'm sure every reader appreciates the breakthrough represented by the laser printer and page-makeup software, a combination so powerful it created new reasons for buying a computer. A similar breakthrough is happening right now in page recognition: the Macintosh (and, I must admit, other personal computers) equipped with a moderately priced scanner and OmniPage software (from Caere
Boucher, Vincent; Marchetti, Mario; Dumoulin, Jean; Cord, Aurélien
Fog conditions are the cause of severe car accidents in western countries because of the poor induced visibility. Its forecast and intensity are still very difficult to predict by weather services. Infrared cameras allow to detect and to identify objects in fog while visibility is too low for eye detection. Over the past years, the implementation of cost effective infrared cameras on some vehicles has enabled such detection. On the other hand pattern recognition algorithms based on Canny filters and Hough transformation are a common tool applied to images. Based on these facts, a joint research program between IFSTTAR and Cerema has been developed to study the benefit of infrared images obtained in a fog tunnel during its natural dissipation. Pattern recognition algorithms have been applied, specifically on road signs which shape is usually associated to a specific meaning (circular for a speed limit, triangle for an alert, …). It has been shown that road signs were detected early enough in images, with respect to images in the visible spectrum, to trigger useful alerts for Advanced Driver Assistance Systems.
Full Text Available Road sign detection and recognition is a significant and challenging issue not only for assisting drivers but also navigating mobile robots. In this paper, we propose a novel and fast approach for the automatic detection and recognition of road signs. First, we use Hue Saturation Intensity (HSI color space to segment the road signs color. And then we locate the road signs based on the geometry symmetry, as almost all the shapes of road sign shapes are symmetrical such circle, rectangle, triangle and octagon. The proposed shape feature is further applied to classify the shape initially. Finally, the road signs are exactly recognized by support vector machine (SVM classifiers. We test our proposed method on real road images and the experimental results show that it can detect and recognize road signs rapidly and accurately.
El Chafei, Cherif
This study describes a system of automatic speaker recognition using the pitch of the voice. The pre-treatment consists in the extraction of the speakers' discriminating characteristics taken from the pitch. The programme of recognition gives, firstly, a preselection and then calculates the distance between the speaker's characteristics to be recognized and those of the speakers already recorded. An experience of recognition has been realized. It has been undertaken with 15 speakers and included 566 tests spread over an intermittent period of four months. The discriminating characteristics used offer several interesting qualities. The algorithms concerning the measure of the characteristics on one hand, the speakers' classification on the other hand, are simple. The results obtained in real time with a minicomputer are satisfactory. Furthermore they probably could be improved if we considered other speaker's discriminating characteristics but this was unfortunately not in our possibilities. (author) [fr
Qi, Yan-nan; Lü, Cheng-xu; Zhang, Jun-ning; Li, Ya-shuo; Zeng, Zhen; Mao, Wen-hua; Jiang, Han-lu; Yang, Bing-nan
Objective: Chinese potato staple food strategy clearly pointed out the need to improve potato processing, while the bottleneck of this strategy is technology and equipment of selection of appropriate raw and processed potato. The purpose of this paper is to summarize the advanced raw and processed potato detection methods. Method: According to consult research literatures in the field of image recognition based potato quality detection, including the shape, weight, mechanical damage, germination, greening, black heart, scab potato etc., the development and direction of this field were summarized in this paper. Result: In order to obtain whole potato surface information, the hardware was built by the synchronous of image sensor and conveyor belt to achieve multi-angle images of a single potato. Researches on image recognition of potato shape are popular and mature, including qualitative discrimination on abnormal and sound potato, and even round and oval potato, with the recognition accuracy of more than 83%. Weight is an important indicator for potato grading, and the image classification accuracy presents more than 93%. The image recognition of potato mechanical damage focuses on qualitative identification, with the main affecting factors of damage shape and damage time. The image recognition of potato germination usually uses potato surface image and edge germination point. Both of the qualitative and quantitative detection of green potato have been researched, currently scab and blackheart image recognition need to be operated using the stable detection environment or specific device. The image recognition of processed potato mainly focuses on potato chips, slices and fries, etc. Conclusion: image recognition as a food rapid detection tool have been widely researched on the area of raw and processed potato quality analyses, its technique and equipment have the potential for commercialization in short term, to meet to the strategy demand of development potato as
Full Text Available Tactile sensors, because of their intrinsic insensitivity to lighting conditions and water turbidity, provide promising opportunities for augmenting the capabilities of vision sensors in applications involving object recognition and localization. This paper presents two approaches for haptic object recognition and localization for ground and underwater environments. The first approach called Batch Ransac and Iterative Closest Point augmented Particle Filter (BRICPPF is based on an innovative combination of particle filters, Iterative-Closest-Point algorithm, and a feature-based Random Sampling and Consensus (RANSAC algorithm for database matching. It can handle a large database of 3D-objects of complex shapes and performs a complete six-degree-of-freedom localization of static objects. The algorithms are validated by experimentation in ground and underwater environments using real hardware. To our knowledge this is the first instance of haptic object recognition and localization in underwater environments. The second approach is biologically inspired, and provides a close integration between exploration and recognition. An edge following exploration strategy is developed that receives feedback from the current state of recognition. A recognition by parts approach is developed which uses the BRICPPF for object sub-part recognition. Object exploration is either directed to explore a part until it is successfully recognized, or is directed towards new parts to endorse the current recognition belief. This approach is validated by simulation experiments.
Guo, Hansong; Huang, He; Huang, Liusheng; Sun, Yu-E
As the size of smartphone touchscreens has become larger and larger in recent years, operability with a single hand is getting worse, especially for female users. We envision that user experience can be significantly improved if smartphones are able to recognize the current operating hand, detect the hand-changing process and then adjust the user interfaces subsequently. In this paper, we proposed, implemented and evaluated two novel systems. The first one leverages the user-generated touchscreen traces to recognize the current operating hand, and the second one utilizes the accelerometer and gyroscope data of all kinds of activities in the user’s daily life to detect the hand-changing process. These two systems are based on two supervised classifiers constructed from a series of refined touchscreen trace, accelerometer and gyroscope features. As opposed to existing solutions that all require users to select the current operating hand or confirm the hand-changing process manually, our systems follow much more convenient and practical methods and allow users to change the operating hand frequently without any harm to the user experience. We conduct extensive experiments on Samsung Galaxy S4 smartphones, and the evaluation results demonstrate that our proposed systems can recognize the current operating hand and detect the hand-changing process with 94.1% and 93.9% precision and 94.1% and 93.7% True Positive Rates (TPR) respectively, when deciding with a single touchscreen trace or accelerometer-gyroscope data segment, and the False Positive Rates (FPR) are as low as 2.6% and 0.7% accordingly. These two systems can either work completely independently and achieve pretty high accuracies or work jointly to further improve the recognition accuracy. PMID:27556461
Ruoff, Carl F. (Inventor); Salisbury, Kenneth, Jr. (Inventor)
A robotic hand is presented having a plurality of fingers, each having a plurality of joints pivotally connected one to the other. Actuators are connected at one end to an actuating and control mechanism mounted remotely from the hand and at the other end to the joints of the fingers for manipulating the fingers and passing externally of the robot manipulating arm in between the hand and the actuating and control mechanism. The fingers include pulleys to route the actuators within the fingers. Cable tension sensing structure mounted on a portion of the hand are disclosed, as is covering of the tip of each finger with a resilient and pliable friction enhancing surface.
Cosimo Della Santina
Full Text Available Humans are able to intuitively exploit the shape of an object and environmental constraints to achieve stable grasps and perform dexterous manipulations. In doing that, a vast range of kinematic strategies can be observed. However, in this work we formulate the hypothesis that such ability can be described in terms of a synergistic behavior in the generation of hand postures, i.e., using a reduced set of commonly used kinematic patterns. This is in analogy with previous studies showing the presence of such behavior in different tasks, such as grasping. We investigated this hypothesis in experiments performed by six subjects, who were asked to grasp objects from a flat surface. We quantitatively characterized hand posture behavior from a kinematic perspective, i.e., the hand joint angles, in both pre-shaping and during the interaction with the environment. To determine the role of tactile feedback, we repeated the same experiments but with subjects wearing a rigid shell on the fingertips to reduce cutaneous afferent inputs. Results show the persistence of at least two postural synergies in all the considered experimental conditions and phases. Tactile impairment does not alter significantly the first two synergies, and contact with the environment generates a change only for higher order Principal Components. A good match also arises between the first synergy found in our analysis and the first synergy of grasping as quantified by previous work. The present study is motivated by the interest of learning from the human example, extracting lessons that can be applied in robot design and control. Thus, we conclude with a discussion on implications for robotics of our findings.
“The Human Hand as an Inspiration for Robot Hand Development” presents an edited collection of authoritative contributions in the area of robot hands. The results described in the volume are expected to lead to more robust, dependable, and inexpensive distributed systems such as those endowed with complex and advanced sensing, actuation, computation, and communication capabilities. The twenty-four chapters discuss the field of robotic grasping and manipulation viewed in light of the human hand’s capabilities and push the state-of-the-art in robot hand design and control. Topics discussed include human hand biomechanics, neural control, sensory feedback and perception, and robotic grasp and manipulation. This book will be useful for researchers from diverse areas such as robotics, biomechanics, neuroscience, and anthropologists.
Jain, Lalit Prithviraj
Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An obvious way to approach such problems is to develop a recognition system that thresholds probabilities to reject unknown classes. Traditional rejection techniques are not about the unknown; they are about the uncertain boundary and rejection around that boundary. Thus traditional techniques only represent the "known unknowns". However, a proper open set recognition algorithm is needed to reduce the risk from the "unknown unknowns". This dissertation examines this concept and finds existing probabilistic multi-class recognition approaches are ineffective for true open set recognition. We hypothesize the cause is due to weak adhoc assumptions combined with closed-world assumptions made by existing calibration techniques. Intuitively, if we could accurately model just the positive data for any known class without overfitting, we could reject the large set of unknown classes even under this assumption of incomplete class knowledge. For this, we formulate the problem as one of modeling positive training data by invoking statistical extreme value theory (EVT) near the decision boundary of positive data with respect to negative data. We provide a new algorithm called the PI-SVM for estimating the unnormalized posterior probability of class inclusion. This dissertation also introduces a new open set recognition model called Compact Abating Probability (CAP), where the probability of class membership decreases in value (abates) as points move from known data toward open space. We show that CAP models improve open set recognition for multiple algorithms. Leveraging the CAP formulation, we go on to describe the novel Weibull-calibrated SVM (W-SVM) algorithm, which combines the useful properties of statistical EVT for score calibration with one-class and binary
Shuzhi Sam Ge
Full Text Available One of the fundamental requirements for an artificial hand to successfully grasp and manipulate an object is to be able to distinguish different objects’ shapes and, more specifically, the objects’ surface curvatures. In this study, we investigate the possibility of enhancing the curvature detection of embedded tactile sensors by proposing a ridged fingertip structure, simulating human fingerprints. In addition, a curvature detection approach based on machine learning methods is proposed to provide the embedded sensors with the ability to discriminate the surface curvature of different objects. For this purpose, a set of experiments were carried out to collect tactile signals from a 2 × 2 tactile sensor array, then the signals were processed and used for learning algorithms. To achieve the best possible performance for our machine learning approach, three different learning algorithms of Naïve Bayes (NB, Artificial Neural Networks (ANN, and Support Vector Machines (SVM were implemented and compared for various parameters. Finally, the most accurate method was selected to evaluate the proposed skin structure in recognition of three different curvatures. The results showed an accuracy rate of 97.5% in surface curvature discrimination.
Genovese, Angelo; Scotti, Fabio
This book examines the context, motivation and current status of biometric systems based on the palmprint, with a specific focus on touchless and less-constrained systems. It covers new technologies in this rapidly evolving field and is one of the first comprehensive books on palmprint recognition systems.It discusses the research literature and the most relevant industrial applications of palmprint biometrics, including the low-cost solutions based on webcams. The steps of biometric recognition are described in detail, including acquisition setups, algorithms, and evaluation procedures. Const
Cuevas, Erik; Perez-Cisneros, Marco
This book presents the use of efficient Evolutionary Computation (EC) algorithms for solving diverse real-world image processing and pattern recognition problems. It provides an overview of the different aspects of evolutionary methods in order to enable the reader in reaching a global understanding of the field and, in conducting studies on specific evolutionary techniques that are related to applications in image processing and pattern recognition. It explains the basic ideas of the proposed applications in a way that can also be understood by readers outside of the field. Image processing and pattern recognition practitioners who are not evolutionary computation researchers will appreciate the discussed techniques beyond simple theoretical tools since they have been adapted to solve significant problems that commonly arise on such areas. On the other hand, members of the evolutionary computation community can learn the way in which image processing and pattern recognition problems can be translated into an...
Liu, Honghai; Ji, Xiaofei; Chan, Chee Seng; Khoury, Mehdi
This book introduces readers to the latest exciting advances in human motion sensing and recognition, from the theoretical development of fuzzy approaches to their applications. The topics covered include human motion recognition in 2D and 3D, hand motion analysis with contact sensors, and vision-based view-invariant motion recognition, especially from the perspective of Fuzzy Qualitative techniques. With the rapid development of technologies in microelectronics, computers, networks, and robotics over the last decade, increasing attention has been focused on human motion sensing and recognition in many emerging and active disciplines where human motions need to be automatically tracked, analyzed or understood, such as smart surveillance, intelligent human-computer interaction, robot motion learning, and interactive gaming. Current challenges mainly stem from the dynamic environment, data multi-modality, uncertain sensory information, and real-time issues. These techniques are shown to effectively address the ...
Carøe, Tanja K; Ebbehøj, Niels E; Bonde, Jens P
BACKGROUND: Occupational hand eczema and/or contact urticaria may have social consequences such as change of profession or not remaining in the workforce. OBJECTIVES: To identify factors associated with job change in a cohort of participants with recognised occupational hand eczema....../contact urticaria METHODS: A registry-based study including 2703 employees with recognised occupational hand eczema/contact urticaria in Denmark in 2010/2011. Four to five years later the participants received a follow-up questionnaire, comprising questions on current job situation (response rate 58.0%). RESULTS...... to specific professions, cleaning personnel changed profession significantly more often than other workers [71.4% (OR = 2.26)], health care workers significantly less often than other workers [34.0% (OR = 0.36)]. CONCLUSION: Job change occurs frequently during the first years after recognition of occupational...
Pal, Sankar K; Ganivada, Avatharam
This book provides a uniform framework describing how fuzzy rough granular neural network technologies can be formulated and used in building efficient pattern recognition and mining models. It also discusses the formation of granules in the notion of both fuzzy and rough sets. Judicious integration in forming fuzzy-rough information granules based on lower approximate regions enables the network to determine the exactness in class shape as well as to handle the uncertainties arising from overlapping regions, resulting in efficient and speedy learning with enhanced performance. Layered network and self-organizing analysis maps, which have a strong potential in big data, are considered as basic modules,. The book is structured according to the major phases of a pattern recognition system (e.g., classification, clustering, and feature selection) with a balanced mixture of theory, algorithm, and application. It covers the latest findings as well as directions for future research, particularly highlighting bioinf...
Conclusion: Giant lipomas of the hand are very rare and may cause compressions and other complications. Thus, they require a careful preoperative evaluation in order to make a proper differential diagnosis. [Hand Microsurg 2015; 4(1.000: 8-11
Lynde, Charles; Guenther, Lyn; Diepgen, Thomas L
Hand dermatitis (HD) is one of the most common skin conditions; however, it is not a homogeneous disease entity. The severity of HD may range from very mild cases to severe chronic forms, which may result in prolonged disability and, occasionally, refractory HD. Chronic hand dermatitis (CHD...
Hand, foot, and mouth disease is a contagious illness that mainly affects children under five. In this podcast, Dr. Eileen Schneider talks about the symptoms of hand, foot, and mouth disease, how it spreads, and ways to help protect yourself and your children from getting infected with the virus.
Solís-V., J.-Francisco; Toxqui-Quitl, Carina; Martínez-Martínez, David; H.-G., Margarita
This work presents a framework designed for the Mexican Sign Language (MSL) recognition. A data set was recorded with 24 static signs from the MSL using 5 different versions, this MSL dataset was captured using a digital camera in incoherent light conditions. Digital Image Processing was used to segment hand gestures, a uniform background was selected to avoid using gloved hands or some special markers. Feature extraction was performed by calculating normalized geometric moments of gray scaled signs, then an Artificial Neural Network performs the recognition using a 10-fold cross validation tested in weka, the best result achieved 95.83% of recognition rate.
The present invention relates to an airfoil shaped body with a leading edge and a trailing edge extending along the longitudinal extension of the body and defining a profile chord, the airfoil shaped body comprising an airfoil shaped facing that forms the outer surface of the airfoil shaped body...
Cure, Laila; Van Enk, Richard
Hand hygiene is the most important intervention to prevent infection in hospitals. Health care workers should clean their hands at least before and after contact with patients. Hand sanitizer dispensers are important to support hand hygiene because they can be made available throughout hospital units. The aim of this study was to determine whether the usability of sanitizer dispensers correlates with compliance of staff in using the sanitizer in a hospital. This study took place in a Midwest, 404-bed, private, nonprofit community hospital with 15 inpatient care units in addition to several ambulatory units. The usability and standardization of sanitizers in 12 participating inpatient units were evaluated. The hospital measured compliance of staff with hand hygiene as part of their quality improvement program. Data from 2010-2012 were analyzed to measure the relationship between compliance and usability using mixed-effects logistic regression models. The total usability score (P = .0046), visibility (P = .003), and accessibility of the sanitizer on entrance to the patient room (P = .00055) were statistically associated with higher observed compliance rates. Standardization alone showed no significant impact on observed compliance (P = .37). Hand hygiene compliance can be influenced by visibility and accessibility of dispensers. The sanitizer location should be part of multifaceted interventions to improve hand hygiene. Copyright © 2015 Association for Professionals in Infection Control and Epidemiology, Inc. Published by Elsevier Inc. All rights reserved.
This paper reviews clinical neuropsychological studies that have indicated that the recognition of a person's identity and the recognition of facial expressions are processed by different cortical and subcortical areas of the brain. The fusiform gyrus, especially the right fusiform gyrus, plays an important role in the recognition of identity. The superior temporal sulcus, amygdala, and medial frontal cortex play important roles in facial-expression recognition. Both facial recognition and facial-expression recognition are highly intellectual processes that involve several regions of the brain.
Full Text Available Avulsion of skin from the hand or fingers is an injury that has a dramatic presentation. The entire musculo-skeletal unit of the finger is intact, and the patient can often move the parts of his naked hand quite normally. The challenge for the reconstructive surgeon lies in resurfacing the hand or finger with a good quality pliable sensate skin cover while preserving the movements and function of the hand. Traditionally, skin grafting has been the standard method of reconstruction in such injuries. However, skin grafting does have many disadvantages, too. This article deals with the features of such injuries, management protocols and other reconstructive options available in the armamentarium of the hand surgeon.
Pizarro, Yaritzmar Rosario; Schuler, Jason M.; Lippitt, Thomas C.
Dexterous robotic hands are changing the way robots and humans interact and use common tools. Unfortunately, the complexity of the joints and actuations drive up the manufacturing cost. Some cutting edge and commercially available rapid prototyping machines now have the ability to print multiple materials and even combine these materials in the same job. A 3D model of a robotic hand was designed using Creo Parametric 2.0. Combining "hard" and "soft" materials, the model was printed on the Object Connex350 3D printer with the purpose of resembling as much as possible the human appearance and mobility of a real hand while needing no assembly. After printing the prototype, strings where installed as actuators to test mobility. Based on printing materials, the manufacturing cost of the hand was $167, significantly lower than other robotic hands without the actuators since they have more complex assembly processes.
Kivell, Tracy L.; Deane, Andrew S.; Tocheri, Matthew W.; Orr, Caley M.; Schmid, Peter; Hawks, John; Berger, Lee R.; Churchill, Steven E.
A nearly complete right hand of an adult hominin was recovered from the Rising Star cave system, South Africa. Based on associated hominin material, the bones of this hand are attributed to Homo naledi. This hand reveals a long, robust thumb and derived wrist morphology that is shared with Neandertals and modern humans, and considered adaptive for intensified manual manipulation. However, the finger bones are longer and more curved than in most australopiths, indicating frequent use of the hand during life for strong grasping during locomotor climbing and suspension. These markedly curved digits in combination with an otherwise human-like wrist and palm indicate a significant degree of climbing, despite the derived nature of many aspects of the hand and other regions of the postcranial skeleton in H. naledi. PMID:26441219
Wilson, Thomas S.; Bearinger, Jane P.
New shape memory polymer compositions, methods for synthesizing new shape memory polymers, and apparatus comprising an actuator and a shape memory polymer wherein the shape memory polymer comprises at least a portion of the actuator. A shape memory polymer comprising a polymer composition which physically forms a network structure wherein the polymer composition has shape-memory behavior and can be formed into a permanent primary shape, re-formed into a stable secondary shape, and controllably actuated to recover the permanent primary shape. Polymers have optimal aliphatic network structures due to minimization of dangling chains by using monomers that are symmetrical and that have matching amine and hydroxl groups providing polymers and polymer foams with clarity, tight (narrow temperature range) single transitions, and high shape recovery and recovery force that are especially useful for implanting in the human body.
Wilson, Thomas S.; Bearinger, Jane P.
New shape memory polymer compositions, methods for synthesizing new shape memory polymers, and apparatus comprising an actuator and a shape memory polymer wherein the shape memory polymer comprises at least a portion of the actuator. A shape memory polymer comprising a polymer composition which physically forms a network structure wherein the polymer composition has shape-memory behavior and can be formed into a permanent primary shape, re-formed into a stable secondary shape, and controllably actuated to recover the permanent primary shape. Polymers have optimal aliphatic network structures due to minimization of dangling chains by using monomers that are symmetrical and that have matching amine and hydroxyl groups providing polymers and polymer foams with clarity, tight (narrow temperature range) single transitions, and high shape recovery and recovery force that are especially useful for implanting in the human body.
Walther, Dirk; Itti, Laurent; Riesenhuber, Maximilian; Poggio, Tomaso; Koch, Christof
...% at a high level is sufficient to recognize multiple objects. To determine the size and shape of the region to be modulated, a rough segmentation is performed, based on pre-attentive features already computed to guide attention. Testing with synthetic and natural stimuli demonstrates that our new approach to attentional selection for recognition yields encouraging results in addition to being biologically plausible.
Converso, L.; Hocek, S.
This paper describes computer-based optical character recognition (OCR) systems, focusing on their components (the computer, the scanner, the OCR, and the output device); how the systems work; and features to consider in selecting a system. A list of 26 questions to ask to evaluate systems for potential purchase is included. (JDD)
Perepelitsa, VA; Sergienko, [No Value; Kochkarov, AM
Definitions of prefractal and fractal graphs are introduced, and they are used to formulate mathematical models in different fields of knowledge. The topicality of fractal-graph recognition from the point of view, of fundamental improvement in the efficiency of the solution of algorithmic problems
Full Text Available Despite the existence of various biometric techniques, like fingerprints, iris scan, as well as hand geometry, the most efficient and more widely-used one is face recognition. This is because it is inexpensive, non-intrusive and natural. Therefore, researchers have developed dozens of face recognition techniques over the last few years. These techniques can generally be divided into three categories, based on the face data processing methodology. There are methods that use the entire face as input data for the proposed recognition system, methods that do not consider the whole face, but only some features or areas of the face and methods that use global and local face characteristics simultaneously. In this paper, we present an overview of some well-known methods in each of these categories. First, we expose the benefits of, as well as the challenges to the use of face recognition as a biometric tool. Then, we present a detailed survey of the well-known methods by expressing each method’s principle. After that, a comparison between the three categories of face recognition techniques is provided. Furthermore, the databases used in face recognition are mentioned, and some results of the applications of these methods on face recognition databases are presented. Finally, we highlight some new promising research directions that have recently appeared.
Crenna, F; Bovio, L; Rossi, G B; Zappa, E; Testa, R; Gasparetto, M
Automatic face recognition is a biometric technique particularly appreciated in security applications. In fact face recognition presents the opportunity to operate at a low invasive level without the collaboration of the subjects under tests, with face images gathered either from surveillance systems or from specific cameras located in strategic points. The automatic recognition algorithms perform a measurement, on the face images, of a set of specific characteristics of the subject and provide a recognition decision based on the measurement results. Unfortunately several quantities may influence the measurement of the face geometry such as its orientation, the lighting conditions, the expression and so on, affecting the recognition rate. On the other hand human recognition of face is a very robust process far less influenced by the surrounding conditions. For this reason it may be interesting to insert perceptual aspects in an automatic facial-based recognition algorithm to improve its robustness. This paper presents a first study in this direction investigating the correlation between the results of a perception experiment and the facial geometry, estimated by means of the position of a set of repere points
Fischer, Bernd M.; Helm, Hanspeter; Jepsen, Peter Uhd
In the recent years, there has been an increased interest in the exploitation of the far-infrared spectral region for applications based on chemical recognition. The fact that on the one hand many packaging materials are transparent for THz radiation and on the other hand the THz-spectra of many ...
Nielsen, Birgitte Lund; Réol, Lise Andersen; Laursen, Hilmar Dyrborg
This catalogue of research in the field of SEI programmes for the school staff’s and teachers’ SEI competencies is based on a review performed by the main researchers Birgitte Lund Nielsen, Lise Andersen Réol and Hilmar Dyrborg Laursen, VIA University College, Denmark, but discussed by the entire...... team of Hand in Hand partner countries and researchers. The aim was to identify the central aspects and elements concerning successful implementation, and school staff’s development of professional competencies in the specific field of supporting students’ social, emotional and intercultural (SEI......) competencies. Abstract: Framed by the EU-project Hand in Hand focusing on Social, Emotional and Intercultural (SEI) competencies among students and school staff, the paper discusses implementation and professional competencies based on a research review. The following five topics were identified: 1...
Feragen, Aasa; Lauze, Francois Bernard; Nielsen, Mads
This paper presents a new geometric framework for analysis of planar treelike shapes for applications such as shape matching, recognition and morphology, using the geometry of the space of treelike shapes. Mathematically, the shape space is given the structure of a stratified set which...... is a quotient of a normed vector space with a metric inherited from the vector space norm. We give examples of geodesic paths in tree-space corresponding to fundamental deformations of small trees, and discuss how these deformations are key building blocks for understanding deformations between larger trees....
Senna, Irene; Maravita, Angelo; Bolognini, Nadia; Parise, Cesare V
Our body is made of flesh and bones. We know it, and in our daily lives all the senses constantly provide converging information about this simple, factual truth. But is this always the case? Here we report a surprising bodily illusion demonstrating that humans rapidly update their assumptions about the material qualities of their body, based on their recent multisensory perceptual experience. To induce a misperception of the material properties of the hand, we repeatedly gently hit participants' hand with a small hammer, while progressively replacing the natural sound of the hammer against the skin with the sound of a hammer hitting a piece of marble. After five minutes, the hand started feeling stiffer, heavier, harder, less sensitive, unnatural, and showed enhanced Galvanic skin response (GSR) to threatening stimuli. Notably, such a change in skin conductivity positively correlated with changes in perceived hand stiffness. Conversely, when hammer hits and impact sounds were temporally uncorrelated, participants did not spontaneously report any changes in the perceived properties of the hand, nor did they show any modulation in GSR. In two further experiments, we ruled out that mere audio-tactile synchrony is the causal factor triggering the illusion, further demonstrating the key role of material information conveyed by impact sounds in modulating the perceived material properties of the hand. This novel bodily illusion, the 'Marble-Hand Illusion', demonstrates that the perceived material of our body, surely the most stable attribute of our bodily self, can be quickly updated through multisensory integration.
Ram Prashanth, N.; Siddarth, B.; Ganesh, Anirudh; Naveen Kumar, Vaegae
We come across a large volume of handwritten texts in our daily lives and handwritten character recognition has long been an important area of research in pattern recognition. The complexity of the task varies among different languages and it so happens largely due to the similarity between characters, distinct shapes and number of characters which are all language-specific properties. There have been numerous works on character recognition of English alphabets and with laudable success, but regional languages have not been dealt with very frequently and with similar accuracies. In this paper, we explored the performance of Deep Belief Networks in the classification of Handwritten Tamil vowels, and conclusively compared the results obtained. The proposed method has shown satisfactory recognition accuracy in light of difficulties faced with regional languages such as similarity between characters and minute nuances that differentiate them. We can further extend this to all the Tamil characters.
Oldham, W.J.B.; Downes, P.T.; Hunter, V.
A method for recognition of mammographic lesions through the use of neural networks is presented. Neural networks have exhibited the ability to learn the shape andinternal structure of patterns. Digitized mammograms containing circumscribed and stelate lesions were used to train a feedfoward synchronous neural network that self-organizes to stable attractor states. Encoding of data for submission to the network was accomplished by performing a fractal analysis of the digitized image. This results in scale invariant representation of the lesions. Results are discussed
Daoudi, Mohamed; Veltkamp, Remco
3D Face Modeling, Analysis and Recognition presents methodologies for analyzing shapes of facial surfaces, develops computational tools for analyzing 3D face data, and illustrates them using state-of-the-art applications. The methodologies chosen are based on efficient representations, metrics, comparisons, and classifications of features that are especially relevant in the context of 3D measurements of human faces. These frameworks have a long-term utility in face analysis, taking into account the anticipated improvements in data collection, data storage, processing speeds, and application s
Anna Elisabetta Galeotti's theory of 'toleration as recognition' has been criticised by Peter Jones for being conceptually incoherent, since liberal toleration presupposes a negative attitude to differences, whereas multicultural recognition requires positive affirmation hereof. The paper spells ...
Schools and school districts can get support and recognition for implementation of school IPM. EPA is developing a program to provide recognition for school districts that are working towards or have achieved a level of success with school IPM programs.
Bijlstra, Gijsbert; Holland, Rob W.; Dotsch, Ron; Hugenberg, Kurt; Wigboldus, Daniel H. J.
We investigated whether stereotype associations between specific emotional expressions and social categories underlie stereotypic emotion recognition biases. Across two studies, we replicated previously documented stereotype biases in emotion recognition using both dynamic (Study 1) and static
Sølund, Thomas; Glent Buch, Anders; Krüger, Norbert
geometric groups; concave, convex, cylindrical and flat 3D object models. The object models have varying amount of local geometric features to challenge existing local shape feature descriptors in terms of descriptiveness and robustness. The dataset is validated in a benchmark which evaluates the matching...... performance of 7 different state-of-the-art local shape descriptors. Further, we validate the dataset in a 3D object recognition pipeline. Our benchmark shows as expected that local shape feature descriptors without any global point relation across the surface have a poor matching performance with flat...
Swati Tomar*1 & Amit Kishore2
This paper presents detailed review in the field of Optical Character Recognition. Various techniques are determine that have been proposed to realize the center of character recognition in an optical character recognition system. Even though, sufficient studies and papers are describes the techniques for converting textual content from a paper document into machine readable form. Optical character recognition is a process where the computer understands automatically the image of handwritten ...
Full Text Available Sign in sign language, equivalent to the word, phrase or a sentence in the oral-language, can be divided in linguistic units of lower levels: shape of the hand, place of articulation, type of movement and orientation of the palm. The first description of these units, which today is present and applicable in Bosnia and Herzegovina (B&H, was given by Zimmerman in 1986, who found 27 shapes of hand, while other types were not systematically developed or described. The target of this study was to determine the possible existence of other forms of hand movements present in sign language in B&H. By the method of content analysis, the 425 analyzed signs in sign launguage in B&H, confirmed their existence, but we also discovered and presented 14 new shapes of the hand. This way, we confirmed the need of implementing a detailed research, standardization and publishing of sign language in B&H, which would provide adequate conditions for its study and application, as for the deaf, and all the others who come into direct contact with them.
Tao, Dapeng; Guo, Yanan; Li, Yaotang; Gao, Xinbo
Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.
Dopkins, Stephen; Sargent, Jesse; Ngo, Catherine T.
We explored the effect of superficial priming in episodic recognition and found it to be different from the effect of semantic priming in episodic recognition. Participants made recognition judgments to pairs of items, with each pair consisting of a prime item and a test item. Correct positive responses to the test item were impeded if the prime…
DeWitt, Iain D. J.
Although spoken word recognition is more fundamental to human communication than text recognition, knowledge of word-processing in auditory cortex is comparatively impoverished. This dissertation synthesizes current models of auditory cortex, models of cortical pattern recognition, models of single-word reading, results in phonetics and results in…
Jones, Emily J. H.; Pascalis, Olivier; Eacott, Madeline J.; Herbert, Jane S.
In two experiments, we investigated the development of representational flexibility in visual recognition memory during infancy using the Visual Paired Comparison (VPC) task. In Experiment 1, 6- and 9-month-old infants exhibited recognition when familiarization and test occurred in the same room, but showed no evidence of recognition when…
Ali, Tauseef; Spreeuwers, Lieuwe Jan; Veldhuis, Raymond N.J.; Quaglia, Adamo; Epifano, Calogera M.
The improvements of automatic face recognition during the last 2 decades have disclosed new applications like border control and camera surveillance. A new application field is forensic face recognition. Traditionally, face recognition by human experts has been used in forensics, but now there is a
Ghali, Ahmed; Cunningham, Andrew S.; Pridmore, Tony P.
Stroke is a major cause of disability and health care expenditure around the world. Existing stroke rehabilitation methods can be effective but are costly and need to be improved. Even modest improvements in the effectiveness of rehabilitation techniques could produce large benefits in terms of quality of life. The work reported here is part of an ongoing effort to integrate virtual reality and machine vision technologies to produce innovative stroke rehabilitation methods. We describe a combined object recognition and event detection system that provides real time feedback to stroke patients performing everyday kitchen tasks necessary for independent living, e.g. making a cup of coffee. The image plane position of each object, including the patient"s hand, is monitored using histogram-based recognition methods. The relative positions of hand and objects are then reported to a task monitor that compares the patient"s actions against a model of the target task. A prototype system has been constructed and is currently undergoing technical and clinical evaluation.
Randall C. O'Reilly
Full Text Available How does the brain learn to recognize objects visually, and perform this difficult feat robustly in the face of many sources of ambiguity and variability? We present a computational model based on the biology of the relevant visual pathways that learns to reliably recognize 100 different object categories in the face of of naturally-occurring variability in location, rotation, size, and lighting. The model exhibits robustness to highly ambiguous, partially occluded inputs. Both the unified, biologically plausible learning mechanism and the robustness to occlusion derive from the role that recurrent connectivity and recurrent processing mechanisms play in the model. Furthermore, this interaction of recurrent connectivity and learning predicts that high-level visual representations should be shaped by error signals from nearby, associated brain areas over the course of visual learning. Consistent with this prediction, we show how semantic knowledge about object categories changes the nature of their learned visual representations, as well as how this representational shift supports the mapping between perceptual and conceptual knowledge. Altogether, these findings support the potential importance of ongoing recurrent processing throughout the brain's visual system and suggest ways in which object recognition can be understood in terms of interactions within and between processes over time.
Bemelman, W. A.; de Wit, L. T.; Busch, O. R.; Gouma, D. J.
Laparoscopic splenectomy is performed routinely in patients with small and moderately enlarged spleens at specialized centers. Large spleens are difficult to handle laparoscopically and hand-assisted laparoscopic splenectomy might facilitate the procedure through enhanced vascular control, easier
... Therapist? Media Find a Hand Surgeon Home Anatomy Animal Bites Email to a friend * required fields From * ... key to prevent problems from a bite. CAUSES Animal Bites Millions of animal bites occur in the ...
Jakati, R.K.; Kaptral, R.S.; Ananthkrishnan, T.S.; Pansare, M.G.
In order to make quick measurements of beta and gamma contaminations on hands and feet of personnel working in radioactive environments, hand and foot contamination monitors are widely used. This paper describes such a monitor system designed with Intel 8085 based microcomputer. The monitoring and warning system is designed to perform measurement of activity spread over surface of hands and soles of shoes or feet. Even though the system has many features to aid testing and maintainance operation, it is easy to use for unskilled persons. In order to check the contamination, the person stands on platform and inserts both his hands into detector assemblies thereby actuating the sensing switches. After a preset interval, annunciation of clean or contaminated status is declared by the system. (author)
Xi, Xiaoming; Yang, Gongping; Yin, Yilong; Meng, Xianjing
Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG). For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG.
Full Text Available Finger veins are a promising biometric pattern for personalized identification in terms of their advantages over existing biometrics. Based on the spatial pyramid representation and the combination of more effective information such as gray, texture and shape, this paper proposes a simple but powerful feature, called Pyramid Histograms of Gray, Texture and Orientation Gradients (PHGTOG. For a finger vein image, PHGTOG can reflect the global spatial layout and local details of gray, texture and shape. To further improve the recognition performance and reduce the computational complexity, we select a personalized subset of features from PHGTOG for each subject by using the sparse weight vector, which is trained by using LASSO and called PFS-PHGTOG. We conduct extensive experiments to demonstrate the promise of the PHGTOG and PFS-PHGTOG, experimental results on our databases show that PHGTOG outperforms the other existing features. Moreover, PFS-PHGTOG can further boost the performance in comparison with PHGTOG.
Al-Talabani, Abdulbasit; Sellahewa, Harin; Jassim, Sabah A.
Human emotion recognition from speech is studied frequently for its importance in many applications, e.g. human-computer interaction. There is a wide diversity and non-agreement about the basic emotion or emotion-related states on one hand and about where the emotion related information lies in the speech signal on the other side. These diversities motivate our investigations into extracting Meta-features using the PCA approach, or using a non-adaptive random projection RP, which significantly reduce the large dimensional speech feature vectors that may contain a wide range of emotion related information. Subsets of Meta-features are fused to increase the performance of the recognition model that adopts the score-based LDC classifier. We shall demonstrate that our scheme outperform the state of the art results when tested on non-prompted databases or acted databases (i.e. when subjects act specific emotions while uttering a sentence). However, the huge gap between accuracy rates achieved on the different types of datasets of speech raises questions about the way emotions modulate the speech. In particular we shall argue that emotion recognition from speech should not be dealt with as a classification problem. We shall demonstrate the presence of a spectrum of different emotions in the same speech portion especially in the non-prompted data sets, which tends to be more "natural" than the acted datasets where the subjects attempt to suppress all but one emotion.
Silvestre, Jason; Levin, L Scott; Serletti, Joseph M; Chang, Benjamin
Designing an effective hand rotation for plastic surgery residents is difficult. The authors address this limitation by elucidating the critical components of the hand curriculum during plastic surgery residency. Hand questions on the Plastic Surgery In-Service Training Exam for six consecutive years (2008 to 2013) were characterized by presence of imaging, vignette setting, question taxonomy, answer domain, anatomy, and topic. Answer references were quantified by source and year of publication. Two hundred sixty-six questions were related to hand surgery (22.7 percent of all questions; 44.3 per year) and 61 were accompanied by an image (22.9 percent). Vignettes tended to be clinic- (50.0 percent) and emergency room-based (35.3 percent) (p < 0.001). Questions required decision-making (60.5 percent) over interpretation (25.9 percent) and recall skills (13.5 percent) (p < 0.001). Answers focused on interventions (57.5 percent) over anatomy/pathology (25.2 percent) and diagnoses (17.3 percent) (p < 0.001). Nearly half of the questions focused on the digits. The highest yield topics were trauma (35.3 percent), reconstruction (24.4 percent), and aesthetic and functional problems (14.2 percent). The Journal of Hand Surgery (American volume) (20.5 percent) and Plastic and Reconstructive Surgery (18.0 percent) were the most-cited journals, and the median publication lag was 7 years. Green's Operative Hand Surgery was the most-referenced textbook (41.8 percent). These results will enable trainees to study hand surgery topics with greater efficiency. Faculty can use these results to ensure that tested topics are covered during residency training. Thus, a benchmark is established to improve didactic, clinical, and operative experiences in hand surgery.
Hand, foot, and mouth disease is a contagious illness that mainly affects children under five. In this podcast, Dr. Eileen Schneider talks about the symptoms of hand, foot, and mouth disease, how it spreads, and ways to help protect yourself and your children from getting infected with the virus. Created: 8/8/2013 by National Center for Immunization and Respiratory Diseases (NCIRD). Date Released: 8/8/2013.
Fossataro, Carlotta; Bruno, Valentina; Gindri, Patrizia; Pia, Lorenzo; Berti, Anna; Garbarini, Francesca
The sense of body ownership, i.e., the belief that a specific body part belongs to us, can be selectively impaired in brain-damaged patients. Recently, a pathological form of embodiment has been described in patients who, when the examiner's hand is located in a body-congruent position, systematically claim that it is their own hand (E+ patients). This paradoxical behavior suggests that, in these patients, the altered sense of body ownership also affects their capacity of visually discriminating the body-identity details of the own and the alien hand, even when both hands are clearly visible on the table. Here, we investigated whether, in E+ patients with spared tactile sensibility, a coherent body ownership could be restored by introducing a multisensory conflict between what the patients feel on the own hand and what they see on the alien hand. To this aim, we asked the patients to rate their sense of body ownership over the alien hand, either after segregated tactile stimulations of the own hand (out of view) and of the alien hand (visible) or after synchronous and asynchronous tactile stimulations of both hands, as in the rubber hand illusion set-up. Our results show that, when the tactile sensation perceived on the patient's own hand was in conflict with visual stimuli observed on the examiner's hand, E+ patients noticed the conflict and spontaneously described visual details of the (visible) examiner's hand (e.g., the fingers length, the nails shape, the skin color…), to conclude that it was not their own hand. These data represent the first evidence that, in E+ patients, an incongruent visual-tactile stimulation of the own and of the alien hand reduces, at least transitorily, the delusional body ownership over the alien hand, by restoring the access to the perceptual self-identity system, where visual body identity details are stored. Copyright © 2017 Elsevier Ltd. All rights reserved.
Thonnat , Monique
International audience; Extracting automatically the semantics from visual data is a real challenge. We describe in this paper how recent work in cognitive vision leads to significative results in activity recognition for visualsurveillance and video monitoring. In particular we present work performed in the domain of video understanding in our PULSAR team at INRIA in Sophia Antipolis. Our main objective is to analyse in real-time video streams captured by static video cameras and to recogniz...
Nasrollahi, Kamal; Moeslund, Thomas B.; Rashidi, Maryam
Developing a reliable, fast, and robust biometric recognition system is still a challenging task. This is because the inputs to these systems can be noisy, occluded, poorly illuminated, rotated, and of very low-resolutions. This paper proposes a probabilistic classifier using Haar-like features......, which mostly have been used for detection, for biometric recognition. The proposed system has been tested for three different biometrics: ear, iris, and hand vein patterns and it is shown that it is robust against most of the mentioned degradations and it outperforms state-of-the-art systems...
Gambone, Elisabeth A.
Spacecraft control algorithms must know the expected vehicle response to any command to the available control effectors, such as reaction thrusters or torque devices. Spacecraft control system design approaches have traditionally relied on the estimated vehicle mass properties to determine the desired force and moment, as well as knowledge of the effector performance to efficiently control the spacecraft. A pattern recognition approach was used to investigate the relationship between the control effector commands and spacecraft responses. Instead of supplying the approximated vehicle properties and the thruster performance characteristics, a database of information relating the thruster ring commands and the desired vehicle response was used for closed-loop control. A Monte Carlo simulation data set of the spacecraft dynamic response to effector commands was analyzed to establish the influence a command has on the behavior of the spacecraft. A tool developed at NASA Johnson Space Center to analyze flight dynamics Monte Carlo data sets through pattern recognition methods was used to perform this analysis. Once a comprehensive data set relating spacecraft responses with commands was established, it was used in place of traditional control methods and gains set. This pattern recognition approach was compared with traditional control algorithms to determine the potential benefits and uses.
Shin, David H; Bohn, Deborah K; Agel, Julie; Lindstrom, Katy A; Cronquist, Sara M; Van Heest, Ann E
To measure and compare hand function for children with normal hand development, congenital hand differences (CHD), and neuromuscular disease (NMD) using a function test with touch screen technology designed as an iPhone application. We measured touch screen hand function in 201 children including 113 with normal hand formation, 43 with CHD, and 45 with NMD. The touch screen test was developed on the iOS platform using an Apple iPhone 4. We measured 4 tasks: touching dots on a 3 × 4 grid, dragging shapes, use of the touch screen camera, and typing a line of text. The test takes 60 to 120 seconds and includes a pretest to familiarize the subject with the format. Each task is timed independently and the overall time is recorded. Children with normal hand development took less time to complete all 4 subtests with increasing age. When comparing children with normal hand development with those with CHD or NMD, in children aged less than 5 years we saw minimal differences; those aged 5 to 6 years with CHD took significantly longer total time; those aged 7 to 8 years with NMD took significantly longer total time; those aged 9 to 11 years with CHD took significantly longer total time; and those aged 12 years and older with NMD took significantly longer total time. Touch screen technology has becoming increasingly relevant to hand function in modern society. This study provides standardized age norms and shows that our test discriminates between normal hand development and that in children with CHD or NMD. Diagnostic III. Copyright © 2015 American Society for Surgery of the Hand. Published by Elsevier Inc. All rights reserved.
Statistical tests for intrinsic shapes of elliptical galaxies have given so far inconclusive and sometimes contradictory results. These failures have been often charged to the fact that classical tests consider only the two axisymmetric shapes (oblate versus prolate), while ellipticals are truly triaxial bodies. On the other hand, recent analyses indicate that the class of elliptical galaxies could be a mixture of (at least) two families having different morphology and dynamical behaviour: (i) a family of fast-rotating, disc-like ellipticals (discy); (ii) a family of slow-rotating, box-shaped ellipticals (boxy). In this paper we review the tests for instrinsic shapes of elliptical galaxies using data of better quality (CCD) with respect to previous applications. (author)
Rasmussen, Majken Kirkegård; Pedersen, Esben Warming; Petersen, Marianne Graves
Shape change is increasingly used in physical user interfaces, both as input and output. Yet, the progress made and the key research questions for shape-changing interfaces are rarely analyzed systematically. We review a sample of existing work on shape-changing interfaces to address these shortc......Shape change is increasingly used in physical user interfaces, both as input and output. Yet, the progress made and the key research questions for shape-changing interfaces are rarely analyzed systematically. We review a sample of existing work on shape-changing interfaces to address...... these shortcomings. We identify eight types of shape that are transformed in various ways to serve both functional and hedonic design purposes. Interaction with shape-changing interfaces is simple and rarely merges input and output. Three questions are discussed based on the review: (a) which design purposes may...
Reading, Matthew W.
Technologies for making self-erecting structures are described herein. An exemplary self-erecting structure comprises a plurality of shape-memory members that connect two or more hub components. When forces are applied to the self-erecting structure, the shape-memory members can deform, and when the forces are removed the shape-memory members can return to their original pre-deformation shape, allowing the self-erecting structure to return to its own original shape under its own power. A shape of the self-erecting structure depends on a spatial orientation of the hub components, and a relative orientation of the shape-memory members, which in turn depends on an orientation of joining of the shape-memory members with the hub components.
Clinton S. Wright; Cameron S. Balog; Jeffrey W. Kelly
Dimensions, volume, and biomass were measured for 121 hand-constructed piles composed primarily of coniferous (n = 63) and shrub/hardwood (n = 58) material at sites in Washington and California. Equations using pile dimensions, shape, and type allow users to accurately estimate the biomass of hand piles. Equations for estimating true pile volume from simple geometric...
Neural network (connectionist) models are designed to encode image features and provide the building blocks for object and shape recognition. These models generally call for: a) initial diffuse connections from one neuron population to another, and b) training to bring about a functional change in those connections so that one or more high-tier neurons will selectively respond to a specific shape stimulus. Advanced models provide for translation, size, and rotation invariance. The present dis...
Albertazzi, Liliana; Da Pos, Osvaldo; Canal, Luisa; Micciolo, Rocco; Malfatti, Michela; Vescovi, Massimo
This article presents an experimental study on the naturally biased association between shape and color. For each basic geometric shape studied, participants were asked to indicate the color perceived as most closely related to it, choosing from the Natural Color System Hue Circle. Results show that the choices of color for each shape were not…
Caris, M G; Labuschagne, H A; Dekker, M; Kramer, M H H; van Agtmael, M A; Vandenbroucke-Grauls, C M J E
Hand hygiene is paramount to prevent healthcare-associated infections, but improving compliance is challenging. When healthcare workers seldom encounter healthcare-associated infections, they will consider the odds of causing infections through poor hand hygiene negligible. Cognitive biases such as these may induce non-compliance. Nudging, 'a friendly push to encourage desired behaviour', could provide an easily implemented, inexpensive measure to address cognitive biases and thus support hand hygiene interventions. To investigate whether behavioural nudges, displayed as posters, can increase the use of alcohol-based hand rub. We developed nudges based on a systematic review of previously described cognitive biases, and tested these through a cross-sectional survey among the target audience. We then conducted a controlled before-after trial on two hospital wards, to assess the effect of these nudges on the use of alcohol-based hand rub, measured with electronic dispensers. Poisson regression analyses adjusted for workload showed that nudges displayed next to dispensers increased their overall use on one ward [poster 1: relative risk: 1.6 (95% confidence interval: 1.2-2.2); poster 2: 1.7 (1.2-2.5)] and during doctor's rounds on both wards [poster 1: ward A: 1.7 (1.1-2.6); ward B: 2.2 (1.3-3.8)]. Use of dispensers without adjacent nudges did not increase. Nudges based on cognitive biases that play a role in hand hygiene, and displayed as posters, could provide an easy, inexpensive measure to increase use of alcohol-based hand rub. When applying nudges to change behaviour, it is important to identify the right nudge for the right audience. Copyright © 2017 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.
Bryner, Darshan; Klassen, Eric; Huiling Le; Srivastava, Anuj
Current techniques for shape analysis tend to seek invariance to similarity transformations (rotation, translation, and scale), but certain imaging situations require invariance to larger groups, such as affine or projective groups. Here we present a general Riemannian framework for shape analysis of planar objects where metrics and related quantities are invariant to affine and projective groups. Highlighting two possibilities for representing object boundaries-ordered points (or landmarks) and parameterized curves-we study different combinations of these representations (points and curves) and transformations (affine and projective). Specifically, we provide solutions to three out of four situations and develop algorithms for computing geodesics and intrinsic sample statistics, leading up to Gaussian-type statistical models, and classifying test shapes using such models learned from training data. In the case of parameterized curves, we also achieve the desired goal of invariance to re-parameterizations. The geodesics are constructed by particularizing the path-straightening algorithm to geometries of current manifolds and are used, in turn, to compute shape statistics and Gaussian-type shape models. We demonstrate these ideas using a number of examples from shape and activity recognition.
Full Text Available According to the recognition heuristic (RH theory, decisions follow the recognition principle: Given a high validity of the recognition cue, people should prefer recognized choice options compared to unrecognized ones. Assuming that the memory strength of choice options is strongly correlated with both the choice criterion and recognition judgments, the RH is a reasonable strategy that approximates optimal decisions with a minimum of cognitive effort (Davis-Stober, Dana, and Budescu, 2010. However, theories of recognition memory are not generally compatible with this assumption. For example, some threshold models of recognition presume that recognition judgments can arise from two types of cognitive states: (1 certainty states in which judgments are almost perfectly correlated with memory strength and (2 uncertainty states in which recognition judgments reflect guessing rather than differences in memory strength. We report an experiment designed to test the prediction that the RH applies to certainty states only. Our results show that memory states rather than recognition judgments affect use of recognition information in binary decisions.
Lu, Zhiyuan; Tong, Kai-Yu; Shin, Henry; Li, Sheng; Zhou, Ping
A hand exoskeleton driven by myoelectric pattern recognition was designed for stroke rehabilitation. It detects and recognizes the user's motion intent based on electromyography (EMG) signals, and then helps the user to accomplish hand motions in real time. The hand exoskeleton can perform six kinds of motions, including the whole hand closing/opening, tripod pinch/opening, and the "gun" sign/opening. A 52-year-old woman, 8 months after stroke, made 20× 2-h visits over 10 weeks to participate in robot-assisted hand training. Though she was unable to move her fingers on her right hand before the training, EMG activities could be detected on her right forearm. In each visit, she took 4× 10-min robot-assisted training sessions, in which she repeated the aforementioned six motion patterns assisted by our intent-driven hand exoskeleton. After the training, her grip force increased from 1.5 to 2.7 kg, her pinch force increased from 1.5 to 2.5 kg, her score of Box and Block test increased from 3 to 7, her score of Fugl-Meyer (Part C) increased from 0 to 7, and her hand function increased from Stage 1 to Stage 2 in Chedoke-McMaster assessment. The results demonstrate the feasibility of robot-assisted training driven by myoelectric pattern recognition after stroke.
Gerlach, Christian; Starrfelt, Randi
There has been an increase in studies adopting an individual difference approach to examine visual cognition and in particular in studies trying to relate face recognition performance with measures of holistic processing (the face composite effect and the part-whole effect). In the present study we examine whether global precedence effects, measured by means of non-face stimuli in Navon's paradigm, can also account for individual differences in face recognition and, if so, whether the effect is of similar magnitude for faces and objects. We find evidence that global precedence effects facilitate both face and object recognition, and to a similar extent. Our results suggest that both face and object recognition are characterized by a coarse-to-fine temporal dynamic, where global shape information is derived prior to local shape information, and that the efficiency of face and object recognition is related to the magnitude of the global precedence effect.
Lee, Ji Woo; Hong, Hyung Gil; Kim, Ki Wan; Park, Kang Ryoung
Despite a decrease in the use of currency due to the recent growth in the use of electronic financial transactions, real money transactions remain very important in the global market. While performing transactions with real money, touching and counting notes by hand, is still a common practice in daily life, various types of automated machines, such as ATMs and banknote counters, are essential for large-scale and safe transactions. This paper presents studies that have been conducted in four major areas of research (banknote recognition, counterfeit banknote detection, serial number recognition, and fitness classification) in the accurate banknote recognition field by various sensors in such automated machines, and describes the advantages and drawbacks of the methods presented in those studies. While to a limited extent some surveys have been presented in previous studies in the areas of banknote recognition or counterfeit banknote recognition, this paper is the first of its kind to review all four areas. Techniques used in each of the four areas recognize banknote information (denomination, serial number, authenticity, and physical condition) based on image or sensor data, and are actually applied to banknote processing machines across the world. This study also describes the technological challenges faced by such banknote recognition techniques and presents future directions of research to overcome them. PMID:28208733
Full Text Available Purpose. Hand infections are common, usually resulting from an untreated injury. In this retrospective study, we report on hand infection cases needing surgical drainage in order to assess patient demographics, causation of infection, clinical course, and clinical management.Methods. Medical records of patients presenting with hand infections, excluding post-surgical infections, treated with incision and debridement over a one-year period were reviewed. Patient demographics; past medical history; infection site(s and causation; intervals between onset of infection, hospital admission, surgical intervention and days of hospitalization; gram stains and cultures; choice of antibiotics; complications; and outcomes were reviewed.Results. Most infections were caused by laceration and the most common site of infection was the palm or dorsum of the hand. Mean length of hospitalization was 6 days. Methicillin-resistant Staphylococcus aureus, beta-hemolytic Streptococcus and methicillin-susceptible Staphylococcus aureus were the most commonly cultured microorganisms. Cephalosporins, clindamycin, amoxicillin/clavulanate, penicillin, vancomycin, and trimethoprim/sulfamethoxazole were major antibiotic choices. Amputations and contracture were the primary complications.Conclusions. Surgery along with medical management were key to treatment and most soft tissue infections resolved without further complications. With prompt and appropriate care, most hand infection patients can achieve full resolution of their infection.
Hosono, Noboru; Mukai, Yoshihiro; Takenaka, Shota; Fuji, Takeshi; Sakaura, Hironobu; Miwa, Toshitada; Makino, Takahiro
The so-called 'myelopathy hand', or characteristic finger paralysis, often recognized in cervical compression myelopathy, has been considered a unique manifestation of cervical myelopathy. We used our original grip and release test, a 15-second test in which finger motion is captured with a digital camera, to investigate whether cervical radiculopathy has the same characteristics as myelopathy hand. Thirty patients with pure radiculopathy, id est (i.e.), who had radiating arm pain and evidence of corresponding nerve root impingement on X-ray images or MRI scans, but did not have spinal cord compression, served as the subjects. In contrast to other radiculopathies, C7 radiculopathy was manifested by a significant reduction in the number of finger motion cycles on the affected side in comparison with the unaffected side, the same as in myelopathy hand. Uncoordinated finger motion was significantly more frequent on the affected side in C6 radiculopathy than on the unaffected side. These findings contradict the conventional notion that myelopathy hand is a unique manifestation of cervical myelopathy, but some radiculopathies manifested the same kinds of finger paralysis observed in myelopathy hand. (author)
Winter, Pawel; Sterner, Henrik; Sterner, Peter
We provide a unified description of (weighted) alpha shapes, beta shapes and the corresponding simplicialcomplexes. We discuss their applicability to various protein-related problems. We also discuss filtrations of alpha shapes and touch upon related persistence issues.We claim that the full...... potential of alpha-shapes and related geometrical constructs in protein-related problems yet remains to be realized and verified. We suggest parallel algorithms for (weighted) alpha shapes, and we argue that future use of filtrations and kinetic variants for larger proteins will need such implementation....
Bebis, George (Inventor); Amayeh, Gholamreza (Inventor)
Hand-based biometric analysis systems and techniques are described which provide robust hand-based identification and verification. An image of a hand is obtained, which is then segmented into a palm region and separate finger regions. Acquisition of the image is performed without requiring particular orientation or placement restrictions. Segmentation is performed without the use of reference points on the images. Each segment is analyzed by calculating a set of Zernike moment descriptors for the segment. The feature parameters thus obtained are then fused and compared to stored sets of descriptors in enrollment templates to arrive at an identity decision. By using Zernike moments, and through additional manipulation, the biometric analysis is invariant to rotation, scale, or translation or an in put image. Additionally, the analysis utilizes re-use of commonly-seen terms in Zernike calculations to achieve additional efficiencies over traditional Zernike moment calculation.
Atzori, Manfredo; Gijsberts, Arjan; Caputo, Barbara; Muller, Henning
People with transradial hand amputations who own a myoelectric prosthesis currently have some control capabilities via sEMG. However, the control systems are still limited and not natural. The Ninapro project is aiming at helping the scientific community to overcome these limits through the creation of publicly available electromyography data sources to develop and test machine learning algorithms. In this paper we describe the movement classification results gained from three subjects with an homogeneous level of amputation, and we compare them with the results of 40 intact subjects. The number of considered subjects can seem small at first sight, but it is not considering the literature of the field (which has to face the difficulty of recruiting trans-radial hand amputated subjects). The classification is performed with four different classifiers and the obtained balanced classification rates are up to 58.6% on 50 movements, which is an excellent result compared to the current literature. Successively, for each subject we find a subset of up to 9 highly independent movements, (defined as movements that can be distinguished with more than 90% accuracy), which is a deeply innovative step in literature. The natural control of a robotic hand in so many movements could lead to an immediate progress in robotic hand prosthetics and it could deeply change the quality of life of amputated subjects.
H.M. Hintjens (Helen); F. Bayisenge
textabstractUrunana (‘Hand in Hand’) is Rwanda’s first radio soap opera. The production emerged during the late 1990s from a three-way transnational production partnership between: The Great Lakes section of the BBC World Service; the Well Woman Media Project of the London-based NGO, Health
Naish, Katherine R; Barnes, Brittany; Obhi, Sukhvinder S
Recent work suggests that motor cortical processing during action observation plays a role in later recognition of the object involved in the action. Here, we investigated whether recognition of the effector making an action is also impaired when transcranial magnetic stimulation (TMS) - thought to interfere with normal cortical activity - is applied over the primary motor cortex (M1) during action observation. In two experiments, single-pulse TMS was delivered over the hand area of M1 while participants watched short clips of hand actions. Participants were then asked whether an image (experiment 1) or a video (experiment 2) of a hand presented later in the trial was the same or different to the hand in the preceding video. In Experiment 1, we found that participants' ability to recognise static images of hands was significantly impaired when TMS was delivered over M1 during action observation, compared to when no TMS was delivered, or when stimulation was applied over the vertex. Conversely, stimulation over M1 did not affect recognition of dot configurations, or recognition of hands that were previously presented as static images (rather than action movie clips) with no object. In Experiment 2, we found that effector recognition was impaired when stimulation was applied part way through (300ms) and at the end (500ms) of the action observation period, indicating that 200ms of action-viewing following stimulation was not long enough to form a new representation that could be used for later recognition. The findings of both experiments suggest that interfering with cortical motor activity during action observation impairs subsequent recognition of the effector involved in the action, which complements previous findings of motor system involvement in object memory. This work provides some of the first evidence that motor processing during action observation is involved in forming representations of the effector that are useful beyond the action observation period
This paper describes a research work on computer aided vision relating to the design of a vision system which can recognize isolated handwritten characters written on a mobile support. We use a technique which consists in analyzing information contained in the contours of the polygon circumscribed to the character's shape. These contours are segmented and labelled to give a new set of features constituted by: - right and left 'profiles', - topological and algebraic unvarying properties. A new method of character's recognition induced from this representation based on a multilevel hierarchical technique is then described. In the primary level, we use a fuzzy classification with dynamic programming technique using 'profiles'. The other levels adjust the recognition by using topological and algebraic unvarying properties. Several results are presented and an accuracy of 99 pc was reached for handwritten numeral characters, thereby attesting the robustness of our algorithm. (author) [fr
Schmitt, Rainer [Hospital for Cardiovascular Diseases, Bad Neustadt an der Saale (Germany). Dept. of Radiology; Lanz, Ulrich [Perlach Hospital, Munich (Germany). Dept. of Hand Surgery
With its complex anatomy and specialized biomechanics, the human hand has always presented physicians with a unique challenge when it comes to diagnosing and treating the diseases that afflict it. And while recent decades have seen a rapid increase in the number of therapeutic options, many diseases and injuries of the hand are still commonly misinterpreted. In diagnostic imaging of the hand, an interdisciplinary team, comprisingspecialists in radiology, surgery, and rheumatology, presents a comprehensive,reliable guide to this topographically intricate area. Highlights include: - More than 1000 high-quality illustrations - All state-of-the-art imaging modalities-including multidetector CT, with 2D displays and 3D reconstructions, and contrast-enhanced MRI with multi-channel, phased-array coils - An overview of all currently used methods of examination - A detailed presentation of the anatomic and functional foundations necessary for diagnosis - Full coverage of all disorders of the hand - Systematic treatment of each disease's definition, pathogenesis, and clinical symptoms, according to a graduated diagnostic plan - Easy-to-use format, featuring crisp images and line drawings seamlessly integrated with concise text, summary tables, and handy checklists - A heavily cross-referenced appendix of differential diagnosis tables - Emphasis on interdisciplinary consultation throughout designed to help both radiologists and clinicians develop the most efficient and effective strategies for evaluating and treating patients, Diagnostic imaging of the hand will leave specialists of all levels with a fresh appreciation for - and a richer understanding of - the expanding array of cutting-edge alternatives for diagnosing and treating disorders of the hand. (orig.)
Schmitt, Rainer; Lanz, Ulrich
With its complex anatomy and specialized biomechanics, the human hand has always presented physicians with a unique challenge when it comes to diagnosing and treating the diseases that afflict it. And while recent decades have seen a rapid increase in the number of therapeutic options, many diseases and injuries of the hand are still commonly misinterpreted. In diagnostic imaging of the hand, an interdisciplinary team, comprisingspecialists in radiology, surgery, and rheumatology, presents a comprehensive,reliable guide to this topographically intricate area. Highlights include: - More than 1000 high-quality illustrations - All state-of-the-art imaging modalities-including multidetector CT, with 2D displays and 3D reconstructions, and contrast-enhanced MRI with multi-channel, phased-array coils - An overview of all currently used methods of examination - A detailed presentation of the anatomic and functional foundations necessary for diagnosis - Full coverage of all disorders of the hand - Systematic treatment of each disease's definition, pathogenesis, and clinical symptoms, according to a graduated diagnostic plan - Easy-to-use format, featuring crisp images and line drawings seamlessly integrated with concise text, summary tables, and handy checklists - A heavily cross-referenced appendix of differential diagnosis tables - Emphasis on interdisciplinary consultation throughout designed to help both radiologists and clinicians develop the most efficient and effective strategies for evaluating and treating patients, Diagnostic imaging of the hand will leave specialists of all levels with a fresh appreciation for - and a richer understanding of - the expanding array of cutting-edge alternatives for diagnosing and treating disorders of the hand. (orig.)
Despite widespread acceptance of the importance of employee recognition for both individuals and organisations and evidence of its increasing use in organisations, employee recognition has received relatively little focused attention from academic researchers. Particularly lacking is research exploring the lived experience of employee recognition and the interpretations and meanings which individuals give to these experiences. Drawing on qualitative interviews conducted as part of my PhD rese...
Konnaris, C; Gavriel, C; Thomik, AAC; Aldo Faisal, A
Our dexterous hand is a fundmanetal human feature that distinguishes us from other animals by enabling us to go beyond grasping to support sophisticated in-hand object manipulation. Our aim was the design of a dexterous anthropomorphic robotic hand that matches the human hand's 24 degrees of freedom, under-actuated by seven motors. With the ability to replicate human hand movements in a naturalistic manner including in-hand object manipulation. Therefore, we focused on the development of a no...
Dan, Luo; Ohya, Jun
Recognizing hand gestures from the video sequence acquired by a dynamic camera could be a useful interface between humans and mobile robots. We develop a state based approach to extract and recognize hand gestures from moving camera images. We improved Human-Following Local Coordinate (HFLC) System, a very simple and stable method for extracting hand motion trajectories, which is obtained from the located human face, body part and hand blob changing factor. Condensation algorithm and PCA-based algorithm was performed to recognize extracted hand trajectories. In last research, this Condensation Algorithm based method only applied for one person's hand gestures. In this paper, we propose a principal component analysis (PCA) based approach to improve the recognition accuracy. For further improvement, temporal changes in the observed hand area changing factor are utilized as new image features to be stored in the database after being analyzed by PCA. Every hand gesture trajectory in the database is classified into either one hand gesture categories, two hand gesture categories, or temporal changes in hand blob changes. We demonstrate the effectiveness of the proposed method by conducting experiments on 45 kinds of sign language based Japanese and American Sign Language gestures obtained from 5 people. Our experimental recognition results show better performance is obtained by PCA based approach than the Condensation algorithm based method.
Full Text Available Brain regions in the intraparietal and the premotor cortices selectively process visual and multisensory events near the hands (peri-hand space. Visual information from the hand itself modulates this processing potentially because it is used to estimate the location of one's own body and the surrounding space. In humans specific occipitotemporal areas process visual information of specific body parts such as hands. Here we used an fMRI block-design to investigate if anterior intraparietal and ventral premotor 'peri-hand areas' exhibit selective responses to viewing images of hands and viewing specific hand orientations. Furthermore, we investigated if the occipitotemporal 'hand area' is sensitive to viewed hand orientation. Our findings demonstrate increased BOLD responses in the left anterior intraparietal area when participants viewed hands and feet as compared to faces and objects. Anterior intraparietal and also occipitotemporal areas in the left hemisphere exhibited response preferences for viewing right hands with orientations commonly viewed for one's own hand as compared to uncommon own hand orientations. Our results indicate that both anterior intraparietal and occipitotemporal areas encode visual limb-specific shape and orientation information.
Paksima, Nader; Besh, Basil R
Contractures of the intrinsic muscles of the fingers disrupt the delicate and complex balance of intrinsic and extrinsic muscles, which allows the hand to be so versatile and functional. The loss of muscle function primarily affects the interphalangeal joints but also may affect etacarpophalangeal joints. The resulting clinical picture is often termed, intrinsic contracture or intrinsic-plus hand. Disruption of the balance between intrinsic and extrinsic muscles has many causes and may be secondary to changes within the intrinsic musculature or the tendon unit. This article reviews diagnosis, etiology, and treatment algorithms in the management of intrinsic contractures of the fingers. Copyright © 2012 Elsevier Inc. All rights reserved.
Patel, M R; Wells, S
Lionfish (Pterois volitans) envenomation of the hand causes excruciating pain and occurs in three grades: (1) erythematous reaction, (2) blister formation, and (3) dermal necrosis. The initial treatment in all cases is to soak the hand in nonscalding water (45 degrees C) until the pain subsides by denaturing the thermolabile venom proteins. The blisters should be immediately excised to prevent dermal necrosis, inasmuch as the blister fluid contains residual active venom. To prevent a hypersensitivity reaction, any further contact with the fish should be avoided.
Dieckmann, Gerhard Peter; Graae Zeltner, Louise; Helsø, Anne-Mette
Non-technical skills (NTS) are an integral part of the abilities healthcare professionals need to optimally care for patients. Integrating NTS into the already complex tasks of healthcare can be a challenge for clinicians. Integrating NTS into simulation-based training increases the demands...... and where they can apply them in their work. It complements existing approaches to teaching NTS by limiting the complexity of the game and by removing medical content, allowing learners to concentrate on NTS. Hand-it-on is relevant for groups and teams working across the range of different healthcare...... and the replication of Hand-it-on by many simulation teams support its value....
Salamanca Cárdenas, Daniela; Castelblanco Domínguez, Junio Andrés; Aguilar Ardila, Laura Andrea
El modelo de Discovering Hands ha sido reconocido internacionalmente como un proyecto innovador que se ha expandido por diferentes países del mundo, como Austria, y se ha empezado a estudiar la propuesta en países como República Checa, India y Colombia. (Discovering Hands, 2016). Esto se debe a que no solo mejora el tratamiento de cáncer de mama, sino que también reduce los costos totales de tratamiento de la enfermedad y aumenta la fuerza laborar de los países donde esté presente. Al represe...
Ueno, S.; Takemura, K.; Yokota, S.; Edamura, K.
An electro-conjugate fluid (ECF) is a kind of functional fluid, which produces a flow (ECF flow) when subjected to high DC voltage. Since it only requires a tiny electrode pair in micrometer size in order to generate the ECF flow, the ECF is a promising micro fluid pressure source. This study proposes a novel micro robot hand using the ECF. The robot hand is mainly composed of five flexible fingers and an ECF flow generator. The flexible finger is made of silicone rubber having several chambers in series along its axis. When the chambers are depressurized, the chambers deflate resulting in making the actuator bend. On the other hand, the ECF flow generator has a needle-ring electrode pair inside. When putting the ECF flow generator into the ECF and applying voltage of 6.0 kV to the electrode pair, we can obtain the pressure of 33.1 kPa. Using the components mentioned above, we developed the ECF robot hand. The height, the width and the mass of the robot hand are 45 mm, 40 mm and 5.2 g, respectively. Since the actuator is flexible, the robot hand can grasp various objects with various shapes without complex controller.
Ghosh, Anarta; Petkov, Nicolai; Gregorio, MD; DiMaio,; Frucci, M; Musio, C
Inspired by psychophysical studies of the human cognitive abilities we propose a novel aspect and a method for performance evaluation of contour based shape recognition algorithms regarding their robustness to incompleteness of contours. We use complete contour representations of objects as a
Pecher, Diane; van Dantzig, Saskia; Zwaan, Rolf A; Zeelenberg, René
According to theories of embodied cognition, language comprehenders simulate sensorimotor experiences to represent the meaning of what they read. Previous studies have shown that picture recognition is better if the object in the picture matches the orientation or shape implied by a preceding sentence. In order to test whether strategic imagery may explain previous findings, language comprehenders first read a list of sentences in which objects were mentioned. Only once the complete list had been read was recognition memory tested with pictures. Recognition performance was better if the orientation or shape of the object matched that implied by the sentence, both immediately after reading the complete list of sentences and after a 45-min delay. These results suggest that previously found match effects were not due to strategic imagery and show that details of sensorimotor simulations are retained over longer periods.
Huang, Lidong; Udupa, Jayaram K.; Tong, Yubing; Odhner, Dewey; Torigian, Drew A.
Body-wide anatomy recognition on CT images with pathology becomes crucial for quantifying body-wide disease burden. This, however, is a challenging problem because various diseases result in various abnormalities of objects such as shape and intensity patterns. We previously developed an automatic anatomy recognition (AAR) system  whose applicability was demonstrated on near normal diagnostic CT images in different body regions on 35 organs. The aim of this paper is to investigate strategies for adapting the previous AAR system to diagnostic CT images of patients with various pathologies as a first step toward automated body-wide disease quantification. The AAR approach consists of three main steps - model building, object recognition, and object delineation. In this paper, within the broader AAR framework, we describe a new strategy for object recognition to handle abnormal images. In the model building stage an optimal threshold interval is learned from near-normal training images for each object. This threshold is optimally tuned to the pathological manifestation of the object in the test image. Recognition is performed following a hierarchical representation of the objects. Experimental results for the abdominal body region based on 50 near-normal images used for model building and 20 abnormal images used for object recognition show that object localization accuracy within 2 voxels for liver and spleen and 3 voxels for kidney can be achieved with the new strategy.
Meyer, Manuel; Riess, Christian; Angelopoulou, Elli; Evangelopoulos, Georgios; Kakadiaris, Ioannis A.
Face is one of the most popular biometric modalities. However, up to now, color is rarely actively used in face recognition. Yet, it is well-known that when a person recognizes a face, color cues can become as important as shape, especially when combined with the ability of people to identify the color of objects independent of illuminant color variations. In this paper, we examine the feasibility and effect of explicitly embedding illuminant color information in face recognition systems. We empirically examine the theoretical maximum gain of including known illuminant color to a 3D-2D face recognition system. We also investigate the impact of using computational color constancy methods for estimating the illuminant color, which is then incorporated into the face recognition framework. Our experiments show that under close-to-ideal illumination estimates, one can improve face recognition rates by 16%. When the illuminant color is algorithmically estimated, the improvement is approximately 5%. These results suggest that color constancy has a positive impact on face recognition, but the accuracy of the illuminant color estimate has a considerable effect on its benefits.
Hirot, France; Lesage, Marine; Pedron, Lya; Meyer, Isabelle; Thomas, Pierre; Cottencin, Olivier; Guardia, Dewi
Body image disturbances and massive weight loss are major clinical symptoms of anorexia nervosa (AN). The aim of the present study was to examine the influence of body changes and eating attitudes on self-face recognition ability in AN. Twenty-seven subjects suffering from AN and 27 control participants performed a self-face recognition task (SFRT). During the task, digital morphs between their own face and a gender-matched unfamiliar face were presented in a random sequence. Participants' self-face recognition failures, cognitive flexibility, body concern and eating habits were assessed with the Self-Face Recognition Questionnaire (SFRQ), Trail Making Test (TMT), Body Shape Questionnaire (BSQ) and Eating Disorder Inventory-2 (EDI-2), respectively. Subjects suffering from AN exhibited significantly greater difficulties than control participants in identifying their own face (p = 0.028). No significant difference was observed between the two groups for TMT (all p > 0.1, non-significant). Regarding predictors of self-face recognition skills, there was a negative correlation between SFRT and body mass index (p = 0.01) and a positive correlation between SFRQ and EDI-2 (p face recognition.
Shape memory alloys (SMA), when deformed, have the ability of returning, in certain circumstances, to their initial shape. Deformations related to this phenomenon are for polycrystals 1-8% and up to 15% for monocrystals. The deformation energy is in the range of 10 6 - 10 7 J/m 3 . The deformation is caused by martensitic transformation in the material. Shape memory alloys exhibit one directional or two directional shape memory effect as well as pseudoelastic effect. Shape change is activated by temperature change, which limits working frequency of SMA to 10 2 Hz. Other group of alloys exhibit magnetic shape memory effect. In these alloys martensitic transformation is triggered by magnetic field, thus their working frequency can be higher. Composites containing shape memory alloys can also be used as shape memory materials (applied in vibration damping devices). Another group of composite materials is called heterostructures, in which SMA alloys are incorporated in a form of thin layers The heterostructures can be used as microactuators in microelectromechanical systems (MEMS). Basic SMA comprise: Ni-Ti, Cu (Cu-Zn,Cu-Al, Cu-Sn) and Fe (Fe-Mn, Fe-Cr-Ni) alloys. Shape memory alloys find applications in such areas: automatics, safety and medical devices and many domestic appliances. Currently the most important appears to be research on magnetic shape memory materials and high temperature SMA. Vital from application point of view are composite materials especially those containing several intelligent materials. (author)
This book uses the spiral shape as a key to a multitude of strange and seemingly disparate stories about art, nature, science, mathematics, and the human endeavour. In a way, the book is itself organized as a spiral, with almost disconnected chapters circling around and closing in on the common theme. A particular strength of the book is its extremely cross-disciplinary nature - everything is fun, and everything is connected! At the same time, the author puts great emphasis on mathematical and scientific correctness, in contrast, perhaps, with some earlier books on spirals. Subjects include the mathematical properties of spirals, sea shells, sun flowers, Greek architecture, air ships, the history of mathematics, spiral galaxies, the anatomy of the human hand, the art of prehistoric Europe, Alfred Hitchcock, and spider webs, to name a few.
Kuhn, Christina D.; Asperud Thomsen, Johanne; Delfi, Tzvetelina
Abstract Recent findings have challenged the existence of category specific brain areas for perceptual processing of words and faces, suggesting the existence of a common network supporting the recognition of both. We examined the performance of patients with focal lesions in posterior cortical...... areas to investigate whether deficits in recognition of words and faces systematically co-occur as would be expected if both functions rely on a common cerebral network. Seven right-handed patients with unilateral brain damage following stroke in areas supplied by the posterior cerebral artery were...... included (four with right hemisphere damage, three with left, tested at least 1 year post stroke). We examined word and face recognition using a delayed match-to-sample paradigm using four different categories of stimuli: cropped faces, full faces, words, and cars. Reading speed and word length effects...
This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques. .
Every human being is proficient in face recognition. However, the reason for and the manner in which humans have attained such an ability remain unknown. These questions can be best answered-through comparative studies of face recognition in non-human animals. Studies in both primates and non-primates show that not only primates, but also non-primates possess the ability to extract information from their conspecifics and from human experimenters. Neural specialization for face recognition is shared with mammals in distant taxa, suggesting that face recognition evolved earlier than the emergence of mammals. A recent study indicated that a social insect, the golden paper wasp, can distinguish their conspecific faces, whereas a closely related species, which has a less complex social lifestyle with just one queen ruling a nest of underlings, did not show strong face recognition for their conspecifics. Social complexity and the need to differentiate between one another likely led humans to evolve their face recognition abilities.
Shakeshaft, Nicholas G; Plomin, Robert
Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities.