WorldWideScience

Sample records for chemically-mediated roostmate recognition

  1. Chemically mediated burrow recognition in the Mexican tarantula Brachypelma vagans female

    Science.gov (United States)

    Dor, Ariane; Machkour-M'rabet, Salima; Legal, Luc; Williams, Trevor; Hénaut, Yann

    2008-12-01

    Chemically mediated communication is common in spiders but has been poorly studied in burrowing tarantulas. This study aimed to determine whether chemical cues influence the behaviour of females of Brachypelma vagans, a Mexican species of tarantula, during encounters with previously inhabited burrows or with extracts from the silk of conspecific females. In laboratory choice tests, female tarantulas entered a burrow that had previously been inhabited by a conspecific female significantly more frequently than a burrow that had never been inhabited. The identity of the previous inhabitant also affected the number of spiders that chose to enter a burrow. Spiders were quicker to choose and enter a burrow previously inhabited by themselves than a burrow previously inhabited by a conspecific or a burrow that had not been previously inhabited. Hexane, methanol and dichloromethane extracts of conspecific silk elicited different responses from female tarantulas when extracts were placed on filter paper disks at one end of an experimental arena with a control filter paper disk, on to which the corresponding solvent alone had been pipetted, placed on the other end of the arena. Spiders showed the strongest responses to hexane extracts of silk, with a significant preference to move towards the hexane extract and a significantly greater period of time spent in proximity to the hexane extract compared to the control disk. Overall and in contrast to expectations, tarantulas were most strongly attracted to the cues left by other conspecific females. As encounters between B. vagans females usually lead to aggression and mortality of one of the participants, we conclude that chemical cues are not signals that are deliberately released by burrow-inhabiting females but may inadvertently escape and cannot be easily suppressed.

  2. Controlled drug release from lung-targeted nanocarriers via chemically mediated shell permeabilisation.

    Science.gov (United States)

    Chen, Hanpeng; Woods, Arcadia; Forbes, Ben; Jones, Stuart

    2016-09-25

    Nanocarriers can aid therapeutic agent administration to the lung, but controlling drug delivery from these systems after deposition in the airways can be problematic. The aim of this study was to evaluate if chemically mediated shell permeabilisation could help manipulate the rate and extent of nanocarrier drug release. Rifampicin was loaded into lipid shell (loading efficiency 41.0±11.4%, size 50nm) and polymer shell nanocarriers (loading efficiency 25.9±2.3%, size 250nm). The drug release at pH 7.4 (lung epithelial pH) and 4.2 (macrophage endosomal pH) with and without the chemical permeabilisers (Pluronic L62D - lipid nanocarriers; H(+)- polymer nanocarriers) was then tested. At pH 7.4 the presence of the permeabilisers increased nanocarrier drug release rate (from 3.2μg/h to 6.8μg/h for lipid shell nanocarriers, 2.3μg/h to 3.4μg/h for polymer shell nanocarriers) and drug release extent (from 50% to 80% for lipid shell nanocarriers, from 45% to 76% for polymer shell nanocarriers). These effects were accompanied by lipid nanocarrier distension (from 50 to 240nm) and polymer shell hydrolysis. At pH 4.2 the polymer nanocarriers did not respond to the permeabiliser, but the lipid nanocarrier maintained a robust drug release enhancement response and hence they demonstrated that the manipulation of controlled drug release from lung-targeted nanocarriers was possible through chemically mediated shell permeabilisation.

  3. Pattern recognition

    CERN Document Server

    Theodoridis, Sergios

    2003-01-01

    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

  4. Fungal laccase, cellobiose dehydrogenase, and chemical mediators: combined actions for the decolorization of different classes of textile dyes.

    Science.gov (United States)

    Ciullini, Ilaria; Tilli, Silvia; Scozzafava, Andrea; Briganti, Fabrizio

    2008-10-01

    Dyes belonging to the mono-, di-, tri- and poly-azo as well as anthraquinonic and mono-azo Cr-complexed classes, chosen among the most utilized in textile applications, were employed for a comparative enzymatic decolorization study using the extracellular crude culture extracts from the white rot fungus Funalia (Trametes) trogii grown on different culture media and activators able to trigger different levels of expression of oxidizing enzymes: laccase and cellobiose dehydrogenase. Laccase containing extracts were capable to decolorize some dyes from all the different classes analyzed, whereas the recalcitrant dyes were subjected to the combined action of laccase and the chemical mediator HBT, or laccase plus cellobiose dehydrogenase. Correlations among the decolorization degree of the various dyes and their electronic and structural diversities were rationalized and discussed. The utilization of cellobiose dehydrogenase in support to the activity of laccase for the decolorization of azo textile dyes resulted in substantial increases in decolorization for all the refractory dyes proving to be a valid alternative to more expensive and less environmentally friendly chemical treatments of textile dyes wastes.

  5. Fingerprint recognition

    OpenAIRE

    Diefenderfer, Graig T.

    2006-01-01

    The use of biometrics is an evolving component in today's society. Fingerprint recognition continues to be one of the most widely used biometric systems. This thesis explores the various steps present in a fingerprint recognition system. The study develops a working algorithm to extract fingerprint minutiae from an input fingerprint image. This stage incorporates a variety of image pre-processing steps necessary for accurate minutiae extraction and includes two different methods of ridge thin...

  6. Facial Recognition

    Directory of Open Access Journals (Sweden)

    Mihalache Sergiu

    2014-05-01

    Full Text Available During their lifetime, people learn to recognize thousands of faces that they interact with. Face perception refers to an individual's understanding and interpretation of the face, particularly the human face, especially in relation to the associated information processing in the brain. The proportions and expressions of the human face are important to identify origin, emotional tendencies, health qualities, and some social information. From birth, faces are important in the individual's social interaction. Face perceptions are very complex as the recognition of facial expressions involves extensive and diverse areas in the brain. Our main goal is to put emphasis on presenting human faces specialized studies, and also to highlight the importance of attractiviness in their retention. We will see that there are many factors that influence face recognition.

  7. Speaker Recognition

    DEFF Research Database (Denmark)

    Mølgaard, Lasse Lohilahti; Jørgensen, Kasper Winther

    2005-01-01

    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...... in applications like banking by telephone and voice mail. The focus of this project is speaker identification, which consists of mapping a speech signal from an unknown speaker to a database of known speakers, i.e. the system has been trained with a number of speakers which the system can recognize....

  8. A theoretical analysis of the extraction of heterocyclic organic compounds from an organic phase using chemically mediated electrochemically modulated complexation in ion exchange polymer beads

    Energy Technology Data Exchange (ETDEWEB)

    Ozekin, K.; Noble, R.D.; Koval, C.A.

    1991-01-01

    A cyclical electrochemical process for the removal of heterocyclic organic compounds (pollutants) from an organic solvent using an ion-exchange polymer is analyzed. In this analysis, there are three main steps: In the first step, the polymer beads containing the active form of the complexing agent are contacted with the contaminated (feed) hydrocarbon phase. The pollutant diffuses into the beads and binds with the complexing agent which is in the reduced state. It is a fast reversible reaction. For the second step, the beads which contain a pollutant are contacted with a waste (receiving) phase and a chemical mediator is then used to oxidize the complexing agent and to reduce its affinity towards the pollutant so that it can be released. The oxidation of the complexing agent is an irreversible reaction. This is a moving boundary problem with countercurrent diffusion. For each mole of mediator that goes into the bead, one mole of pollutant exits since each complexing agent binds one pollutant. In the third step, the waste hydrocarbon phase is removed and a second chemical mediator is then used to reduce the complexing agent. The reduction of the complexing agent is also an irreversible reaction. Partial differential equations are used to analyze this process. 26 refs., 9 figs.

  9. The recognition of work

    OpenAIRE

    Nierling, Linda

    2007-01-01

    The following article argues that recognition structures in work relations differ significantly in the sphere of paid work in contrast to unpaid work in private spheres. According to the systematic approach on recognition of Axel Honneth three different levels of recognition are identified: the interpersonal recognition, organisational recognition and societal recognition. Based on this framework it can be stated that recognition structures in the sphere of paid work and in private spheres di...

  10. Gesture Recognition Summarization

    Institute of Scientific and Technical Information of China (English)

    ZHANG Ting-fang; FENG Zhi-quan; SU Yuan-yuan; JIANG Yan

    2014-01-01

    Gesture recognition is an important research in the field of human-computer interaction. Hand Gestures are strong variable and flexible, so the gesture recognition has always been an important challenge for the researchers. In this paper, we first outlined the development of gestures recognition, and different classification of gestures based on different purposes. Then we respectively introduced common methods used in the process of gesture segmentation, feature extraction and recognition. Finally, the gesture recognition was summarized and the studying prospects were given.

  11. Iris Recognition Technique

    Institute of Scientific and Technical Information of China (English)

    XIE Mei

    2006-01-01

    The demand on security is increasing greatly in these years and biometric recognition gradually becomes a hot field of research. Iris recognition is a new branch of biometric recognition, which is regarded as the most stable, safe and accurate biometric recognition method. In these years, much progress in this field has been made by scholars and experts of different countries. In this paper, some successful iris recognition methods are listed and their performance are compared. Furthermore, the existing problems and challenges are discussed.

  12. Object reading: text recognition for object recognition

    NARCIS (Netherlands)

    Karaoglu, S.; van Gemert, J.C.; Gevers, T.

    2012-01-01

    We propose to use text recognition to aid in visual object class recognition. To this end we first propose a new algorithm for text detection in natural images. The proposed text detection is based on saliency cues and a context fusion step. The algorithm does not need any parameter tuning and can d

  13. Recognition and Toleration

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2010-01-01

    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...

  14. Multimodal eye recognition

    Science.gov (United States)

    Zhou, Zhi; Du, Yingzi; Thomas, N. L.; Delp, Edward J., III

    2010-04-01

    Multimodal biometrics use more than one means of biometric identification to achieve higher recognition accuracy, since sometimes a unimodal biometric is not good enough used to do identification and classification. In this paper, we proposed a multimodal eye recognition system, which can obtain both iris and sclera patterns from one color eye image. Gabor filter and 1-D Log-Gabor filter algorithms have been applied as the iris recognition algorithms. In sclera recognition, we introduced automatic sclera segmentation, sclera pattern enhancement, sclera pattern template generation, and sclera pattern matching. We applied kernelbased matching score fusion to improve the performance of the eye recognition system. The experimental results show that the proposed eye recognition method can achieve better performance compared to unimodal biometric identification, and the accuracy of our proposed kernel-based matching score fusion method is higher than two classic linear matching score fusion methods: Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA).

  15. Pattern recognition & machine learning

    CERN Document Server

    Anzai, Y

    1992-01-01

    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.

  16. Comparison of associative recognition versus source recognition.

    Science.gov (United States)

    Park, Heekyeong; Abellanoza, Cheryl; Schaeffer, James D

    2014-10-03

    The importance of the medial temporal lobe (MTL) for memory of arbitrary associations has been well established. However, the contribution of the MTL in concurrent retrieval of different classes of associations remains unclear. The present fMRI study investigated neural correlates of concurrent retrieval of associative and source memories. Participants studied a list of object pairs with two study tasks and judged the status and context of the pair during test. Associative retrieval was supported by neural activity in bilateral prefrontal cortex and left ventral occipito-temporal cortex, while source recognition was linked to activity in the right caudate. Both the hippocampus and MTL cortex showed retrieval activity for associative and source memory. Importantly, greater brain activity for successful associative recognition accompanied with successful source recognition was evident in left perirhinal and anterior hippocampal regions. These results indicate that the MTL is critical in the retrieval of different classes of associations.

  17. Multimodal recognition of emotions

    NARCIS (Netherlands)

    Datcu, D.

    2009-01-01

    This thesis proposes algorithms and techniques to be used for automatic recognition of six prototypic emotion categories by computer programs, based on the recognition of facial expressions and emotion patterns in voice. Considering the applicability in real-life conditions, the research is carried

  18. Recognition measured values

    OpenAIRE

    LEITKEP, Zdeněk

    2012-01-01

    This work deals recognition measured values. The main task is to find suitable method for preprocessing images and create interface to software performing recognition. Created application will be used primarily to analyze the photos on site acquisition. Application is developed in Java and properly documented on javadoc level.

  19. Handwritten Digits Recognition

    OpenAIRE

    Grand, Eric

    2000-01-01

    My work of diploma consisted in developing a Windows application for the recognition of the handwritten digits. The source images come from a pen-scanner. The user can also draw the digits directly with the mouse and do the recognition of it. In this software, I integrated the SVM Light reconizer.

  20. Handbook of Face Recognition

    CERN Document Server

    Li, Stan Z

    2011-01-01

    This highly anticipated new edition provides a comprehensive account of face recognition research and technology, spanning the full range of topics needed for designing operational face recognition systems. After a thorough introductory chapter, each of the following chapters focus on a specific topic, reviewing background information, up-to-date techniques, and recent results, as well as offering challenges and future directions. Features: fully updated, revised and expanded, covering the entire spectrum of concepts, methods, and algorithms for automated face detection and recognition systems

  1. Mobile intention recognition

    CERN Document Server

    Kiefer, Peter

    2011-01-01

    Mobile Intention Recognition addresses problems of practical relevance for mobile system engineers: how can we make mobile assistance systems more intelligent? How can we model and recognize patterns of human behavior which span more than a limited spatial context? This text provides an overview on plan and intention recognition, ranging from the late 1970s to very recent approaches. This overview is unique as it discusses approaches with respect to the specificities of mobile intention recognition. This book covers problems from research on mobile assistance systems using methods from artific

  2. PCA facial expression recognition

    Science.gov (United States)

    El-Hori, Inas H.; El-Momen, Zahraa K.; Ganoun, Ali

    2013-12-01

    This paper explores and compares techniques for automatically recognizing facial actions in sequences of images. The comparative study of Facial Expression Recognition (FER) techniques namely Principal Component's analysis (PCA) and PCA with Gabor filters (GF) is done. The objective of this research is to show that PCA with Gabor filters is superior to the first technique in terms of recognition rate. To test and evaluates their performance, experiments are performed using real database by both techniques. The universally accepted five principal emotions to be recognized are: Happy, Sad, Disgust and Angry along with Neutral. The recognition rates are obtained on all the facial expressions.

  3. Forensic speaker recognition

    NARCIS (Netherlands)

    Meuwly, Didier

    2009-01-01

    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

  4. Work and Recognition

    DEFF Research Database (Denmark)

    Willig, Rasmus

    2004-01-01

    individual and collective identity formation and has led to an increase in social pathological illnesses such as stress and depression. By juxtaposing these analyses with Honneth’s theory on recognition, we conclude that the contemporary logic of work is unable to provide adequate forms of recognition......The article deals with the relationship between work and recognition, taking Axel Honneth’s social-philosophical theory of the struggle for recognition as its point of departure. In order to give sociological substance to Honneth’s theory, we turn to three contemporary social theorists - Jean......-Pierre Le Goff, Christophe Dejours and Emmanuel Renault. In spite of many differences, their work is united by a critical description of the logic of work and its consequences for individual individuation. These theorists agree that the growth of autonomy, flexibility and mobility has destabilised...

  5. Human Emotion Recognition System

    Directory of Open Access Journals (Sweden)

    Dilbag Singh

    2012-08-01

    Full Text Available This paper discusses the application of feature extraction of facial expressions with combination of neural network for the recognition of different facial emotions (happy, sad, angry, fear, surprised, neutral etc... Humans are capable of producing thousands of facial actions during communication that vary in complexity, intensity, and meaning. This paper analyses the limitations with existing system Emotion recognition using brain activity. In this paper by using an existing simulator I have achieved 97 percent accurate results and it is easy and simplest way than Emotion recognition using brain activity system. Purposed system depends upon human face as we know face also reflects the human brain activities or emotions. In this paper neural network has been used for better results. In the end of paper comparisons of existing Human Emotion Recognition System has been made with new one.

  6. The Recognition Of Fatigue

    DEFF Research Database (Denmark)

    Elsass, Peter; Jensen, Bodil; Mørup, Rikke;

    2007-01-01

    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...

  7. Evaluating music emotion recognition

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2013-01-01

    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....

  8. Why recognition is rational

    Directory of Open Access Journals (Sweden)

    Clintin P. Davis-Stober

    2010-07-01

    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.

  9. Touchless palmprint recognition systems

    CERN Document Server

    Genovese, Angelo; Scotti, Fabio

    2014-01-01

    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

  10. Recognition as care

    DEFF Research Database (Denmark)

    Ahlmark, Nanna; Whyte, Susan Reynolds; Harting, Janneke

    2014-01-01

    This longitudinal study provides critical insight into the social processes of municipal diabetes training for Arabic-speaking immigrants in Denmark focusing on participants’ experiences. Our study builds on observations of three diabetes courses and 36 interviews with participants at the start of......-based and solidarity-based recognition to analyse what was at stake in these experiences, and we engage Annemarie Mol’s concept of a logic of care to show how recognition unfolded practically during the training. We propose that participants’ wider social context and experiences of misrecognition situated the training...

  11. [Prosopagnosia and facial expression recognition].

    Science.gov (United States)

    Koyama, Shinichi

    2014-04-01

    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.

  12. Automatic aircraft recognition

    Science.gov (United States)

    Hmam, Hatem; Kim, Jijoong

    2002-08-01

    Automatic aircraft recognition is very complex because of clutter, shadows, clouds, self-occlusion and degraded imaging conditions. This paper presents an aircraft recognition system, which assumes from the start that the image is possibly degraded, and implements a number of strategies to overcome edge fragmentation and distortion. The current vision system employs a bottom up approach, where recognition begins by locating image primitives (e.g., lines and corners), which are then combined in an incremental fashion into larger sets of line groupings using knowledge about aircraft, as viewed from a generic viewpoint. Knowledge about aircraft is represented in the form of whole/part shape description and the connectedness property, and is embedded in production rules, which primarily aim at finding instances of the aircraft parts in the image and checking the connectedness property between the parts. Once a match is found, a confidence score is assigned and as evidence in support of an aircraft interpretation is accumulated, the score is increased proportionally. Finally a selection of the resulting image interpretations with the highest scores, is subjected to competition tests, and only non-ambiguous interpretations are allowed to survive. Experimental results demonstrating the effectiveness of the current recognition system are given.

  13. Recognition of fractal graphs

    NARCIS (Netherlands)

    Perepelitsa, VA; Sergienko, [No Value; Kochkarov, AM

    1999-01-01

    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 i

  14. Tolerance and recognition

    Directory of Open Access Journals (Sweden)

    Hans Marius Hansteen

    2014-12-01

    Full Text Available Even though “toleration” and “recognition” designate opposing attitudes (to tolerate something, implies a negative stance towards it, whereas recognition seems to imply a positive one, the concepts do not constitute mutually exclusive alternatives. However, “toleration” is often associated with liberal universalism, focusing on individual rights, whereas “recognition” often connotes communitarian perspectives, focusing on relations and identity. This paper argues that toleration may be founded on recognition, and that recognition may imply toleration. In outlining a differentiated understanding of the relationship between toleration and recognition, it seems apt to avoid an all-to-general dichotomy between universalism and particularism or, in other words, to reach beyond the debate between liberalism and communitarianism in political philosophy.The paper takes as its starting point the view that the discussion on toleration and diversity in intercultural communication is one of the contexts where it seems important to get beyond the liberal/communitarian dichotomy. Some basic features of Rainer Forst’s theory of toleration and Axel Honneth’s theory of the struggle for recognition are presented, in order to develop a more substantial understanding of the relationship between the concepts of toleration and recognition. One lesson from Forst is that toleration is a normatively dependent concept, i.e., that it is impossible to deduce principles for toleration and its limits from a theory of toleration as such. A central lesson from Honneth is that recognition – understood as a basic human need – is always conflictual and therefore dynamic.Accordingly, a main point in the paper is that the theory of struggles for and about recognition (where struggles for designates struggles within an established order of recognition, and struggles about designates struggles that challenge established orders of recognition may clarify what

  15. Automatic object recognition

    Science.gov (United States)

    Ranganath, H. S.; Mcingvale, Pat; Sage, Heinz

    1988-01-01

    Geometric and intensity features are very useful in object recognition. An intensity feature is a measure of contrast between object pixels and background pixels. Geometric features provide shape and size information. A model based approach is presented for computing geometric features. Knowledge about objects and imaging system is used to estimate orientation of objects with respect to the line of sight.

  16. Pattern recognition in bioinformatics.

    Science.gov (United States)

    de Ridder, Dick; de Ridder, Jeroen; Reinders, Marcel J T

    2013-09-01

    Pattern recognition is concerned with the development of systems that learn to solve a given problem using a set of example instances, each represented by a number of features. These problems include clustering, the grouping of similar instances; classification, the task of assigning a discrete label to a given instance; and dimensionality reduction, combining or selecting features to arrive at a more useful representation. The use of statistical pattern recognition algorithms in bioinformatics is pervasive. Classification and clustering are often applied to high-throughput measurement data arising from microarray, mass spectrometry and next-generation sequencing experiments for selecting markers, predicting phenotype and grouping objects or genes. Less explicitly, classification is at the core of a wide range of tools such as predictors of genes, protein function, functional or genetic interactions, etc., and used extensively in systems biology. A course on pattern recognition (or machine learning) should therefore be at the core of any bioinformatics education program. In this review, we discuss the main elements of a pattern recognition course, based on material developed for courses taught at the BSc, MSc and PhD levels to an audience of bioinformaticians, computer scientists and life scientists. We pay attention to common problems and pitfalls encountered in applications and in interpretation of the results obtained.

  17. Autonomy and Recognition

    Directory of Open Access Journals (Sweden)

    Miguel Giusti

    2007-04-01

    Full Text Available Resumen:El presente ensayo contiene dos partes. En la primera se hace una breve descripción de las carencias de la reflexión moral a las que parece venir al encuentro el concepto de reconocimiento. Charles Taylor y Axel Honneth, protagonistas en estos debates, dan buenas razones para dirigir la discusión hacia el tema del reconocimiento, pero no coinciden ni en su definición, ni en el modo de recuperar la tesis de Hegel, ni tampoco en la forma de tratar la relación entre autonomía y reconocimiento. En la segunda parte se analiza la concepción propiamente hegeliana, con la intención de destacar el nexo esencial, no la ruptura, que existe entre la noción de reconocimiento y el modelo conceptual de la voluntad libre o del espíritu. Abstract:This essay is divided into two parts. The first one is a short description of the deficiencies of moral reflection, which seem to lead the discussion towards the concept of recognition. Charles Taylor and Axel Honneth, two of the protagonists of these debates, give very good reasons for turning the argument towards the issue of recognition, but they do not agree on its definition, on the way to recover the Hegelian thesis, or on how to approach the relationship between autonomy and recognition. The second part constitutes an analysis of the Hegelian conception of recognition, in order to highlight the essential link –rather than the rupture– between the notion of recognition and the conceptual model of free will or spirit.

  18. Galeotti on recognition as inclusion

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2008-01-01

    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 ...

  19. RECOGNITION AND ASSESSMENT IN ACCOUNTANCY

    Directory of Open Access Journals (Sweden)

    DIMA FLORIN CONSTANTIN

    2012-11-01

    Full Text Available The recognition and assessment of the component elements of the annual financial statements’ structures is crucial in order that the information released by them fulfils the qualitative characteristics and the reflected image is a “true and fair view”. Therefore, our approach takes into consideration the recognition and assessment methods for the component elements of the financial statements’ structures, as well as certain possible risks arising from the erroneous recognition or non-recognition of some of these elements.

  20. Supporting Quality Teachers with Recognition

    Science.gov (United States)

    Andrews, Hans A.

    2011-01-01

    Value has been found in providing recognition and awards programs for excellent teachers. Research has also found a major lack of these programs in both the USA and in Australia. Teachers receiving recognition and awards for their teaching have praised recognition programs as providing motivation for them to continue high-level instruction.…

  1. Superficial Priming in Episodic Recognition

    Science.gov (United States)

    Dopkins, Stephen; Sargent, Jesse; Ngo, Catherine T.

    2010-01-01

    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…

  2. Word Recognition in Auditory Cortex

    Science.gov (United States)

    DeWitt, Iain D. J.

    2013-01-01

    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…

  3. Six Regularities of Source Recognition

    Science.gov (United States)

    Glanzer, Murray; Hilford, Andy; Kim, Kisok

    2004-01-01

    In recent work, researchers have shown that source-recognition memory can be incorporated in an extended signal detection model that covers both it and item-recognition memory (A. Hilford, M. Glanzer, K. Kim, & L. T. DeCarlo, 2002). In 5 experiments, using learning variables that have an established effect on item recognition, the authors tested…

  4. Forensic Face Recognition: A Survey

    NARCIS (Netherlands)

    Ali, Tauseef; Spreeuwers, Luuk; Veldhuis, Raymond; Quaglia, Adamo; Epifano, Calogera M.

    2012-01-01

    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

  5. Vehicle License Plate Recognition Syst

    Directory of Open Access Journals (Sweden)

    Meenakshi,R. B. Dubey

    2012-12-01

    Full Text Available The vehicle license plate recognition system has greater efficiency for vehicle monitoring in automatic zone access control. This Plate recognition system will avoid special tags, since all vehicles possess a unique registration number plate. A number of techniques have been used for car plate characters recognition. This system uses neural network character recognition and pattern matching of characters as two character recognition techniques. In this approach multilayer feed-forward back-propagation algorithm is used. The performance of the proposed algorithm has been tested on several car plates and provides very satisfactory results.

  6. Visual affect recognition

    CERN Document Server

    Stathopoulou, I-O

    2010-01-01

    It is generally known that human faces, as well as body motions and gestures, provide a wealth of information about a person, such as age, race, sex and emotional state. This monograph primarily studies the perception of facial expression of emotion, and secondarily of motion and gestures, with the purpose of developing a fully automated visual affect recognition system for use in modes of human/computer interaction. The book begins with a survey of the literature on emotion perception, followed by a description of empirical studies conducted with human participants and the construction of a '

  7. Advances in Speech Recognition

    CERN Document Server

    Neustein, Amy

    2010-01-01

    This volume is comprised of contributions from eminent leaders in the speech industry, and presents a comprehensive and in depth analysis of the progress of speech technology in the topical areas of mobile settings, healthcare and call centers. The material addresses the technical aspects of voice technology within the framework of societal needs, such as the use of speech recognition software to produce up-to-date electronic health records, not withstanding patients making changes to health plans and physicians. Included will be discussion of speech engineering, linguistics, human factors ana

  8. Recent progress in fingerprint recognition

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Fingerprint recognition has been increasingly used to realize personal identification in civilian's daily life, such as ID card, fingerprints hard disk and so on. Great improvement has been achieved in the on-line fingerprint sensing technology and automatic fingerprint recognition algorithms. Various fingerprint recognition techniques, including fingerprint acquisition, classification, enhancement and matching, are highly improved. This paper overviews recent advances in fingerprint recognition and summarizes the algorithm proposed for every step with special focuses on the enhancement of low-quality fingerprints and the matching of the distorted fingerprint images. Both issues are believed to be significant and challenging tasks. In addition, we also discuss the common evaluation for the fingerprint recognition algorithm of the Fingerprint Verification Competition 2004 (FVC2004) and the Fingerprint Vendor Technology Evaluation 2003 (FpVTE2003), based on which we could measure the performance of the recognition algorithm objectively and uniformly.

  9. Human activity recognition and prediction

    CERN Document Server

    2016-01-01

    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. .

  10. [Comparative studies of face recognition].

    Science.gov (United States)

    Kawai, Nobuyuki

    2012-07-01

    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.

  11. Genetic specificity of face recognition.

    Science.gov (United States)

    Shakeshaft, Nicholas G; Plomin, Robert

    2015-10-13

    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.

  12. Speech recognition in university classrooms

    OpenAIRE

    Wald, Mike; Bain, Keith; Basson, Sara H

    2002-01-01

    The LIBERATED LEARNING PROJECT (LLP) is an applied research project studying two core questions: 1) Can speech recognition (SR) technology successfully digitize lectures to display spoken words as text in university classrooms? 2) Can speech recognition technology be used successfully as an alternative to traditional classroom notetaking for persons with disabilities? This paper addresses these intriguing questions and explores the underlying complex relationship between speech recognition te...

  13. Pilgrims Face Recognition Dataset -- HUFRD

    OpenAIRE

    Aly, Salah A.

    2012-01-01

    In this work, we define a new pilgrims face recognition dataset, called HUFRD dataset. The new developed dataset presents various pilgrims' images taken from outside the Holy Masjid El-Harram in Makkah during the 2011-2012 Hajj and Umrah seasons. Such dataset will be used to test our developed facial recognition and detection algorithms, as well as assess in the missing and found recognition system \\cite{crowdsensing}.

  14. Speech Recognition on Mobile Devices

    DEFF Research Database (Denmark)

    Tan, Zheng-Hua; Lindberg, Børge

    2010-01-01

    The enthusiasm of deploying automatic speech recognition (ASR) on mobile devices is driven both by remarkable advances in ASR technology and by the demand for efficient user interfaces on such devices as mobile phones and personal digital assistants (PDAs). This chapter presents an overview of ASR...... in the mobile context covering motivations, challenges, fundamental techniques and applications. Three ASR architectures are introduced: embedded speech recognition, distributed speech recognition and network speech recognition. Their pros and cons and implementation issues are discussed. Applications within...... command and control, text entry and search are presented with an emphasis on mobile text entry....

  15. Frequency-Based Fingerprint Recognition

    Science.gov (United States)

    Aguilar, Gualberto; Sánchez, Gabriel; Toscano, Karina; Pérez, Héctor

    abstract Fingerprint recognition is one of the most popular methods used for identification with greater success degree. Fingerprint has unique characteristics called minutiae, which are points where a curve track ends, intersects, or branches off. In this chapter a fingerprint recognition method is proposed in which a combination of Fast Fourier Transform (FFT) and Gabor filters is used for image enhancement. A novel recognition stage using local features for recognition is also proposed. Also a verification stage is introduced to be used when the system output has more than one person.

  16. Markov Models for Handwriting Recognition

    CERN Document Server

    Plotz, Thomas

    2011-01-01

    Since their first inception, automatic reading systems have evolved substantially, yet the recognition of handwriting remains an open research problem due to its substantial variation in appearance. With the introduction of Markovian models to the field, a promising modeling and recognition paradigm was established for automatic handwriting recognition. However, no standard procedures for building Markov model-based recognizers have yet been established. This text provides a comprehensive overview of the application of Markov models in the field of handwriting recognition, covering both hidden

  17. Study of Face Recognition Techniques

    Directory of Open Access Journals (Sweden)

    Sangeeta Kaushik

    2014-12-01

    Full Text Available A study of both face recognition and detection techniques is carried out using the algorithms like Principal Component Analysis (PCA, Kernel Principal Component Analysis (KPCA, Linear Discriminant Analysis (LDA and Line Edge Map (LEM. These algorithms show different rates of accuracy under different conditions. The automatic recognition of human faces presents a challenge to the pattern recognition community. Typically, human faces are different in shapes with minor similarity from person to person. Furthermore, lighting condition changes, facial expressions and pose variations further complicate the face recognition task as one of the difficult problems in pattern analysis.

  18. Radically enhanced molecular recognition

    KAUST Repository

    Trabolsi, Ali

    2009-12-17

    The tendency for viologen radical cations to dimerize has been harnessed to establish a recognition motif based on their ability to form extremely strong inclusion complexes with cyclobis(paraquat-p-phenylene) in its diradical dicationic redox state. This previously unreported complex involving three bipyridinium cation radicals increases the versatility of host-guest chemistry, extending its practice beyond the traditional reliance on neutral and charged guests and hosts. In particular, transporting the concept of radical dimerization into the field of mechanically interlocked molecules introduces a higher level of control within molecular switches and machines. Herein, we report that bistable and tristable [2]rotaxanes can be switched by altering electrochemical potentials. In a tristable [2]rotaxane composed of a cyclobis(paraquat-p-phenylene) ring and a dumbbell with tetrathiafulvalene, dioxynaphthalene and bipyridinium recognition sites, the position of the ring can be switched. On oxidation, it moves from the tetrathiafulvalene to the dioxynaphthalene, and on reduction, to the bipyridinium radical cation, provided the ring is also reduced simultaneously to the diradical dication. © 2010 Macmillan Publishers Limited. All rights reserved.

  19. Attribute measure recognition approach and its applications to emitter recognition

    Institute of Scientific and Technical Information of China (English)

    GUAN Xin; HE You; YI Xiao

    2005-01-01

    This paper studies the emitter recognition problem. A new recognition method based on attribute measure for emitter recognition is put forward. The steps of the method are presented. The approach to determining the weight coefficient is also discussed. Moreover, considering the temporal redundancy of emitter information detected by multi-sensor system, this new recognition method is generalized to multi-sensor system. A method based on the combination of attribute measure and D-S evidence theory is proposed. The implementation of D-S reasoning is always restricted by basic probability assignment function. Constructing basic probability assignment function based on attribute measure is presented in multi-sensor recognition system. Examples of recognizing the emitter purpose and system are selected to demonstrate the method proposed. Experimental results show that the performance of this new method is accurate and effective.

  20. The Legal Recognition of Sign Languages

    Science.gov (United States)

    De Meulder, Maartje

    2015-01-01

    This article provides an analytical overview of the different types of explicit legal recognition of sign languages. Five categories are distinguished: constitutional recognition, recognition by means of general language legislation, recognition by means of a sign language law or act, recognition by means of a sign language law or act including…

  1. Iris Recognition Using Wavelet

    Directory of Open Access Journals (Sweden)

    Khaliq Masood

    2013-08-01

    Full Text Available Biometric systems are getting more attention in the present era. Iris recognition is one of the most secure and authentic among the other biometrics and this field demands more authentic, reliable and fast algorithms to implement these biometric systems in real time. In this paper, an efficient localization technique is presented to identify pupil and iris boundaries using histogram of the iris image. Two small portions of iris have been used for polar transformation to reduce computational time and to increase the efficiency of the system. Wavelet transform is used for feature vector generation. Rotation of iris is compensated without shifts in the iris code. System is tested on Multimedia University Iris Database and results show that proposed system has encouraging performance.

  2. Chemical recognition software

    Energy Technology Data Exchange (ETDEWEB)

    Wagner, J.S.; Trahan, M.W.; Nelson, W.E.; Hargis, P.H. Jr.; Tisone, G.C.

    1994-06-01

    We have developed a capability to make real time concentration measurements of individual chemicals in a complex mixture using a multispectral laser remote sensing system. Our chemical recognition and analysis software consists of three parts: (1) a rigorous multivariate analysis package for quantitative concentration and uncertainty estimates, (2) a genetic optimizer which customizes and tailors the multivariate algorithm for a particular application, and (3) an intelligent neural net chemical filter which pre-selects from the chemical database to find the appropriate candidate chemicals for quantitative analyses by the multivariate algorithms, as well as providing a quick-look concentration estimate and consistency check. Detailed simulations using both laboratory fluorescence data and computer synthesized spectra indicate that our software can make accurate concentration estimates from complex multicomponent mixtures, even when the mixture is noisy and contaminated with unknowns.

  3. Chemical recognition software

    Energy Technology Data Exchange (ETDEWEB)

    Wagner, J.S.; Trahan, M.W.; Nelson, W.E.; Hargis, P.J. Jr.; Tisone, G.C.

    1994-12-01

    We have developed a capability to make real time concentration measurements of individual chemicals in a complex mixture using a multispectral laser remote sensing system. Our chemical recognition and analysis software consists of three parts: (1) a rigorous multivariate analysis package for quantitative concentration and uncertainty estimates, (2) a genetic optimizer which customizes and tailors the multivariate algorithm for a particular application, and (3) an intelligent neural net chemical filter which pre-selects from the chemical database to find the appropriate candidate chemicals for quantitative analyses by the multivariate algorithms, as well as providing a quick-look concentration estimate and consistency check. Detailed simulations using both laboratory fluorescence data and computer synthesized spectra indicate that our software can make accurate concentration estimates from complex multicomponent mixtures. even when the mixture is noisy and contaminated with unknowns.

  4. SAR: Stroke Authorship Recognition

    KAUST Repository

    Shaheen, Sara

    2015-10-15

    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? Also, could training methods be devised to develop particular styles? To answer these questions, we propose the Stroke Authorship Recognition (SAR) approach, a novel method that distinguishes the authorship of 2D digitized drawings. SAR converts a drawing into a histogram of stroke attributes that is discriminative of authorship. We provide extensive classification experiments on a large variety of data sets, which validate SAR\\'s ability to distinguish unique authorship of artists and designers. We also demonstrate the usefulness of SAR in several applications including the detection of fraudulent sketches, the training and monitoring of artists in learning a particular new style and the first quantitative way to measure the quality of automatic sketch synthesis tools. © 2015 The Eurographics Association and John Wiley & Sons Ltd.

  5. Forensic Face Recognition: A Survey

    NARCIS (Netherlands)

    Ali, Tauseef; Veldhuis, Raymond; Spreeuwers, Luuk

    2010-01-01

    Beside a few papers which focus on the forensic aspects of automatic face recognition, there is not much published about it in contrast to the literature on developing new techniques and methodologies for biometric face recognition. In this report, we review forensic facial identification which is t

  6. Side-View Face Recognition

    NARCIS (Netherlands)

    Santemiz, Pinar; Spreeuwers, Luuk J.; Veldhuis, Raymond N.J.; Biggelaar , van den Olivier

    2011-01-01

    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 th

  7. Quantum-Limited Image Recognition

    Science.gov (United States)

    1989-12-01

    J. S. Bomba ,’Alpha-numeric character recognition using local operations,’ Fall Joint Comput. Conf., 218-224 (1959). 53. D. Barnea and H. Silverman...for Chapter 6 1. J. S. Bomba ,’Alpha-numeric character recognition using local operations,’ Fall Joint Comput. Conf., 218-224 (1959). 2. D. Bamea and H

  8. FILTWAM and Voice Emotion Recognition

    NARCIS (Netherlands)

    Bahreini, Kiavash; Nadolski, Rob; Westera, Wim

    2014-01-01

    This paper introduces the voice emotion recognition part of our framework for improving learning through webcams and microphones (FILTWAM). This framework enables multimodal emotion recognition of learners during game-based learning. The main goal of this study is to validate the use of microphone d

  9. Coordinate Transformations in Object Recognition

    Science.gov (United States)

    Graf, Markus

    2006-01-01

    A basic problem of visual perception is how human beings recognize objects after spatial transformations. Three central classes of findings have to be accounted for: (a) Recognition performance varies systematically with orientation, size, and position; (b) recognition latencies are sequentially additive, suggesting analogue transformation…

  10. Pattern Recognition by Combined Invariants

    Institute of Scientific and Technical Information of China (English)

    WANG Xiaohong; ZHAO Rongchun

    2001-01-01

    A feature-based recognition of objectsor patterns independent of their position, size, orien-tation and other variations has been the goal of muchrecent research. The existing approaches to invarianttwo-dimensional pattern recognition are useless whenpattern is blurred. In this paper, we present a novelpattern recognition system which can solve the prob-lem by using combined invariants as image features.The classification technique we choose for our systemis weighted normalized cross correlation. The mean ofthe intraclass standard deviations of the kth featureover the total number of prototypes for each class isused as a weighting factor during the classification pro-cess to improve recognition accuracy. The feasibilityof our pattern recognition system and the invarianceof the combined features with respect to translation,scaling, rotation and blurring are approved by numer-ical experiments on head images.

  11. Online handwritten mathematical expression recognition

    Science.gov (United States)

    Büyükbayrak, Hakan; Yanikoglu, Berrin; Erçil, Aytül

    2007-01-01

    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.

  12. Viewpoint Manifolds for Action Recognition

    Directory of Open Access Journals (Sweden)

    Souvenir Richard

    2009-01-01

    Full Text Available Abstract Action recognition from video is a problem that has many important applications to human motion analysis. In real-world settings, the viewpoint of the camera cannot always be fixed relative to the subject, so view-invariant action recognition methods are needed. Previous view-invariant methods use multiple cameras in both the training and testing phases of action recognition or require storing many examples of a single action from multiple viewpoints. In this paper, we present a framework for learning a compact representation of primitive actions (e.g., walk, punch, kick, sit that can be used for video obtained from a single camera for simultaneous action recognition and viewpoint estimation. Using our method, which models the low-dimensional structure of these actions relative to viewpoint, we show recognition rates on a publicly available dataset previously only achieved using multiple simultaneous views.

  13. Viewpoint Manifolds for Action Recognition

    Directory of Open Access Journals (Sweden)

    Richard Souvenir

    2009-01-01

    Full Text Available Action recognition from video is a problem that has many important applications to human motion analysis. In real-world settings, the viewpoint of the camera cannot always be fixed relative to the subject, so view-invariant action recognition methods are needed. Previous view-invariant methods use multiple cameras in both the training and testing phases of action recognition or require storing many examples of a single action from multiple viewpoints. In this paper, we present a framework for learning a compact representation of primitive actions (e.g., walk, punch, kick, sit that can be used for video obtained from a single camera for simultaneous action recognition and viewpoint estimation. Using our method, which models the low-dimensional structure of these actions relative to viewpoint, we show recognition rates on a publicly available dataset previously only achieved using multiple simultaneous views.

  14. Optimizing Face Recognition Using PCA

    Directory of Open Access Journals (Sweden)

    Manal Abdullah

    2012-03-01

    Full Text Available Principle Component Analysis PCA is a classical feature extraction and data representation technique widely used in pattern recognition. It is one of the most successful techniques in face recognition. But it has drawback of high computational especially for big size database. This paper conducts a study to optimize the time complexity of PCA (eigenfaces that does not affects the recognition performance. The authors minimize the participated eigenvectors which consequently decreases the computational time. A comparison is done to compare the differences between the recognition time in the original algorithm and in the enhanced algorithm. The performance of the original and the enhanced proposed algorithm is tested on face94 face database. Experimental results show that the recognition time is reduced by 35% by applying our proposed enhanced algorithm. DET Curves are used to illustrate the experimental results.

  15. Optimizing Face Recognition Using PCA

    Directory of Open Access Journals (Sweden)

    Manal Abdullah

    2012-04-01

    Full Text Available Principle Component Analysis PCA is a classical feature extraction and data representation technique widely used in pattern recognition. It is one of the most successful techniques in face recognition. But it has drawback of high computational especially for big size database. This paper conducts a study to optimize the time complexity of PCA (eigenfaces that does not affects the recognition performance. The authorsminimize the participated eigenvectors which consequently decreases the computational time. A comparison is done to compare the differences between the recognition time in the original algorithm and in the enhanced algorithm. The performance of the original and the enhanced proposed algorithm is tested on face94 face database. Experimental results show that the recognition time is reduced by 35% by applying our proposed enhanced algorithm. DET Curves are used to illustrate the experimental results.

  16. Recognition memory impairments caused by false recognition of novel objects.

    Science.gov (United States)

    Yeung, Lok-Kin; Ryan, Jennifer D; Cowell, Rosemary A; Barense, Morgan D

    2013-11-01

    A fundamental assumption underlying most current theories of amnesia is that memory impairments arise because previously studied information either is lost rapidly or is made inaccessible (i.e., the old information appears to be new). Recent studies in rodents have challenged this view, suggesting instead that under conditions of high interference, recognition memory impairments following medial temporal lobe damage arise because novel information appears as though it has been previously seen. Here, we developed a new object recognition memory paradigm that distinguished whether object recognition memory impairments were driven by previously viewed objects being treated as if they were novel or by novel objects falsely recognized as though they were previously seen. In this indirect, eyetracking-based passive viewing task, older adults at risk for mild cognitive impairment showed false recognition to high-interference novel items (with a significant degree of feature overlap with previously studied items) but normal novelty responses to low-interference novel items (with a lower degree of feature overlap). The indirect nature of the task minimized the effects of response bias and other memory-based decision processes, suggesting that these factors cannot solely account for false recognition. These findings support the counterintuitive notion that recognition memory impairments in this memory-impaired population are not characterized by forgetting but rather are driven by the failure to differentiate perceptually similar objects, leading to the false recognition of novel objects as having been seen before.

  17. Kernel learning algorithms for face recognition

    CERN Document Server

    Li, Jun-Bao; Pan, Jeng-Shyang

    2013-01-01

    Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new

  18. Spectral recognition of graphs

    Directory of Open Access Journals (Sweden)

    Cvetković Dragoš

    2012-01-01

    Full Text Available At some time, in the childhood of spectral graph theory, it was conjectured that non-isomorphic graphs have different spectra, i.e. that graphs are characterized by their spectra. Very quickly this conjecture was refuted and numerous examples and families of non-isomorphic graphs with the same spectrum (cospectral graphs were found. Still some graphs are characterized by their spectra and several mathematical papers are devoted to this topic. In applications to computer sciences, spectral graph theory is considered as very strong. The benefit of using graph spectra in treating graphs is that eigenvalues and eigenvectors of several graph matrices can be quickly computed. Spectral graph parameters contain a lot of information on the graph structure (both global and local including some information on graph parameters that, in general, are computed by exponential algorithms. Moreover, in some applications in data mining, graph spectra are used to encode graphs themselves. The Euclidean distance between the eigenvalue sequences of two graphs on the same number of vertices is called the spectral distance of graphs. Some other spectral distances (also based on various graph matrices have been considered as well. Two graphs are considered as similar if their spectral distance is small. If two graphs are at zero distance, they are cospectral. In this sense, cospectral graphs are similar. Other spectrally based measures of similarity between networks (not necessarily having the same number of vertices have been used in Internet topology analysis, and in other areas. The notion of spectral distance enables the design of various meta-heuristic (e.g., tabu search, variable neighbourhood search algorithms for constructing graphs with a given spectrum (spectral graph reconstruction. Several spectrally based pattern recognition problems appear in many areas (e.g., image segmentation in computer vision, alignment of protein-protein interaction networks in bio

  19. Logo Recognition Theory and Practice

    CERN Document Server

    Chen, Jingying

    2011-01-01

    Used by companies, organizations, and even individuals to promote recognition of their brand, logos can also act as a valuable means of identifying the source of a document. E-business applications can retrieve and catalog products according to their logos. Governmental agencies can easily inspect goods using smart mobile devices that use logo recognition techniques. However, because logos are two-dimensional shapes of varying complexity, the recognition process can be challenging. Although promising results have been found for clean logos, they have not been as robust for noisy logos. Logo Re

  20. Macromolecular recognition: Recognition of polymer side chains by cyclodextrin

    Science.gov (United States)

    Hashidzume, Akihito; Harada, Akira

    2015-12-01

    The interaction of cyclodextrins (CD) with water soluble polymers possessing guest residues has been investigated as model systems in biological molecular recognition. The selectivity of interaction of CD with polymer-carrying guest residues is controlled by polymer chains, i.e., the steric effect of polymer main chain, the conformational effect of polymer main chain, and multi-site interaction. Macroscopic assemblies have been also realized based on molecular recognition using polyacrylamide-based gels possessing CD and guest residues.

  1. Effective indexing for face recognition

    Science.gov (United States)

    Sochenkov, I.; Sochenkova, A.; Vokhmintsev, A.; Makovetskii, A.; Melnikov, A.

    2016-09-01

    Face recognition is one of the most important tasks in computer vision and pattern recognition. Face recognition is useful for security systems to provide safety. In some situations it is necessary to identify the person among many others. In this case this work presents new approach in data indexing, which provides fast retrieval in big image collections. Data indexing in this research consists of five steps. First, we detect the area containing face, second we align face, and then we detect areas containing eyes and eyebrows, nose, mouth. After that we find key points of each area using different descriptors and finally index these descriptors with help of quantization procedure. The experimental analysis of this method is performed. This paper shows that performing method has results at the level of state-of-the-art face recognition methods, but it is also gives results fast that is important for the systems that provide safety.

  2. Iris Recognition using Orthogonal Transforms

    Directory of Open Access Journals (Sweden)

    M.Mani Roja

    2012-12-01

    Full Text Available Iris Recognition is a biometric recognition technique in which features of the iris are used to uniquely identify individuals. Iris recognition has over the years emerged as one of the most accuratebiometric techniques as opposed to other biometric techniques like face, signature and fingerprint. First, the iris image is pre processed using canny edge detector using a Gaussian filter. The iris edge and the pupil edge are extracted using image morphological operation, image opening. After normalization of red, green and blue components of the colour iris using Euclidean distance method, they are combined to form the localized colour iris. For feature vectors extraction, orthogonal transforms like discrete cosine transform, discrete sine transform and discrete Fourier transform have been considered. The proposed iris recognition system is very time efficient and it takes less than 1 second to grant authentication.

  3. Similarity measures for face recognition

    CERN Document Server

    Vezzetti, Enrico

    2015-01-01

    Face recognition has several applications, including security, such as (authentication and identification of device users and criminal suspects), and in medicine (corrective surgery and diagnosis). Facial recognition programs rely on algorithms that can compare and compute the similarity between two sets of images. This eBook explains some of the similarity measures used in facial recognition systems in a single volume. Readers will learn about various measures including Minkowski distances, Mahalanobis distances, Hansdorff distances, cosine-based distances, among other methods. The book also summarizes errors that may occur in face recognition methods. Computer scientists "facing face" and looking to select and test different methods of computing similarities will benefit from this book. The book is also useful tool for students undertaking computer vision courses.

  4. Gesture recognition on smart cameras

    Science.gov (United States)

    Dziri, Aziz; Chevobbe, Stephane; Darouich, Mehdi

    2013-02-01

    Gesture recognition is a feature in human-machine interaction that allows more natural interaction without the use of complex devices. For this reason, several methods of gesture recognition have been developed in recent years. However, most real time methods are designed to operate on a Personal Computer with high computing resources and memory. In this paper, we analyze relevant methods found in the literature in order to investigate the ability of smart camera to execute gesture recognition algorithms. We elaborate two hand gesture recognition pipelines. The first method is based on invariant moments extraction and the second on finger tips detection. The hand detection method used for both pipeline is based on skin color segmentation. The results obtained show that the un-optimized versions of invariant moments method and finger tips detection method can reach 10 fps on embedded processor and use about 200 kB of memory.

  5. Pattern recognition and string matching

    CERN Document Server

    Cheng, Xiuzhen

    2002-01-01

    The research and development of pattern recognition have proven to be of importance in science, technology, and human activity. Many useful concepts and tools from different disciplines have been employed in pattern recognition. Among them is string matching, which receives much theoretical and practical attention. String matching is also an important topic in combinatorial optimization. This book is devoted to recent advances in pattern recognition and string matching. It consists of twenty eight chapters written by different authors, addressing a broad range of topics such as those from classifica­ tion, matching, mining, feature selection, and applications. Each chapter is self-contained, and presents either novel methodological approaches or applications of existing theories and techniques. The aim, intent, and motivation for publishing this book is to pro­ vide a reference tool for the increasing number of readers who depend upon pattern recognition or string matching in some way. This includes student...

  6. Defect Recognition in Thermosonic Imaging

    Institute of Scientific and Technical Information of China (English)

    CHEN Dapeng; WU Naiming; ZHANG Zheng

    2012-01-01

    This work is aimed at developing an effective method for defect recognition in thermosonic imaging.The heat mechanism of thermosonic imaging is introduced,and the problem for defect recognition is discussed.For this purpose,defect existing in the inner wall of a metal pipeline specimen and defects embedded in a carbon fiber reinforced plastic (CFRP) laminate are tested.The experimental data are processed by pulse phase thermography (PPT) method to show the phase images at different frequencies,and the characteristic of phase angle vs frequency curve of thermal anomalies and sound area is analyzed.A binary image,which is based on the characteristic value of defects,is obtained by a new recognition algorithm to show the defects.Results demonstrate good defect recognition performance for thermosonic imaging,and the reliability of this technique can be improved by the method.

  7. Pattern Recognition Theory of Mind

    OpenAIRE

    2009-01-01

    I propose that pattern recognition, memorization and processing are key concepts that can be a principle set for the theoretical modeling of the mind function. Most of the questions about the mind functioning can be answered by a descriptive modeling and definitions from these principles. An understandable consciousness definition can be drawn based on the assumption that a pattern recognition system can recognize its own patterns of activity. The principles, descriptive modeling and definiti...

  8. [Neurological disease and facial recognition].

    Science.gov (United States)

    Kawamura, Mitsuru; Sugimoto, Azusa; Kobayakawa, Mutsutaka; Tsuruya, Natsuko

    2012-07-01

    To discuss the neurological basis of facial recognition, we present our case reports of impaired recognition and a review of previous literature. First, we present a case of infarction and discuss prosopagnosia, which has had a large impact on face recognition research. From a study of patient symptoms, we assume that prosopagnosia may be caused by unilateral right occipitotemporal lesion and right cerebral dominance of facial recognition. Further, circumscribed lesion and degenerative disease may also cause progressive prosopagnosia. Apperceptive prosopagnosia is observed in patients with posterior cortical atrophy (PCA), pathologically considered as Alzheimer's disease, and associative prosopagnosia in frontotemporal lobar degeneration (FTLD). Second, we discuss face recognition as part of communication. Patients with Parkinson disease show social cognitive impairments, such as difficulty in facial expression recognition and deficits in theory of mind as detected by the reading the mind in the eyes test. Pathological and functional imaging studies indicate that social cognitive impairment in Parkinson disease is possibly related to damages in the amygdalae and surrounding limbic system. The social cognitive deficits can be observed in the early stages of Parkinson disease, and even in the prodromal stage, for example, patients with rapid eye movement (REM) sleep behavior disorder (RBD) show impairment in facial expression recognition. Further, patients with myotonic dystrophy type 1 (DM 1), which is a multisystem disease that mainly affects the muscles, show social cognitive impairment similar to that of Parkinson disease. Our previous study showed that facial expression recognition impairment of DM 1 patients is associated with lesion in the amygdalae and insulae. Our study results indicate that behaviors and personality traits in DM 1 patients, which are revealed by social cognitive impairment, are attributable to dysfunction of the limbic system.

  9. On Tangut Historical Documents Recognition*

    Science.gov (United States)

    Liu, Changqing

    As the Tangut studies have made progress, a considerable number of Tangut historical documents' copies have been published. It is of great importance to carry out digitalization and domestication of these copies. The paper firstly makes an initial processing of images by global threshold, then dissect the photocopies by scanning. Finally adopts the recognition approach of principal component analysis. The experiment shows that a better recognition can be achieved by calculation without extra time.

  10. Voice congruency facilitates word recognition.

    Directory of Open Access Journals (Sweden)

    Sandra Campeanu

    Full Text Available Behavioral studies of spoken word memory have shown that context congruency facilitates both word and source recognition, though the level at which context exerts its influence remains equivocal. We measured event-related potentials (ERPs while participants performed both types of recognition task with words spoken in four voices. Two voice parameters (i.e., gender and accent varied between speakers, with the possibility that none, one or two of these parameters was congruent between study and test. Results indicated that reinstating the study voice at test facilitated both word and source recognition, compared to similar or no context congruency at test. Behavioral effects were paralleled by two ERP modulations. First, in the word recognition test, the left parietal old/new effect showed a positive deflection reflective of context congruency between study and test words. Namely, the same speaker condition provided the most positive deflection of all correctly identified old words. In the source recognition test, a right frontal positivity was found for the same speaker condition compared to the different speaker conditions, regardless of response success. Taken together, the results of this study suggest that the benefit of context congruency is reflected behaviorally and in ERP modulations traditionally associated with recognition memory.

  11. Pattern Recognition Using Neural Networks

    Directory of Open Access Journals (Sweden)

    Santaji Ghorpade

    2010-12-01

    Full Text Available Face Recognition has been identified as one of the attracting research areas and it has drawn the attention of many researchers due to its varying applications such as security systems, medical systems,entertainment, etc. Face recognition is the preferred mode of identification by humans: it is natural,robust and non-intrusive. A wide variety of systems requires reliable personal recognition schemes to either confirm or determine the identity of an individual requesting their services. The purpose of such schemes is to ensure that the rendered services are accessed only by a legitimate user and no one else.Examples of such applications include secure access to buildings, computer systems, laptops, cellular phones, and ATMs. In the absence of robust personal recognition schemes, these systems are vulnerable to the wiles of an impostor.In this paper we have developed and illustrated a recognition system for human faces using a novel Kohonen self-organizing map (SOM or Self-Organizing Feature Map (SOFM based retrieval system.SOM has good feature extracting property due to its topological ordering. The Facial Analytics results for the 400 images of AT&T database reflects that the face recognition rate using one of the neural network algorithm SOM is 85.5% for 40 persons.

  12. Holistic processing predicts face recognition.

    Science.gov (United States)

    Richler, Jennifer J; Cheung, Olivia S; Gauthier, Isabel

    2011-04-01

    The concept of holistic processing is a cornerstone of face-recognition research. In the study reported here, we demonstrated that holistic processing predicts face-recognition abilities on the Cambridge Face Memory Test and on a perceptual face-identification task. Our findings validate a large body of work that relies on the assumption that holistic processing is related to face recognition. These findings also reconcile the study of face recognition with the perceptual-expertise work it inspired; such work links holistic processing of objects with people's ability to individuate them. Our results differ from those of a recent study showing no link between holistic processing and face recognition. This discrepancy can be attributed to the use in prior research of a popular but flawed measure of holistic processing. Our findings salvage the central role of holistic processing in face recognition and cast doubt on a subset of the face-perception literature that relies on a problematic measure of holistic processing.

  13. Comparing Face Detection and Recognition Techniques

    OpenAIRE

    Korra, Jyothi

    2016-01-01

    This paper implements and compares different techniques for face detection and recognition. One is find where the face is located in the images that is face detection and second is face recognition that is identifying the person. We study three techniques in this paper: Face detection using self organizing map (SOM), Face recognition by projection and nearest neighbor and Face recognition using SVM.

  14. Kazakh Traditional Dance Gesture Recognition

    Science.gov (United States)

    Nussipbekov, A. K.; Amirgaliyev, E. N.; Hahn, Minsoo

    2014-04-01

    Full body gesture recognition is an important and interdisciplinary research field which is widely used in many application spheres including dance gesture recognition. The rapid growth of technology in recent years brought a lot of contribution in this domain. However it is still challenging task. In this paper we implement Kazakh traditional dance gesture recognition. We use Microsoft Kinect camera to obtain human skeleton and depth information. Then we apply tree-structured Bayesian network and Expectation Maximization algorithm with K-means clustering to calculate conditional linear Gaussians for classifying poses. And finally we use Hidden Markov Model to detect dance gestures. Our main contribution is that we extend Kinect skeleton by adding headwear as a new skeleton joint which is calculated from depth image. This novelty allows us to significantly improve the accuracy of head gesture recognition of a dancer which in turn plays considerable role in whole body gesture recognition. Experimental results show the efficiency of the proposed method and that its performance is comparable to the state-of-the-art system performances.

  15. An audiovisual emotion recognition system

    Science.gov (United States)

    Han, Yi; Wang, Guoyin; Yang, Yong; He, Kun

    2007-12-01

    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.

  16. Early development of visual recognition.

    Science.gov (United States)

    Plebe, Alessio; Domenella, Rosaria Grazia

    2006-01-01

    The most important ability of the human vision is object recognition, yet it is exactly the less understood aspect of the vision system. Computational models have been helpful in progressing towards an explanation of this obscure cognitive ability, and today it is possible to conceive more refined models, thanks to the new availability of neuroscientific data about the human visual cortex. This work proposes a model of the development of the object recognition capability, under a different perspective with respect to the most common approaches, with a precise theoretical epistemology. It is assumed that the main processing functions involved in recognition are not genetically determined and hardwired in the neural circuits, but are the result of interactions between epigenetic influences and the basic neural plasticity mechanisms. The model is organized in modules related with the main visual biological areas, and is implemented mainly using the LISSOM architecture, a recent self-organizing algorithm closely reflecting the essential behavior of cortical circuits.

  17. Mandarin recognition over the telephone

    Science.gov (United States)

    Kao, Yuhung

    1996-06-01

    Mandarin Chinese is the official language in China and Taiwan, it is the native language of a quarter of the world population. As the services enabled by speech recognition technology (e.g. telephone voice dialing, information query) become more popular in English, we would like to extend this capability to other languages. Mandarin is one of the major languages under research in our laboratory. This paper describes how we extend our work in English speech recognition into Mandarin. We will described the corpus: Voice Across Taiwan, the training of a complete set of Mandarin syllable models, preliminary performance results and error analysis. A fast prototyping system was built, where a user can write any context free grammar with no restriction of vocabulary, then the grammar can be compiled into recognition models. It enables user to quickly test the performance of a new vocabulary.

  18. Mobile-Customer Identity Recognition

    Institute of Scientific and Technical Information of China (English)

    LI Zhan; XU Ji-sheng; XU Min; SUN Hong

    2005-01-01

    By utilizing artificial intelligence and pattern recognition techniques, we propose an integrated mobile-customer identity recognition approach in this paper, based on customer's behavior characteristics extracted from the customer information database. To verify the effectiveness of this approach, a test has been run on the dataset consisting of 1 000 customers in 3 consecutive months. The result is compared with the real dataset in the fourth month consisting of 162 customers, which has been set as the customers for recognition. The high correct rate of the test (96.30%), together with 1.87% of the judge-by-mistake rate and 7.82% of the leaving-out rate, demonstrates the effectiveness of this approach.

  19. Emotion-independent face recognition

    Science.gov (United States)

    De Silva, Liyanage C.; Esther, Kho G. P.

    2000-12-01

    Current face recognition techniques tend to work well when recognizing faces under small variations in lighting, facial expression and pose, but deteriorate under more extreme conditions. In this paper, a face recognition system to recognize faces of known individuals, despite variations in facial expression due to different emotions, is developed. The eigenface approach is used for feature extraction. Classification methods include Euclidean distance, back propagation neural network and generalized regression neural network. These methods yield 100% recognition accuracy when the training database is representative, containing one image representing the peak expression for each emotion of each person apart from the neutral expression. The feature vectors used for comparison in the Euclidean distance method and for training the neural network must be all the feature vectors of the training set. These results are obtained for a face database consisting of only four persons.

  20. DNA recognition by synthetic constructs.

    Science.gov (United States)

    Pazos, Elena; Mosquera, Jesús; Vázquez, M Eugenio; Mascareñas, José L

    2011-09-05

    The interaction of transcription factors with specific DNA sites is key for the regulation of gene expression. Despite the availability of a large body of structural data on protein-DNA complexes, we are still far from fully understanding the molecular and biophysical bases underlying such interactions. Therefore, the development of non-natural agents that can reproduce the DNA-recognition properties of natural transcription factors remains a major and challenging goal in chemical biology. In this review we summarize the basics of double-stranded DNA recognition by transcription factors, and describe recent developments in the design and preparation of synthetic DNA binders. We mainly focus on synthetic peptides that have been designed by following the DNA interaction of natural proteins, and we discuss how the tools of organic synthesis can be used to make artificial constructs equipped with functionalities that introduce additional properties to the recognition process, such as sensing and controllability.

  1. Gesture Recognition Using Character Recognition Techniques on Two-dimensional Eigenspace

    OpenAIRE

    大野, 宏; 山本, 正信; Ohno, Hiroshi; Yamamoto, Masanobu

    1999-01-01

    This paper describes a novel method for gesture recognition using character recognition techniques on two-dimensional eigenspace. An image-based approach can capture human body poses in 3D motion from multiple image sequences. The sequence of poses can be reduced into a trajectory on the two-dimensional eigenspace with preserving the main features in gesture, so that the gesture recognition equals the character recognition. Experiments for the gesture recognition using some character recognit...

  2. A Survey: Face Recognition Techniques

    Directory of Open Access Journals (Sweden)

    Muhammad Sharif

    2012-12-01

    Full Text Available In this study, the existing techniques of face recognition are to be encountered along with their pros and cons to conduct a brief survey. The most general methods include Eigenface (Eigenfeatures, Hidden Markov Model (HMM, geometric based and template matching approaches. This survey actually performs analysis on these approaches in order to constitute face representations which will be discussed as under. In the second phase of the survey, factors affecting the recognition rates and processes are also discussed along with the solutions provided by different authors.

  3. Simultaneous tracking and activity recognition

    DEFF Research Database (Denmark)

    Manfredotti, Cristina Elena; Fleet, David J.; Hamilton, Howard J.

    2011-01-01

    Many tracking problems involve several distinct objects interacting with each other. We develop a framework that takes into account interactions between objects allowing the recognition of complex activities. In contrast to classic approaches that consider distinct phases of tracking and activity...... be used to improve the prediction step of the tracking, while, at the same time, tracking information can be used for online activity recognition. Experimental results in two different settings show that our approach 1) decreases the error rate and improves the identity maintenance of the positional...

  4. Individual Recognition in Ant Queens

    DEFF Research Database (Denmark)

    D'Ettorre, Patrizia; Heinze, Jürgen

    2005-01-01

    Personal relationships are the cornerstone of vertebrate societies, but insect societies are either too large for individual recognition, or their members were assumed to lack the necessary cognitive abilities 1 and 2 . This paradigm has been challenged by the recent discovery that paper wasps...... recognize each other's unique facial color patterns [3] . Individual recognition is advantageous when dominance hierarchies control the partitioning of work and reproduction 2 and 4 . Here, we show that unrelated founding queens of the ant Pachycondyla villosa use chemical cues to recognize each other...

  5. Traffic-Sign Recognition Systems

    CERN Document Server

    Escalera, Sergio

    2011-01-01

    This work presents a full generic approach to the detection and recognition of traffic signs. The approach is based on the latest computer vision methods for object detection, and on powerful methods for multiclass classification. The challenge was to robustly detect a set of different sign classes in real time, and to classify each detected sign into a large, extensible set of classes. To address this challenge, several state-of-the-art methods were developed that can be used for different recognition problems. Following an introduction to the problems of traffic sign detection and categoriza

  6. Pattern Recognition Theory of Mind

    CERN Document Server

    de Paiva, Gilberto

    2009-01-01

    I propose that pattern recognition, memorization and processing are key concepts that can be a principle set for the theoretical modeling of the mind function. Most of the questions about the mind functioning can be answered by a descriptive modeling and definitions from these principles. An understandable consciousness definition can be drawn based on the assumption that a pattern recognition system can recognize its own patterns of activity. The principles, descriptive modeling and definitions can be a basis for theoretical and applied research on cognitive sciences, particularly at artificial intelligence studies.

  7. Human ear recognition by computer

    CERN Document Server

    Bhanu, Bir; Chen, Hui

    2010-01-01

    Biometrics deals with recognition of individuals based on their physiological or behavioral characteristics. The human ear is a new feature in biometrics that has several merits over the more common face, fingerprint and iris biometrics. Unlike the fingerprint and iris, it can be easily captured from a distance without a fully cooperative subject, although sometimes it may be hidden with hair, scarf and jewellery. Also, unlike a face, the ear is a relatively stable structure that does not change much with the age and facial expressions. ""Human Ear Recognition by Computer"" is the first book o

  8. Discriminative learning for speech recognition

    CERN Document Server

    He, Xiadong

    2008-01-01

    In this book, we introduce the background and mainstream methods of probabilistic modeling and discriminative parameter optimization for speech recognition. The specific models treated in depth include the widely used exponential-family distributions and the hidden Markov model. A detailed study is presented on unifying the common objective functions for discriminative learning in speech recognition, namely maximum mutual information (MMI), minimum classification error, and minimum phone/word error. The unification is presented, with rigorous mathematical analysis, in a common rational-functio

  9. Unequal recognition, misrecognition and injustice

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2012-01-01

    Euro-multiculturalism is (1) concerned with religiously defined immigrant minorities; (2) sees policies of recognition as a means to secure multicultural equality between groups; (3) endorses the moderate secularism of European states; and (4) adopts a contextualist approach to answering the norm......Euro-multiculturalism is (1) concerned with religiously defined immigrant minorities; (2) sees policies of recognition as a means to secure multicultural equality between groups; (3) endorses the moderate secularism of European states; and (4) adopts a contextualist approach to answering...... endorses moderate secularism and contextualism....

  10. Acoustic modeling for emotion recognition

    CERN Document Server

    Anne, Koteswara Rao; Vankayalapati, Hima Deepthi

    2015-01-01

     This book presents state of art research in speech emotion recognition. Readers are first presented with basic research and applications – gradually more advance information is provided, giving readers comprehensive guidance for classify emotions through speech. Simulated databases are used and results extensively compared, with the features and the algorithms implemented using MATLAB. Various emotion recognition models like Linear Discriminant Analysis (LDA), Regularized Discriminant Analysis (RDA), Support Vector Machines (SVM) and K-Nearest neighbor (KNN) and are explored in detail using prosody and spectral features, and feature fusion techniques.

  11. Pattern Recognition Based Detection Recognition of Traffic Sign Using SVM

    Directory of Open Access Journals (Sweden)

    S. Sathiya

    2014-05-01

    Full Text Available The objective of this work describes a method for Traffic sign detection and recognition from the traffic panel board(signage. It detect the traffic signs especially for Indian conditions. Images are acquired through the camera and it is invariant to size then it is scaled. It consist of the following steps, first, it detect the traffic sign, if it has sufficient contrast from the background then we use sobel edge detection technique and morphological dilation. Second, extract the detected traffic sign from the board using row count and column count. Third, to extract the feature using DCT, DWT and Hybrid DWT-DCT. In training phase, DCT 20 highest energy coefficients are extracted, In DWT 300 features extracted from each traffic sign and in Hybrid DWT-DCT 20 features are extracted. Finally recognition are performed through SVM. The application is to improve the efficiency of transportation networks through applications of communication visually impaired person wear the camera to identify the traffic destination board. Experimental results show that state-of-the-art algorithms obtains highly competitive performance and is especially efficient to different levels of corruptions. The performance of Traffic Sign recognition is evaluated for Traffic Sign board image and the system achieves a recognition rate of 86% using DCT, 90% using DWT and 96% using Hybrid DWT-DCT and SVM.

  12. Pattern recognition in speech and language processing

    CERN Document Server

    Chou, Wu

    2003-01-01

    Minimum Classification Error (MSE) Approach in Pattern Recognition, Wu ChouMinimum Bayes-Risk Methods in Automatic Speech Recognition, Vaibhava Goel and William ByrneA Decision Theoretic Formulation for Adaptive and Robust Automatic Speech Recognition, Qiang HuoSpeech Pattern Recognition Using Neural Networks, Shigeru KatagiriLarge Vocabulary Speech Recognition Based on Statistical Methods, Jean-Luc GauvainToward Spontaneous Speech Recognition and Understanding, Sadaoki FuruiSpeaker Authentication, Qi Li and Biing-Hwang JuangHMMs for Language Processing Problems, Ri

  13. Towards automatic forensic face recognition

    NARCIS (Netherlands)

    Ali, Tauseef; Spreeuwers, Luuk; Veldhuis, Raymond

    2011-01-01

    In this paper we present a methodology and experimental results for evidence evaluation in the context of forensic face recognition. In forensic applications, the matching score (hereafter referred to as similarity score) from a biometric system must be represented as a Likelihood Ratio (LR). In our

  14. Output Interference in Recognition Memory

    Science.gov (United States)

    Criss, Amy H.; Malmberg, Kenneth J.; Shiffrin, Richard M.

    2011-01-01

    Dennis and Humphreys (2001) proposed that interference in recognition memory arises solely from the prior contexts of the test word: Interference does not arise from memory traces of other words (from events prior to the study list or on the study list, and regardless of similarity to the test item). We evaluate this model using output…

  15. Face recognition, a landmarks tale

    NARCIS (Netherlands)

    Beumer, Gerrit Maarten

    2009-01-01

    Face recognition is a technology that appeals to the imagination of many people. This is particularly reflected in the popularity of science-fiction films and forensic detective series such as CSI, CSI New York, CSI Miami, Bones and NCIS. Although these series tend to be set in the present, their a

  16. Mobile Visual Recognition on Smartphones

    Directory of Open Access Journals (Sweden)

    Zhenwen Gui

    2013-01-01

    Full Text Available This paper addresses the recognition of large-scale outdoor scenes on smartphones by fusing outputs of inertial sensors and computer vision techniques. The main contributions can be summarized as follows. Firstly, we propose an ORD (overlap region divide method to plot image position area, which is fast enough to find the nearest visiting area and can also reduce the search range compared with the traditional approaches. Secondly, the vocabulary tree-based approach is improved by introducing GAGCC (gravity-aligned geometric consistency constraint. Our method involves no operation in the high-dimensional feature space and does not assume a global transform between a pair of images. Thus, it substantially reduces the computational complexity and memory usage, which makes the city scale image recognition feasible on the smartphone. Experiments on a collected database including 0.16 million images show that the proposed method demonstrates excellent recognition performance, while maintaining the average recognition time about 1 s.

  17. Action Recognition using Motion Primitives

    DEFF Research Database (Denmark)

    Moeslund, Thomas B.; Fihl, Preben; Holte, Michael Boelstoft

    The number of potential applications has made automatic recognition of human actions a very active research area. Different approaches have been followed based on trajectories through some state space. In this paper we also model an action as a trajectory through a state space, but we represent t...

  18. Motion Primitives for Action Recognition

    DEFF Research Database (Denmark)

    Fihl, Preben; Holte, Michael Boelstoft; Moeslund, Thomas B.

    2007-01-01

    The number of potential applications has made automatic recognition of human actions a very active research area. Different approaches have been followed based on trajectories through some state space. In this paper we also model an action as a trajectory through a state space, but we represent t...

  19. Emotion recognition during cocaine intoxication.

    Science.gov (United States)

    Kuypers, K P C; Steenbergen, L; Theunissen, E L; Toennes, S W; Ramaekers, J G

    2015-11-01

    Chronic or repeated cocaine use has been linked to impairments in social skills. It is not clear whether cocaine is responsible for this impairment or whether other factors, like polydrug use, distort the observed relation. We aimed to investigate this relation by means of a placebo-controlled experimental study. Additionally, associations between stressor-related activity (cortisol, cardiovascular parameters) induced by the biological stressor cocaine, and potential cocaine effects on emotion recognition were studied. Twenty-four healthy recreational cocaine users participated in this placebo-controlled within-subject study. Participants were tested between 1 and 2 h after treatment with oral cocaine (300 mg) or placebo. Emotion recognition of low and high intensity expressions of basic emotions (fear, anger, disgust, sadness, and happiness) was tested. Findings show that cocaine impaired recognition of negative emotions; this was mediated by the intensity of the presented emotions. When high intensity expressions of Anger and Disgust were shown, performance under influence of cocaine 'normalized' to placebo-like levels while it made identification of Sadness more difficult. The normalization of performance was most notable for participants with the largest cortisol responses in the cocaine condition compared to placebo. It was demonstrated that cocaine impairs recognition of negative emotions, depending on the intensity of emotion expression and cortisol response.

  20. Phosphate Recognition in Structural Biology

    NARCIS (Netherlands)

    Hirsch, Anna K.H.; Fischer, Felix R.; Diederich, François

    2007-01-01

    Drug-discovery research in the past decade has seen an increased selection of targets with phosphate recognition sites, such as protein kinases and phosphatases, in the past decade. This review attempts, with the help of database-mining tools, to give an overview of the most important principles in

  1. Age-invariant face recognition.

    Science.gov (United States)

    Park, Unsang; Tong, Yiying; Jain, Anil K

    2010-05-01

    One of the challenges in automatic face recognition is to achieve temporal invariance. In other words, the goal is to come up with a representation and matching scheme that is robust to changes due to facial aging. Facial aging is a complex process that affects both the 3D shape of the face and its texture (e.g., wrinkles). These shape and texture changes degrade the performance of automatic face recognition systems. However, facial aging has not received substantial attention compared to other facial variations due to pose, lighting, and expression. We propose a 3D aging modeling technique and show how it can be used to compensate for the age variations to improve the face recognition performance. The aging modeling technique adapts view-invariant 3D face models to the given 2D face aging database. The proposed approach is evaluated on three different databases (i.g., FG-NET, MORPH, and BROWNS) using FaceVACS, a state-of-the-art commercial face recognition engine.

  2. License plate recognition using DTCNNs

    NARCIS (Netherlands)

    ter Brugge, M.H; Stevens, J.H; Nijhuis, J.A G; Spaanenburg, L; Tavsanonoglu, V

    1998-01-01

    Automatic license plate recognition requires a series of complex image processing steps. For practical use, the amount of data to he processed must be minimized early on. This paper shows that the computationally most intensive steps can be realized by DTCNNs. Moreover; high-level operations like fi

  3. Intelligent Scene Analysis and Recognition

    Science.gov (United States)

    2010-03-30

    in IEEE Conference on Computer Vision and Pattern Recognition, 2005, pp. 688–695. [15] J. Vogel and B. Schiele , “A semantic typicality measure for...Computer Vision, vol. 60, pp. 63–86, 2004. [54] M. Stark, M. Goesele, and B. Schiele , “A shape-based object class model for knowledge trans- fer,” in In

  4. Data complexity in pattern recognition

    CERN Document Server

    Kam Ho Tin

    2006-01-01

    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

  5. Object recognition memory in zebrafish.

    Science.gov (United States)

    May, Zacnicte; Morrill, Adam; Holcombe, Adam; Johnston, Travis; Gallup, Joshua; Fouad, Karim; Schalomon, Melike; Hamilton, Trevor James

    2016-01-01

    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.

  6. Method and System for Object Recognition Search

    Science.gov (United States)

    Duong, Tuan A. (Inventor); Duong, Vu A. (Inventor); Stubberud, Allen R. (Inventor)

    2012-01-01

    A method for object recognition using shape and color features of the object to be recognized. An adaptive architecture is used to recognize and adapt the shape and color features for moving objects to enable object recognition.

  7. Voice Recognition in Face-Blind Patients.

    Science.gov (United States)

    Liu, Ran R; Pancaroglu, Raika; Hills, Charlotte S; Duchaine, Brad; Barton, Jason J S

    2016-04-01

    Right or bilateral anterior temporal damage can impair face recognition, but whether this is an associative variant of prosopagnosia or part of a multimodal disorder of person recognition is an unsettled question, with implications for cognitive and neuroanatomic models of person recognition. We assessed voice perception and short-term recognition of recently heard voices in 10 subjects with impaired face recognition acquired after cerebral lesions. All 4 subjects with apperceptive prosopagnosia due to lesions limited to fusiform cortex had intact voice discrimination and recognition. One subject with bilateral fusiform and anterior temporal lesions had a combined apperceptive prosopagnosia and apperceptive phonagnosia, the first such described case. Deficits indicating a multimodal syndrome of person recognition were found only in 2 subjects with bilateral anterior temporal lesions. All 3 subjects with right anterior temporal lesions had normal voice perception and recognition, 2 of whom performed normally on perceptual discrimination of faces. This confirms that such lesions can cause a modality-specific associative prosopagnosia.

  8. Pattern recognition, machine intelligence and biometrics

    CERN Document Server

    Wang, Patrick S P

    2012-01-01

    ""Pattern Recognition, Machine Intelligence and Biometrics"" covers the most recent developments in Pattern Recognition and its applications, using artificial intelligence technologies within an increasingly critical field. It covers topics such as: image analysis and fingerprint recognition; facial expressions and emotions; handwriting and signatures; iris recognition; hand-palm gestures; and multimodal based research. The applications span many fields, from engineering, scientific studies and experiments, to biomedical and diagnostic applications, to personal identification and homeland secu

  9. Data structures, computer graphics, and pattern recognition

    CERN Document Server

    Klinger, A; Kunii, T L

    1977-01-01

    Data Structures, Computer Graphics, and Pattern Recognition focuses on the computer graphics and pattern recognition applications of data structures methodology.This book presents design related principles and research aspects of the computer graphics, system design, data management, and pattern recognition tasks. The topics include the data structure design, concise structuring of geometric data for computer aided design, and data structures for pattern recognition algorithms. The survey of data structures for computer graphics systems, application of relational data structures in computer gr

  10. Hand Gesture Recognition: A Literature Review

    OpenAIRE

    Rafiqul Zaman Khan; Noor Adnan Ibraheem

    2012-01-01

    Hand gesture recognition system received great attention in the recent few years because of its manifoldness applications and the ability to interact with machine efficiently through human computer interaction. In this paper a survey of recent hand gesture recognition systems is presented. Key issues of hand gesture recognition system are presented with challenges of gesture system. Review methods of recent postures and gestures recognition system presented as well. Summary of res...

  11. Age Dependent Face Recognition using Eigenface

    OpenAIRE

    Hlaing Htake Khaung Tin

    2013-01-01

    Face recognition is the most successful form of human surveillance. Face recognition technology, is being used to improve human efficiency when recognition faces, is one of the fastest growing fields in the biometric industry. In the first stage, the age is classified into eleven categories which distinguish the person oldness in terms of age. In the second stage of the process is face recognition based on the predicted age. Age prediction has considerable potential applications in human comp...

  12. Computing negentropy based signatures for texture recognition

    Directory of Open Access Journals (Sweden)

    Daniela COLTUC

    2007-12-01

    Full Text Available The proposed method aims to provide a new tool for texture recognition. For this purpose, a set of texture samples are decomposed by using the FastICA algorithm and characterized by a negentropy based signature. In order to do recognition, the texture signatures are compared by means of Minkowski distance. The recognition rates, computed for a set of 320 texture samples, show a medium recognition accuracy and the method may be further improved.

  13. Employee recognition and performance: A field experiment

    OpenAIRE

    Bradler, C.; Dur, R.; Neckermann, S.; Non, J.A.

    2013-01-01

    This paper reports the results from a controlled field experiment designed to investigate the causal effect of public recognition on employee performance. We hired more than 300 employees to work on a three-hour data-entry task. In a random sample of work groups, workers unexpectedly received recognition after two hours of work. We find that recognition increases subsequent performance substantially, and particularly so when recognition is exclusively provided to the best performers. Remarkab...

  14. Natural Language Processing: Word Recognition without Segmentation.

    Science.gov (United States)

    Saeed, Khalid; Dardzinska, Agnieszka

    2001-01-01

    Discussion of automatic recognition of hand and machine-written cursive text using the Arabic alphabet focuses on an algorithm for word recognition. Describes results of testing words for recognition without segmentation and considers the algorithms' use for words of different fonts and for processing whole sentences. (Author/LRW)

  15. Recognition of an Independent Self-Consciousness

    DEFF Research Database (Denmark)

    Bjerre, Henrik Jøker

    2009-01-01

    Hegel's concept in the Phenomenology of the Spirit of the "recognition of an independent self-consciousness" is investigated as a point of separation for contemporary philosophy of recognition. I claim that multiculturalism and the theories of recognition (such as Axel Honneth's) based on empiric...

  16. Micro-Recognition - Erving Goffman as Recognition Thinker

    DEFF Research Database (Denmark)

    Jacobsen, Michael Hviid; Kristiansen, Søren

    2009-01-01

      The purpose of this article is to present, develop and exemplify the argument that Erving Goffman can be regarded as an important yet somewhat overlooked contributor to recognition theory in contemporary sociology. Despite often being neglected in this respect, this article provides an interpre......  The purpose of this article is to present, develop and exemplify the argument that Erving Goffman can be regarded as an important yet somewhat overlooked contributor to recognition theory in contemporary sociology. Despite often being neglected in this respect, this article provides...... an interpretation of Goffman as a major recognition theorist on the micro-level of social analysis by way of his ritual metaphor. Erving Goffman's sociology is conventionally approached and appreciated primarily through his famous dramaturgical metaphor that describes and comprehends social life through...... the analytical lens of the theatre where people are seen as manipulative actors concerned with their own self-presentations and impression managements. Throughout especially the earlier parts of his work, Goffman however also advanced a much more Durkheimian inspired view of social life that rests on the idea...

  17. Hierarchical Recognition Scheme for Human Facial Expression Recognition Systems

    Directory of Open Access Journals (Sweden)

    Muhammad Hameed Siddiqi

    2013-12-01

    Full Text Available Over the last decade, human facial expressions recognition (FER has emerged as an important research area. Several factors make FER a challenging research problem. These include varying light conditions in training and test images; need for automatic and accurate face detection before feature extraction; and high similarity among different expressions that makes it difficult to distinguish these expressions with a high accuracy. This work implements a hierarchical linear discriminant analysis-based facial expressions recognition (HL-FER system to tackle these problems. Unlike the previous systems, the HL-FER uses a pre-processing step to eliminate light effects, incorporates a new automatic face detection scheme, employs methods to extract both global and local features, and utilizes a HL-FER to overcome the problem of high similarity among different expressions. Unlike most of the previous works that were evaluated using a single dataset, the performance of the HL-FER is assessed using three publicly available datasets under three different experimental settings: n-fold cross validation based on subjects for each dataset separately; n-fold cross validation rule based on datasets; and, finally, a last set of experiments to assess the effectiveness of each module of the HL-FER separately. Weighted average recognition accuracy of 98.7% across three different datasets, using three classifiers, indicates the success of employing the HL-FER for human FER.

  18. Embedded Face Detection and Recognition

    Directory of Open Access Journals (Sweden)

    Göksel Günlü

    2012-10-01

    Full Text Available The need to increase security in open or public spaces has in turn given rise to the requirement to monitor these spaces and analyse those images on‐site and on‐time. At this point, the use of smart cameras ‐ of which the popularity has been increasing ‐ is one step ahead. With sensors and Digital Signal Processors (DSPs, smart cameras generate ad hoc results by analysing the numeric images transmitted from the sensor by means of a variety of image‐processing algorithms. Since the images are not transmitted to a distance processing unit but rather are processed inside the camera, it does not necessitate high‐ bandwidth networks or high processor powered systems; it can instantaneously decide on the required access. Nonetheless, on account of restricted memory, processing power and overall power, image processing algorithms need to be developed and optimized for embedded processors. Among these algorithms, one of the most important is for face detection and recognition. A number of face detection and recognition methods have been proposed recently and many of these methods have been tested on general‐purpose processors. In smart cameras ‐ which are real‐life applications of such methods ‐ the widest use is on DSPs. In the present study, the Viola‐Jones face detection method ‐ which was reported to run faster on PCs ‐ was optimized for DSPs; the face recognition method was combined with the developed sub‐region and mask‐based DCT (Discrete Cosine Transform. As the employed DSP is a fixed‐point processor, the processes were performed with integers insofar as it was possible. To enable face recognition, the image was divided into sub‐ regions and from each sub‐region the robust coefficients against disruptive elements ‐ like face expression, illumination, etc. ‐ were selected as the features. The discrimination of the selected features was enhanced via LDA (Linear Discriminant Analysis and then employed for

  19. Research on Radar Emitter Attribute Recognition Method

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    In order to solve emitter recognition problems in a practical reconnaissance environment, attribute mathematics is introduced. The basic concepts and theory of attribute set and attribute measure are described in detail. A new attribute recognition method based on attribute measure is presented in this paper. Application example is given, which demonstrates this new method is accurate and effective. Moreover, computer simulation for recognizing the emitter purpose is selected, and compared with classical statistical pattern recognition through simulation. The excellent experimental results demonstrate that this is a brand-new attribute recognition method as compared to existing statistical pattern recognition techniques.

  20. Famous face recognition, face matching, and extraversion.

    Science.gov (United States)

    Lander, Karen; Poyarekar, Siddhi

    2015-01-01

    It has been previously established that extraverts who are skilled at interpersonal interaction perform significantly better than introverts on a face-specific recognition memory task. In our experiment we further investigate the relationship between extraversion and face recognition, focusing on famous face recognition and face matching. Results indicate that more extraverted individuals perform significantly better on an upright famous face recognition task and show significantly larger face inversion effects. However, our results did not find an effect of extraversion on face matching or inverted famous face recognition.

  1. Non Audio-Video gesture recognition system

    DEFF Research Database (Denmark)

    Craciunescu, Razvan; Mihovska, Albena Dimitrova; Kyriazakos, Sofoklis

    2016-01-01

    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...

  2. Offline Handwritten Devanagari Script Recognition

    Directory of Open Access Journals (Sweden)

    Ved Prakash Agnihotri

    2012-07-01

    Full Text Available Handwritten Devanagari script recognition system using neural network is presented in this paper. Diagonal based feature extraction is used for extracting features of the handwritten Devanagari script. After that these feature of each character image is converted into chromosome bit string of length 378. More than 1000 sample is used for training and testing purpose in this proposed work. It is attempted to use the power of genetic algorithm to recognize the character. In step-I preprocessing on the character image, then image suitable for feature extraction as here is used. Diagonal based feature extraction method to extract 54 features to each character. In the next step character recognize image in which extracted feature in converted into Chromosome bit string of size 378. In recognition step using fitness function in which find the Chromosome difference between unknown character and Chromosome which are store in data base.

  3. Molecular Recognition and Ligand Association

    Science.gov (United States)

    Baron, Riccardo; McCammon, J. Andrew

    2013-04-01

    We review recent developments in our understanding of molecular recognition and ligand association, focusing on two major viewpoints: (a) studies that highlight new physical insight into the molecular recognition process and the driving forces determining thermodynamic signatures of binding and (b) recent methodological advances in applications to protein-ligand binding. In particular, we highlight the challenges posed by compensating enthalpic and entropic terms, competing solute and solvent contributions, and the relevance of complex configurational ensembles comprising multiple protein, ligand, and solvent intermediate states. As more complete physics is taken into account, computational approaches increase their ability to complement experimental measurements, by providing a microscopic, dynamic view of ensemble-averaged experimental observables. Physics-based approaches are increasingly expanding their power in pharmacology applications.

  4. Face Recognition using Curvelet Transform

    CERN Document Server

    Cohen, Rami

    2011-01-01

    Face recognition has been studied extensively for more than 20 years now. Since the beginning of 90s the subject has became a major issue. This technology is used in many important real-world applications, such as video surveillance, smart cards, database security, internet and intranet access. This report reviews recent two algorithms for face recognition which take advantage of a relatively new multiscale geometric analysis tool - Curvelet transform, for facial processing and feature extraction. This transform proves to be efficient especially due to its good ability to detect curves and lines, which characterize the human's face. An algorithm which is based on the two algorithms mentioned above is proposed, and its performance is evaluated on three data bases of faces: AT&T (ORL), Essex Grimace and Georgia-Tech. k-nearest neighbour (k-NN) and Support vector machine (SVM) classifiers are used, along with Principal Component Analysis (PCA) for dimensionality reduction. This algorithm shows good results, ...

  5. Emotion Recognition using Speech Features

    CERN Document Server

    Rao, K Sreenivasa

    2013-01-01

    “Emotion Recognition Using Speech Features” covers emotion-specific features present in speech and discussion of suitable models for capturing emotion-specific information for distinguishing different emotions.  The content of this book is important for designing and developing  natural and sophisticated speech systems. Drs. Rao and Koolagudi lead a discussion of how emotion-specific information is embedded in speech and how to acquire emotion-specific knowledge using appropriate statistical models. Additionally, the authors provide information about using evidence derived from various features and models. The acquired emotion-specific knowledge is useful for synthesizing emotions. Discussion includes global and local prosodic features at syllable, word and phrase levels, helpful for capturing emotion-discriminative information; use of complementary evidences obtained from excitation sources, vocal tract systems and prosodic features in order to enhance the emotion recognition performance;  and pro...

  6. FINGER-VEIN RECOGNITION SYSTEMS

    Directory of Open Access Journals (Sweden)

    A.Haritha Deepthi

    2015-10-01

    Full Text Available As the Person‟s/Organization‟s Private information‟s are becoming very easy to access, the demand for a Simple, Convenient, Efficient, and a highly Securable Authentication System has been increased. In considering these requirements for data Protection, Biometrics, which uses human physiological or behavioral system for personal Identification has been found as a solution for these difficulties. However most of the biometric systems have high complexity in both time and space. So we are going to use a Real time Finger-Vein recognition System for authentication purposes. In this paper we had implemented the Finger Vein Recognition concept using MATLAB R2013a. The features used are Lacunarity Distance, Blanket Dimension distance. This has more accuracy when compared to conventional methods.

  7. Face Recognition in Various Illuminations

    Directory of Open Access Journals (Sweden)

    Saurabh D. Parmar,

    2014-05-01

    Full Text Available Face Recognition (FR under various illuminations is very challenging. Normalization technique is useful for removing the dimness and shadow from the facial image which reduces the effect of illumination variations still retaining the necessary information of the face. The robust local feature extractor which is the gray-scale invariant texture called Local Binary Pattern (LBP is helpful for feature extraction. K-Nearest Neighbor classifier is utilized for the purpose of classification and to match the face images from the database. Experimental results were based on Yale-B database with three different sub categories. The proposed method has been tested to robust face recognition in various illumination conditions. Extensive experiment shows that the proposed system can achieve very encouraging performance in various illumination environments.

  8. Covert Face Recognition without Prosopagnosia

    Directory of Open Access Journals (Sweden)

    H. D. Ellis

    1993-01-01

    Full Text Available An experiment is reported where subjects were presented with familiar or unfamiliar faces for supraliminal durations or for durations individually assessed as being below the threshold for recognition. Their electrodermal responses to each stimulus were measured and the results showed higher peak amplitude skin conductance responses for familiar than for unfamiliar faces, regardless of whether they had been displayed supraliminally or subliminally. A parallel is drawn between elevated skin conductance responses to subliminal stimuli and findings of covert recognition of familiar faces in prosopagnosic patients, some of whom show increased electrodermal activity (EDA to previously familiar faces. The supraliminal presentation data also served to replicate similar work by Tranel et al (1985. The results are considered alongside other data indicating the relation between non-conscious, “automatic” aspects of normal visual information processing and abilities which can be found to be preserved without awareness after brain injury.

  9. Gesture Recognition Based Mouse Events

    Directory of Open Access Journals (Sweden)

    Rachit Puri

    2013-12-01

    Full Text Available This paper presents the maneuver of mouse pointer a nd performs various mouse operations such as left click, right click, double click, drag etc using ge stures recognition technique. Recognizing gestures is a complex task which involves many aspects such as mo tion modeling, motion analysis, pattern recognition and machine learning. Keeping all the essential factors in mind a system has been created which recognizes the movement of fingers and various patterns formed by them. Color caps have been used for fingers to distinguish it f rom the background color such as skin color. Thus recog nizing the gestures various mouse events have been performed. The application has been created on MATL AB environment with operating system as windows 7.

  10. Physics of Automatic Target Recognition

    CERN Document Server

    Sadjadi, Firooz

    2007-01-01

    Physics of Automatic Target Recognition addresses the fundamental physical bases of sensing, and information extraction in the state-of-the art automatic target recognition field. It explores both passive and active multispectral sensing, polarimetric diversity, complex signature exploitation, sensor and processing adaptation, transformation of electromagnetic and acoustic waves in their interactions with targets, background clutter, transmission media, and sensing elements. The general inverse scattering, and advanced signal processing techniques and scientific evaluation methodologies being used in this multi disciplinary field will be part of this exposition. The issues of modeling of target signatures in various spectral modalities, LADAR, IR, SAR, high resolution radar, acoustic, seismic, visible, hyperspectral, in diverse geometric aspects will be addressed. The methods for signal processing and classification will cover concepts such as sensor adaptive and artificial neural networks, time reversal filt...

  11. Face recognition using Krawtchouk moment

    Indian Academy of Sciences (India)

    J Sheeba Rani; D Devaraj

    2012-08-01

    Feature extraction is one of the important tasks in face recognition. Moments are widely used feature extractor due to their superior discriminatory power and geometrical invariance. Moments generally capture the global features of the image. This paper proposes Krawtchouk moment for feature extraction in face recognition system, which has the ability to extract local features from any region of interest. Krawtchouk moment is used to extract both local features and global features of the face. The extracted features are fused using summed normalized distance strategy. Nearest neighbour classifier is employed to classify the faces. The proposed method is tested using ORL and Yale databases. Experimental results show that the proposed method is able to recognize images correctly, even if the images are corrupted with noise and possess change in facial expression and tilt.

  12. Speech Recognition in 7 Languages

    Science.gov (United States)

    2000-08-01

    best monolingual cross-lingual [10] F. Weng, H. Bratt, L. Neumeyer, and A. Stol- recognizers could not always be tested. cke. A Study of Multilingual ...are r the same tm the proaches, namely portation, cross-lingual and simul- two languages are recognized at the same time, the taneous multilingual ...in cross-lingual will present experiments and results for different ap- recognition for different baseline systems and found proaches of multilingual

  13. Named Entity Recognition for IDEAL

    OpenAIRE

    Du, Qianzhou; Zhang, Xuan

    2015-01-01

    This project explored how to apply Named Entity Recognition to large Twitter and web page datasets to extract useful entities such as people, organization, location, and date. In addition, this NER utility has been scaled to the MapReduce framework on the Hadoop cluster. A schema and software allow this to be integrated with IDEAL. The term “Named Entity”, which was first introduced by Grishman and Sundheim, is widely used in Natural Language Processing (NLP). The researchers were focusing...

  14. Activity Recognition in Social Media

    Science.gov (United States)

    2015-12-29

    activity is splitting. 6 Crowd video classification Ability to identify crowd behavior enables crowd management systems to design and manage public...characterize group activities . We then showed the effectiveness of group level features in crowd video classification . 9 List of Publications 1. N. Bhargava, S...AFRL-AFOSR-JP-TR-2016-0044 Activity Recognition in Social Media Subhasis Chaudhuri INDIAN INSTITUTE OF TECHNOLOGY BOMBAY Final Report 05/09/2016

  15. Offline arabic character recognition system

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    Several languages use the Arabic alphabets and arabic scripts present challenges because the letter shape is context sensitive. For the past three decades, there has been a mounting interest among researchers in this problem. In this paper we present an Arabic Character Recognition system and quence steps of recognizing Arabic text. These steps are separately discussed, and previous research work on each step is reviewed. Also in this paper we give some samples of Arabic fonts.

  16. Feature Recognition for Virtual Machining

    OpenAIRE

    Xú, Shixin; Anwer, Nabil; Qiao, Lihong

    2014-01-01

    International audience; Virtual machining uses software tools to simulate machining processes in virtual environments ahead of actual production. This paper proposes that feature recognition techniques can be applied in the course of virtual machining, such as identifying some process problems, and presenting corresponding correcting advices. By comparing with the original CAD model, form errors of the machining features can be found. And then corrections are suggested to process designers. T...

  17. Object Recognition Using Range Images.

    Science.gov (United States)

    1985-12-01

    with a multiplexed filter which contains a number of rotated and scaled filters (Leib and others, 1978:2892-2899) and (Mendelsohn and Wohlers , 1980...Butler, Steve. "Three Dimensional Pattern Recognition." Unpublished report . Electro-Optical Terminal Guidance Branch, Eglin AFB FL, 1985. Casasent, David...Correlation:Final Report , June 1982-January 1984. Electro-Optical Terminal Guidance Branch, Eglin AFB FL, August 1985. 136 rv Fujil, H. and Y. Ohtsuba

  18. Attentional Selection in Object Recognition

    Science.gov (United States)

    1993-02-01

    understanding of a scene is important for robots to deal effectively with their environment. This may involve determining which objects are present in a...image color texture edge parallel parallel age&’ segatentatio line agorithas detector detector line rasp eser"Of color texture edge repow parallel...generic so that it could possibly be used for other tasks that do not necessarily involve recognition. Thus using this se- lection mechanism, a robot

  19. WHEEL CHAIR USING VOICE RECOGNITION

    OpenAIRE

    Manish Kumar Yadav*; Rajat Kumar; Santosh Yadav; Ravindra Prajapati; Prof. Kshirsagar

    2016-01-01

    The wide spread prevalence of lost limbs and sensing system is of major concern in present day due to wars, accident, age and health problems. This Omni-directional wheelchair was designed for the less able elderly to move more flexibly in narrow spaces, such as elevators or small aisle. The wheelchair is developed to help disabled patients by using speech recognition system to control the movement of wheelchair in different directions by using voice commands and also the simple movement of t...

  20. Pattern Recognition Using Associative Memories

    OpenAIRE

    Burles, Nathan John

    2014-01-01

    The human brain is extremely effective at performing pattern recognition, even in the presence of noisy or distorted inputs. Artificial neural networks attempt to imitate the structure of the brain, often with a view to mimicking its success. The binary correlation matrix memory (CMM) is a particular type of neural network that is capable of learning and recalling associations extremely quickly, as well as displaying a high storage capacity and having the ability to generalise from patterns a...

  1. Visual recognition of permuted words

    Science.gov (United States)

    Rashid, Sheikh Faisal; Shafait, Faisal; Breuel, Thomas M.

    2010-02-01

    In current study we examine how letter permutation affects in visual recognition of words for two orthographically dissimilar languages, Urdu and German. We present the hypothesis that recognition or reading of permuted and non-permuted words are two distinct mental level processes, and that people use different strategies in handling permuted words as compared to normal words. A comparison between reading behavior of people in these languages is also presented. We present our study in context of dual route theories of reading and it is observed that the dual-route theory is consistent with explanation of our hypothesis of distinction in underlying cognitive behavior for reading permuted and non-permuted words. We conducted three experiments in lexical decision tasks to analyze how reading is degraded or affected by letter permutation. We performed analysis of variance (ANOVA), distribution free rank test, and t-test to determine the significance differences in response time latencies for two classes of data. Results showed that the recognition accuracy for permuted words is decreased 31% in case of Urdu and 11% in case of German language. We also found a considerable difference in reading behavior for cursive and alphabetic languages and it is observed that reading of Urdu is comparatively slower than reading of German due to characteristics of cursive script.

  2. Multithread Face Recognition in Cloud

    Directory of Open Access Journals (Sweden)

    Dakshina Ranjan Kisku

    2016-01-01

    Full Text Available Faces are highly challenging and dynamic objects that are employed as biometrics evidence in identity verification. Recently, biometrics systems have proven to be an essential security tools, in which bulk matching of enrolled people and watch lists is performed every day. To facilitate this process, organizations with large computing facilities need to maintain these facilities. To minimize the burden of maintaining these costly facilities for enrollment and recognition, multinational companies can transfer this responsibility to third-party vendors who can maintain cloud computing infrastructures for recognition. In this paper, we showcase cloud computing-enabled face recognition, which utilizes PCA-characterized face instances and reduces the number of invariant SIFT points that are extracted from each face. To achieve high interclass and low intraclass variances, a set of six PCA-characterized face instances is computed on columns of each face image by varying the number of principal components. Extracted SIFT keypoints are fused using sum and max fusion rules. A novel cohort selection technique is applied to increase the total performance. The proposed protomodel is tested on BioID and FEI face databases, and the efficacy of the system is proven based on the obtained results. We also compare the proposed method with other well-known methods.

  3. Gesture Recognition Technology: A Review

    Directory of Open Access Journals (Sweden)

    PALLAVI HALARNKAR

    2012-11-01

    Full Text Available Gesture Recognition Technology has evolved greatly over the years. The past has seen the contemporary Human – Computer Interface techniques and their drawbacks, which limit the speed and naturalness of the human brain and body. As a result gesture recognition technology has developed since the early 1900s with a view to achieving ease and lessening the dependence on devices like keyboards, mice and touchscreens. Attempts have been made to combine natural gestures to operate with the technology around us to enable us to make optimum use of our body gestures making our work faster and more human friendly. The present has seen huge development in this field ranging from devices like virtual keyboards, video game controllers to advanced security systems which work on face, hand and body recognition techniques. The goal is to make full use of themovements of the body and every angle made by the parts of the body in order to supplement technology to become human friendly and understand natural human behavior and gestures. The future of this technology is very bright with prototypes of amazing devices in research and development to make the world equipped with digital information at hand whenever and wherever required.

  4. Fingerprint recognition using image processing

    Science.gov (United States)

    Dholay, Surekha; Mishra, Akassh A.

    2011-06-01

    Finger Print Recognition is concerned with the difficult task of matching the images of finger print of a person with the finger print present in the database efficiently. Finger print Recognition is used in forensic science which helps in finding the criminals and also used in authentication of a particular person. Since, Finger print is the only thing which is unique among the people and changes from person to person. The present paper describes finger print recognition methods using various edge detection techniques and also how to detect correct finger print using a camera images. The present paper describes the method that does not require a special device but a simple camera can be used for its processes. Hence, the describe technique can also be using in a simple camera mobile phone. The various factors affecting the process will be poor illumination, noise disturbance, viewpoint-dependence, Climate factors, and Imaging conditions. The described factor has to be considered so we have to perform various image enhancement techniques so as to increase the quality and remove noise disturbance of image. The present paper describe the technique of using contour tracking on the finger print image then using edge detection on the contour and after that matching the edges inside the contour.

  5. Infant visual attention and object recognition.

    Science.gov (United States)

    Reynolds, Greg D

    2015-05-15

    This paper explores the role visual attention plays in the recognition of objects in infancy. Research and theory on the development of infant attention and recognition memory are reviewed in three major sections. The first section reviews some of the major findings and theory emerging from a rich tradition of behavioral research utilizing preferential looking tasks to examine visual attention and recognition memory in infancy. The second section examines research utilizing neural measures of attention and object recognition in infancy as well as research on brain-behavior relations in the early development of attention and recognition memory. The third section addresses potential areas of the brain involved in infant object recognition and visual attention. An integrated synthesis of some of the existing models of the development of visual attention is presented which may account for the observed changes in behavioral and neural measures of visual attention and object recognition that occur across infancy.

  6. Acquired prosopagnosia without word recognition deficits.

    Science.gov (United States)

    Susilo, Tirta; Wright, Victoria; Tree, Jeremy J; Duchaine, Bradley

    2015-01-01

    It has long been suggested that face recognition relies on specialized mechanisms that are not involved in visual recognition of other object categories, including those that require expert, fine-grained discrimination at the exemplar level such as written words. But according to the recently proposed many-to-many theory of object recognition (MTMT), visual recognition of faces and words are carried out by common mechanisms [Behrmann, M., & Plaut, D. C. ( 2013 ). Distributed circuits, not circumscribed centers, mediate visual recognition. Trends in Cognitive Sciences, 17, 210-219]. MTMT acknowledges that face and word recognition are lateralized, but posits that the mechanisms that predominantly carry out face recognition still contribute to word recognition and vice versa. MTMT makes a key prediction, namely that acquired prosopagnosics should exhibit some measure of word recognition deficits. We tested this prediction by assessing written word recognition in five acquired prosopagnosic patients. Four patients had lesions limited to the right hemisphere while one had bilateral lesions with more pronounced lesions in the right hemisphere. The patients completed a total of seven word recognition tasks: two lexical decision tasks and five reading aloud tasks totalling more than 1200 trials. The performances of the four older patients (3 female, age range 50-64 years) were compared to those of 12 older controls (8 female, age range 56-66 years), while the performances of the younger prosopagnosic (male, 31 years) were compared to those of 14 younger controls (9 female, age range 20-33 years). We analysed all results at the single-patient level using Crawford's t-test. Across seven tasks, four prosopagnosics performed as quickly and accurately as controls. Our results demonstrate that acquired prosopagnosia can exist without word recognition deficits. These findings are inconsistent with a key prediction of MTMT. They instead support the hypothesis that face

  7. The mate recognition protein gene mediates reproductive isolation and speciation in the Brachionus plicatilis cryptic species complex

    Directory of Open Access Journals (Sweden)

    Gribble Kristin E

    2012-08-01

    Full Text Available Abstract Background Chemically mediated prezygotic barriers to reproduction likely play an important role in speciation. In facultatively sexual monogonont rotifers from the Brachionus plicatilis cryptic species complex, mate recognition of females by males is mediated by the Mate Recognition Protein (MRP, a globular glycoprotein on the surface of females, encoded by the mmr-b gene family. In this study, we sequenced mmr-b copies from 27 isolates representing 11 phylotypes of the B. plicatilis species complex, examined the mode of evolution and selection of mmr-b, and determined the relationship between mmr-b genetic distance and mate recognition among isolates. Results Isolates of the B. plicatilis species complex have 1–4 copies of mmr-b, each composed of 2–9 nearly identical tandem repeats. The repeats within a gene copy are generally more similar than are gene copies among phylotypes, suggesting concerted evolution. Compared to housekeeping genes from the same isolates, mmr-b has accumulated only half as many synonymous differences but twice as many non-synonymous differences. Most of the amino acid differences between repeats appear to occur on the outer face of the protein, and these often result in changes in predicted patterns of phosphorylation. However, we found no evidence of positive selection driving these differences. Isolates with the most divergent copies were unable to mate with other isolates and rarely self-crossed. Overall the degree of mate recognition was significantly correlated with the genetic distance of mmr-b. Conclusions Discrimination of compatible mates in the B. plicatilis species complex is determined by proteins encoded by closely related copies of a single gene, mmr-b. While concerted evolution of the tandem repeats in mmr-b may function to maintain identity, it can also lead to the rapid spread of a mutation through all copies in the genome and thus to reproductive isolation. The mmr-b gene is evolving

  8. Face Recognition in Uncontrolled Environment

    Directory of Open Access Journals (Sweden)

    Radhey Shyam

    2016-08-01

    Full Text Available This paper presents a novel method of facial image representation for face recognition in uncontrolled environment. It is named as augmented local binary patterns (A-LBP that works on both, uniform and non-uniform patterns. It replaces the central non-uniform pattern with a majority value of the neighbouring uniform patterns obtained after processing all neighbouring non-uniform patterns. These patterns are finally combined with the neighbouring uniform patterns, in order to extract discriminatory information from the local descriptors. The experimental results indicate the vitality of the proposed method on particular face datasets, where the images are prone to extreme variations of illumination.

  9. Face Processing: Models For Recognition

    Science.gov (United States)

    Turk, Matthew A.; Pentland, Alexander P.

    1990-03-01

    The human ability to process faces is remarkable. We can identify perhaps thousands of faces learned throughout our lifetime and read facial expression to understand such subtle qualities as emotion. These skills are quite robust, despite sometimes large changes in the visual stimulus due to expression, aging, and distractions such as glasses or changes in hairstyle or facial hair. Computers which model and recognize faces will be useful in a variety of applications, including criminal identification, human-computer interface, and animation. We discuss models for representing faces and their applicability to the task of recognition, and present techniques for identifying faces and detecting eye blinks.

  10. COMMERCIAL FUND, RECOGNITION AND ASSESSMENT

    Directory of Open Access Journals (Sweden)

    VIOREL TRIF

    2010-01-01

    Full Text Available The importance of the immaterial investments within companies nowadays urges the specialists in accounting to find the ways to present more in the elements. In their studies researchers face the controversy reinvestments, as an asset in the balance sheet or an expense in the profit or loss account. The main goal of this paper is to analyze the difficulties in commercial fund. In the first part we will analyze various definitions of the problems concerning the commercial fund’s recognition and assessment. The paper also suggests that investments are really social and economic problems.

  11. Introduction to radar target recognition

    CERN Document Server

    Tait, P

    2006-01-01

    This new text provides an overview of the radar target recognition process and covers the key techniques being developed for operational systems. It is based on the fundamental scientific principles of high resolution radar, and explains how the techniques can be used in real systems, taking into account the characteristics of practical radar system designs and component limitations. It also addresses operational aspects, such as how high resolution modes would fit in with other functions such as detection and tracking. Mathematics is kept to a minimum and the complex techniques and issues are

  12. On speech recognition during anaesthesia

    DEFF Research Database (Denmark)

    Alapetite, Alexandre

    2007-01-01

    This PhD thesis in human-computer interfaces (informatics) studies the case of the anaesthesia record used during medical operations and the possibility to supplement it with speech recognition facilities. Problems and limitations have been identified with the traditional paper-based anaesthesia...... record, but also with newer electronic versions typically based on touch-screen and keyboard, in particular ergonomic issues and the fact that anaesthesiologists tend to postpone the registration of the medications and other events during busy periods of anaesthesia, which in turn may lead to gaps...

  13. Online recognition of the multiphase flow regime

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    The key reasons that the present method cannot be used to solve the industrial multi- phase flow pattern recognition are clarified firstly. The prerequisite to realize the online recognition is proposed and recognition rules for partial flow pattern are obtained based on the massive experimental data. The standard templates for every flow regime feature are calculated with self-organization cluster algorithm. The multi-sensor data fusion method is proposed to realize the online recognition of multiphase flow regime with the pressure and differential pressure signals, which overcomes the severe influence of fluid flow velocity and the oil fraction on the recognition. The online recognition method is tested in the practice, which has less than 10 percent measurement error. The method takes advantages of high confidence, good fault tolerance and less requirement of single sensor performance.

  14. Parameters Optimization of Synergetic Recognition Approach

    Institute of Scientific and Technical Information of China (English)

    GAOJun; DONGHuoming; SHAOJing; ZHAOJing

    2005-01-01

    Synergetic pattern recognition is a novel and effective pattern recognition method, and has some advantages in image recognition. Researches have shown that attention parameters λ and parameters B, C directly influence on the recognition results, but there is no general research theory to control these parameters in the recognition process. We abstractly analyze these parameters in this paper, and purpose a novel parameters optimization method based on simulated annealing algorithm. SA algorithm has good optimization performance and is used to search the global optimized solution of these parameters. Theoretic analysis and experimental results both show that the proposed parameters optimization method is effective, which can fully improve the performance of synergetic recognition approach, and the algorithm realization is simple and fast.

  15. Online recognition of the multiphase flow regime

    Institute of Scientific and Technical Information of China (English)

    BAI BoFeng; ZHANG ShaoJun; ZHAO Liang; ZHANG XiMin; GUO LieJin

    2008-01-01

    The key reasons that the present method cannot be used to solve the industrial multi-phase flow pattern recognition are clarified firstly. The prerequisite to realize the online recognition is proposed and recognition rules for partial flow pattern are obtained based on the massive experimental data. The standard templates for every flow regime feature are calculated with self-organization cluster algorithm. The multi-sensor data fusion method is proposed to realize the online recognition of multiphase flow regime with the pressure and differential pressure signals, which overcomes the severe influence of fluid flow velocity and the oil fraction on the recognition. The online recognition method is tested in the practice, which has less than 10 percent measurement error. The method takes advantages of high confidence, good fault tolerance and less requirement of single sensor performance.

  16. Speech recognition with amplitude and frequency modulations

    Science.gov (United States)

    Zeng, Fan-Gang; Nie, Kaibao; Stickney, Ginger S.; Kong, Ying-Yee; Vongphoe, Michael; Bhargave, Ashish; Wei, Chaogang; Cao, Keli

    2005-02-01

    Amplitude modulation (AM) and frequency modulation (FM) are commonly used in communication, but their relative contributions to speech recognition have not been fully explored. To bridge this gap, we derived slowly varying AM and FM from speech sounds and conducted listening tests using stimuli with different modulations in normal-hearing and cochlear-implant subjects. We found that although AM from a limited number of spectral bands may be sufficient for speech recognition in quiet, FM significantly enhances speech recognition in noise, as well as speaker and tone recognition. Additional speech reception threshold measures revealed that FM is particularly critical for speech recognition with a competing voice and is independent of spectral resolution and similarity. These results suggest that AM and FM provide independent yet complementary contributions to support robust speech recognition under realistic listening situations. Encoding FM may improve auditory scene analysis, cochlear-implant, and audiocoding performance. auditory analysis | cochlear implant | neural code | phase | scene analysis

  17. Machine learning techniques in dialogue act recognition

    Directory of Open Access Journals (Sweden)

    Mark Fišel

    2007-05-01

    Full Text Available This report addresses dialogue acts, their existing applications and techniques of automatically recognizing them, in Estonia as well as elsewhere. Three main applications are described: in dialogue systems to determine the intention of the speaker, in dialogue systems with machine translation to resolve ambiguities in the possible translation variants and in speech recognition to reduce word recognition error rate. Several recognition techniques are described on the surface level: how they work and how they are trained. A summary of the corresponding representation methods is provided for each technique. The paper also includes examples of applying the techniques to dialogue act recognition.The author comes to the conclusion that using the current evaluation metric it is impossible to compare dialogue act recognition techniques when these are applied to different dialogue act tag sets. Dialogue acts remain an open research area, with space and need for developing new recognition techniques and methods of evaluation.

  18. Document recognition serving people with disabilities

    Science.gov (United States)

    Fruchterman, James R.

    2007-01-01

    Document recognition advances have improved the lives of people with print disabilities, by providing accessible documents. This invited paper provides perspectives on the author's career progression from document recognition professional to social entrepreneur applying this technology to help people with disabilities. Starting with initial thoughts about optical character recognition in college, it continues with the creation of accurate omnifont character recognition that did not require training. It was difficult to make a reading machine for the blind in a commercial setting, which led to the creation of a nonprofit social enterprise to deliver these devices around the world. This network of people with disabilities scanning books drove the creation of Bookshare.org, an online library of scanned books. Looking forward, the needs for improved document recognition technology to further lower the barriers to reading are discussed. Document recognition professionals should be proud of the positive impact their work has had on some of society's most disadvantaged communities.

  19. Studies of human vision recognition: some improvements

    Science.gov (United States)

    Wu, Bo-Wen; Fang, Yi-Chin; Chang, Lin-Song

    2010-01-01

    This paper proposes a new method to improve human recognition by artificial intelligence, specifically of images without the interference of high frequencies. The human eye is the most delicate optical system. Notwithstanding the dramatic progression of its structure and functions through a long evolution, the capability of visual recognition is not yet close to perfection. This paper is a study, based on the limitations of recognition by the human eye, of image recognition through the application of artificial intelligence. Those aspects which have been explored focus on human eye modeling, including aberration analysis, creative models of the human eye, human vision recognition characteristics and various mathematical models for verification. By using images consisting of four black and white bands and modulation transfer function (MTF) curve evaluation recognition capability on all the studied models, the optimum model most compatible with the physiology of the human eye is found.

  20. Handwritten digits recognition based on immune network

    Science.gov (United States)

    Li, Yangyang; Wu, Yunhui; Jiao, Lc; Wu, Jianshe

    2011-11-01

    With the development of society, handwritten digits recognition technique has been widely applied to production and daily life. It is a very difficult task to solve these problems in the field of pattern recognition. In this paper, a new method is presented for handwritten digit recognition. The digit samples firstly are processed and features extraction. Based on these features, a novel immune network classification algorithm is designed and implemented to the handwritten digits recognition. The proposed algorithm is developed by Jerne's immune network model for feature selection and KNN method for classification. Its characteristic is the novel network with parallel commutating and learning. The performance of the proposed method is experimented to the handwritten number datasets MNIST and compared with some other recognition algorithms-KNN, ANN and SVM algorithm. The result shows that the novel classification algorithm based on immune network gives promising performance and stable behavior for handwritten digits recognition.

  1. Increasing the discrimination of SAR recognition models

    Science.gov (United States)

    Bhanu, Bir; Jones, Grinnell, III

    2001-08-01

    The focus of this paper is optimizing recognition models for Synthetic Aperture Radar signatures of vehicles to improve the performance of a recognition algorithm under the extended operating conditions of target articulation, occlusion and configuration variants. The recognition models are based on quasi-invariant local features, scattering center locations and magnitudes. The approach determines the similarities and differences among the various vehicle models. Methods to penalize similar features or reward dissimilar features are used to increase the distinguishability of the recognition model instances. Extensive experimental recognition results are presented in terms of confusion matrices and receiver operating characteristic curves to show the improvements in recognition performance for MSTAR vehicle targets with articulation, configuration variants and occlusion.

  2. Face Recognition in Real-world Images

    OpenAIRE

    Fontaine, Xavier; Achanta, Radhakrishna; Süsstrunk, Sabine

    2017-01-01

    Face recognition systems are designed to handle well-aligned images captured under controlled situations. However real-world images present varying orientations, expressions, and illumination conditions. Traditional face recognition algorithms perform poorly on such images. In this paper we present a method for face recognition adapted to real-world conditions that can be trained using very few training examples and is computationally efficient. Our method consists of performing a novel align...

  3. Automated leukocyte recognition using fuzzy divergence.

    Science.gov (United States)

    Ghosh, Madhumala; Das, Devkumar; Chakraborty, Chandan; Ray, Ajoy K

    2010-10-01

    This paper aims at introducing an automated approach to leukocyte recognition using fuzzy divergence and modified thresholding techniques. The recognition is done through the segmentation of nuclei where Gamma, Gaussian and Cauchy type of fuzzy membership functions are studied for the image pixels. It is in fact found that Cauchy leads better segmentation as compared to others. In addition, image thresholding is modified for better recognition. Results are studied and discussed.

  4. MEMBRAIN NEURAL NETWORK FOR VISUAL PATTERN RECOGNITION

    Directory of Open Access Journals (Sweden)

    Artur Popko

    2013-06-01

    Full Text Available Recognition of visual patterns is one of significant applications of Artificial Neural Networks, which partially emulate human thinking in the domain of artificial intelligence. In the paper, a simplified neural approach to recognition of visual patterns is portrayed and discussed. This paper is dedicated for investigators in visual patterns recognition, Artificial Neural Networking and related disciplines. The document describes also MemBrain application environment as a powerful and easy to use neural networks’ editor and simulator supporting ANN.

  5. Fusing Facial Features for Face Recognition

    Directory of Open Access Journals (Sweden)

    Jamal Ahmad Dargham

    2012-06-01

    Full Text Available Face recognition is an important biometric method because of its potential applications in many fields, such as access control, surveillance, and human-computer interaction. In this paper, a face recognition system that fuses the outputs of three face recognition systems based on Gabor jets is presented. The first system uses the magnitude, the second uses the phase, and the third uses the phase-weighted magnitude of the jets. The jets are generated from facial landmarks selected using three selection methods. It was found out that fusing the facial features gives better recognition rate than either facial feature used individually regardless of the landmark selection method.

  6. Comparative Analysis of Hand Gesture Recognition Techniques

    Directory of Open Access Journals (Sweden)

    Arpana K. Patel

    2015-03-01

    Full Text Available During past few years, human hand gesture for interaction with computing devices has continues to be active area of research. In this paper survey of hand gesture recognition is provided. Hand Gesture Recognition is contained three stages: Pre-processing, Feature Extraction or matching and Classification or recognition. Each stage contains different methods and techniques. In this paper define small description of different methods used for hand gesture recognition in existing system with comparative analysis of all method with its benefits and drawbacks are provided.

  7. On Multiple Typeface Arabic Script Recognition

    Directory of Open Access Journals (Sweden)

    Abdelmalek Zidouri

    2010-08-01

    Full Text Available In this study, we propose a new sub-word segmentation and recognition scheme, which is independent of font size and font type. D ifferent ways of recognition are attempted namely Neural N et, template matching and principal component analysis. Results show that the real problem in Arabic character recognition remains the challenging separation of sub-words into characters. The system is realized in a modularized way. The combination of the different modules forms the basis of a complete Arabic OCR system. A successful preprocessing stage is reported. Unlike Latin based languages, recognition of printed Arabic characters remains an open field of research.

  8. Recent Advances in Robust Speech Recognition Technology

    CERN Document Server

    Ramírez, Javier

    2011-01-01

    This E-book is a collection of articles that describe advances in speech recognition technology. Robustness in speech recognition refers to the need to maintain high speech recognition accuracy even when the quality of the input speech is degraded, or when the acoustical, articulate, or phonetic characteristics of speech in the training and testing environments differ. Obstacles to robust recognition include acoustical degradations produced by additive noise, the effects of linear filtering, nonlinearities in transduction or transmission, as well as impulsive interfering sources, and diminishe

  9. People Recognition: A Historical/Anthropological Perspective

    Directory of Open Access Journals (Sweden)

    A. Ardila

    1993-01-01

    Full Text Available Using current neurological and neuropsychological literature, and the analysis of different cultural and historical conditions, people recognition is analyzed. Different “subsystems” or “modules” could be involved in individuals' recognition: living versus non-living, own species versus other species, familiar versus non-familiar, males versus females, and individual identification versus emotional identification. Not only visual, but also auditory and even olfactory information may be involved in people recognition. Visual information involved in people recognition is proposed to include not only the perception of faces, but also the perception of whole body and gait, clothes, emotional expressions, and individual marks.

  10. Rank Pooling for Action Recognition.

    Science.gov (United States)

    Fernando, Basura; Gavves, Efstratios; Oramas M, Jose Oramas; Ghodrati, Amir; Tuytelaars, Tinne

    2017-04-01

    We propose a function-based temporal pooling method that captures the latent structure of the video sequence data - e.g., how frame-level features evolve over time in a video. We show how the parameters of a function that has been fit to the video data can serve as a robust new video representation. As a specific example, we learn a pooling function via ranking machines. By learning to rank the frame-level features of a video in chronological order, we obtain a new representation that captures the video-wide temporal dynamics of a video, suitable for action recognition. Other than ranking functions, we explore different parametric models that could also explain the temporal changes in videos. The proposed functional pooling methods, and rank pooling in particular, is easy to interpret and implement, fast to compute and effective in recognizing a wide variety of actions. We evaluate our method on various benchmarks for generic action, fine-grained action and gesture recognition. Results show that rank pooling brings an absolute improvement of 7-10 average pooling baseline. At the same time, rank pooling is compatible with and complementary to several appearance and local motion based methods and features, such as improved trajectories and deep learning features.

  11. Texture based iris recognition system

    Science.gov (United States)

    Mehrotra, Hunny; Gupta, Phalguni; Kaushik, Anil K.

    2008-04-01

    The paper proposes an efficient iris recognition algorithm, obtained through the fusion of Haar Wavelet and Circular Mellin operator. The recognition system preprocesses the captured iris image to remove the effect of holes or spot of light lying on the pupillary region which creates problem in pupil localization. The processed image is localized by detecting inner and outer boundaries from the pupil center using maximum value of the spectrum image. Then the eyelids are detected by fitting a 3 rd degree polynomial on the suitable edge segments and removing the region occluded by eyelids from the normalized iris image. The features for the iris pattern are extracted using Haar Wavelet and Circular Mellin operator. The Haar Wavelet decomposition reduces the size of feature vector while Circular Mellin operator is used for rotation and scale invariant feature extraction. The features are compared using Hamming Distance method and the fusion is done at decision level using Conjunction rule. The recognizer is found to be more robust with accuracy level more than 95%.

  12. Speech recognition from spectral dynamics

    Indian Academy of Sciences (India)

    Hynek Hermansky

    2011-10-01

    Information is carried in changes of a signal. The paper starts with revisiting Dudley’s concept of the carrier nature of speech. It points to its close connection to modulation spectra of speech and argues against short-term spectral envelopes as dominant carriers of the linguistic information in speech. The history of spectral representations of speech is briefly discussed. Some of the history of gradual infusion of the modulation spectrum concept into Automatic recognition of speech (ASR) comes next, pointing to the relationship of modulation spectrum processing to wellaccepted ASR techniques such as dynamic speech features or RelAtive SpecTrAl (RASTA) filtering. Next, the frequency domain perceptual linear prediction technique for deriving autoregressive models of temporal trajectories of spectral power in individual frequency bands is reviewed. Finally, posterior-based features, which allow for straightforward application of modulation frequency domain information, are described. The paper is tutorial in nature, aims at a historical global overview of attempts for using spectral dynamics in machine recognition of speech, and does not always provide enough detail of the described techniques. However, extensive references to earlier work are provided to compensate for the lack of detail in the paper.

  13. Segmental Rescoring in Text Recognition

    Science.gov (United States)

    2014-02-04

    ttm № tes/m, m* tmvr mowm* a Smyrna Of l δrtA£ACf02S’ A w m - y i p m AmiKSiS € f № ) C № № m .. sg6#?«rA fiθN ; Atφ h Sft№’·’Spxn mm m fim f№b t&m&mm...applying a Hidden Markov Model (HMM) recognition approach. Generating the plurality text hypotheses for the image forming includes generating a first...image. Applying segmental analysis to a segmentation determined by a first OCR engine, such as a segmentation determined by a Hidden Markov Model (HMM

  14. Recognition of handwriting from electromyography.

    Directory of Open Access Journals (Sweden)

    Michael Linderman

    Full Text Available 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.

  15. Aircraft recognition and tracking device

    Science.gov (United States)

    Filis, Dimitrios P.; Renios, Christos I.

    2011-11-01

    The technology of aircraft recognition and tracking has various applications in all areas of air navigation, be they civil or military, spanning from air traffic control and regulation at civilian airports to anti-aircraft weapon handling and guidance for military purposes.1, 18 The system presented in this thesis is an alternative implementation of identifying and tracking flying objects, which benefits from the optical spectrum by using an optical camera built into a servo motor (pan-tilt unit). More specifically, through the purpose-developed software, when a target (aircraft) enters the field of view of the camera18, it is both detected and identified.5, 22 Then the servo motor, being provided with data on target position and velocity, tracks the aircraft while it is in constant communication with the camera (Fig. 1). All the features are so designed as to operate under real time conditions.

  16. Place recognition using batlike sonar.

    Science.gov (United States)

    Vanderelst, Dieter; Steckel, Jan; Boen, Andre; Peremans, Herbert; Holderied, Marc W

    2016-08-02

    Echolocating bats have excellent spatial memory and are able to navigate to salient locations using bio-sonar. Navigating and route-following require animals to recognize places. Currently, it is mostly unknown how bats recognize places using echolocation. In this paper, we propose template based place recognition might underlie sonar-based navigation in bats. Under this hypothesis, bats recognize places by remembering their echo signature - rather than their 3D layout. Using a large body of ensonification data collected in three different habitats, we test the viability of this hypothesis assessing two critical properties of the proposed echo signatures: (1) they can be uniquely classified and (2) they vary continuously across space. Based on the results presented, we conclude that the proposed echo signatures satisfy both criteria. We discuss how these two properties of the echo signatures can support navigation and building a cognitive map.

  17. Robotic CCD microscope for enhanced crystal recognition

    Science.gov (United States)

    Segelke, Brent W.; Toppani, Dominique

    2007-11-06

    A robotic CCD microscope and procedures to automate crystal recognition. The robotic CCD microscope and procedures enables more accurate crystal recognition, leading to fewer false negative and fewer false positives, and enable detection of smaller crystals compared to other methods available today.

  18. The improved relative entropy for face recognition

    Directory of Open Access Journals (Sweden)

    Zhang Qi Rong

    2016-01-01

    Full Text Available The relative entropy is least sensitive to noise. In this paper, we propose the improved relative entropy for face recognition (IRE. The IRE method of recognition rate is far higher than the LDA, LPP method, by experimental results on CMU PIE face database and YALE B face database.

  19. Object Recognition Memory and the Rodent Hippocampus

    Science.gov (United States)

    Broadbent, Nicola J.; Gaskin, Stephane; Squire, Larry R.; Clark, Robert E.

    2010-01-01

    In rodents, the novel object recognition task (NOR) has become a benchmark task for assessing recognition memory. Yet, despite its widespread use, a consensus has not developed about which brain structures are important for task performance. We assessed both the anterograde and retrograde effects of hippocampal lesions on performance in the NOR…

  20. A New Method for Target Recognition

    Institute of Scientific and Technical Information of China (English)

    LU Jian-dong

    2004-01-01

    A reasonable explanation is given for possibility distribution descriptor that defined by Hall and Kandel and used in target recognition. Based on this explanation, possibility distribution entropy is defined. Some properties of possibility distribution entropy are discussed and a experiment for recognition of two fighters is shown.

  1. Weed Recognition Framework for Robotic Precision Farming

    DEFF Research Database (Denmark)

    Kounalakis, Tsampikos; Triantafyllidis, Georgios; Nalpantidis, Lazaros

    2016-01-01

    In this paper, we introduce a novel framework which applies known image features combined with advanced linear image representations for weed recognition. Our proposed weed recognition framework, is based on state-of-the-the art object/image categorization methods exploiting enhanced performance ...

  2. Case-Based Policy and Goal Recognition

    Science.gov (United States)

    2015-09-30

    Springfield, VA USA 2 ASEE Postdoctoral Fellow 3 Navy Center for Applied Research in Artificial Intelligence ; Naval Research Laboratory (Code 5514...tion performance in comparison to a baseline algorithm. Keywords: Policy recognition, intelligent agents, goal reasoning, air combat 1 Introduction The...recognition in beyond visual range air combat. In: Proceedings of the Twenty-Eighth Inter- national Florida Artificial Intelligence Research Society

  3. Gesture recognition for interactive exercise programs.

    Science.gov (United States)

    Perkins, Jedediah; Pavel, Misha; Jimison, Holly B; Scott, Susan

    2008-01-01

    This paper describes a gesture recognition system which can recognize seated exercises that will be incorporated into an in-home automated interactive exercise program. Hidden Markov Models (HMMs) are used as a motion classifier, with motion features extracted from the grayscale images and the location of the subject's head estimated at initialization. An overall recognition rate of 94.1% is achieved.

  4. Syllable Transposition Effects in Korean Word Recognition

    Science.gov (United States)

    Lee, Chang H.; Kwon, Youan; Kim, Kyungil; Rastle, Kathleen

    2015-01-01

    Research on the impact of letter transpositions in visual word recognition has yielded important clues about the nature of orthographic representations. This study investigated the impact of syllable transpositions on the recognition of Korean multisyllabic words. Results showed that rejection latencies in visual lexical decision for…

  5. Isolated Speech Recognition Using Artificial Neural Networks

    Science.gov (United States)

    2007-11-02

    In this project Artificial Neural Networks are used as research tool to accomplish Automated Speech Recognition of normal speech. A small size...the first stage of this work are satisfactory and thus the application of artificial neural networks in conjunction with cepstral analysis in isolated word recognition holds promise.

  6. Complex Spectral Minutiae Representation For Fingerprint Recognition

    NARCIS (Netherlands)

    Xu, Haiyun; Veldhuis, Raymond N.J.

    2010-01-01

    The spectral minutiae representation is designed for combining fingerprint recognition with template protection. This puts several constraints to the fingerprint recognition system: first, no relative alignment of two fingerprints is allowed due to the encrypted storage; second, a fixed-length featu

  7. Recognition without Awareness: Encoding and Retrieval Factors

    Science.gov (United States)

    Craik, Fergus I. M.; Rose, Nathan S.; Gopie, Nigel

    2015-01-01

    The article reports 4 experiments that explore the notion of recognition without awareness using words as the material. Previous work by Voss and associates has shown that complex visual patterns were correctly selected as targets in a 2-alternative forced-choice (2-AFC) recognition test although participants reported that they were guessing. The…

  8. The recognition heuristic: A decade of research

    Directory of Open Access Journals (Sweden)

    Gerd Gigerenzer

    2011-02-01

    Full Text Available The recognition heuristic exploits the basic psychological capacity for recognition in order to make inferences about unknown quantities in the world. In this article, we review and clarify issues that emerged from our initial work (Goldstein and Gigerenzer, 1999, 2002, including the distinction between a recognition and an evaluation process. There is now considerable evidence that (i the recognition heuristic predicts the inferences of a substantial proportion of individuals consistently, even in the presence of one or more contradicting cues, (ii people are adaptive decision makers in that accordance increases with larger recognition validity and decreases in situations when the validity is low or wholly indeterminable, and (iii in the presence of contradicting cues, some individuals appear to select different strategies. Little is known about these individual differences, or how to precisely model the alternative strategies. Although some researchers have attributed judgments inconsistent with the use of the recognition heuristic to compensatory processing, little research on such compensatory models has been reported. We discuss extensions of the recognition model, open questions, unanticipated results, and the surprising predictive power of recognition in forecasting.

  9. Automatic Intention Recognition in Conversation Processing

    Science.gov (United States)

    Holtgraves, Thomas

    2008-01-01

    A fundamental assumption of many theories of conversation is that comprehension of a speaker's utterance involves recognition of the speaker's intention in producing that remark. However, the nature of intention recognition is not clear. One approach is to conceptualize a speaker's intention in terms of speech acts [Searle, J. (1969). "Speech…

  10. Acoustic Pattern Recognition on Android Devices

    DEFF Research Database (Denmark)

    Møller, Maiken Bjerg; Gaarsdal, Jesper; Steen, Kim Arild

    2013-01-01

    an Android application developed for acoustic pattern recognition of bird species. The acoustic data is recorded using a built-in microphone, and pattern recognition is performed on the device, requiring no network connection. The algorithm is implemented in C++ as a native Android module and the Open...

  11. Automatic, Dimensional and Continuous Emotion Recognition

    NARCIS (Netherlands)

    Gunes, Hatice; Pantic, Maja; Vallverdú, J.

    2010-01-01

    Recognition and analysis of human emotions have attracted a lot of interest in the past two decades and have been researched extensively in neuroscience, psychology, cognitive sciences, and computer sciences. Most of the past research in machine analysis of human emotion has focused on recognition o

  12. Exemplar Based Recognition of Visual Shapes

    DEFF Research Database (Denmark)

    Olsen, Søren I.

    2005-01-01

    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...

  13. Modal-Power-Based Haptic Motion Recognition

    Science.gov (United States)

    Kasahara, Yusuke; Shimono, Tomoyuki; Kuwahara, Hiroaki; Sato, Masataka; Ohnishi, Kouhei

    Motion recognition based on sensory information is important for providing assistance to human using robots. Several studies have been carried out on motion recognition based on image information. However, in the motion of humans contact with an object can not be evaluated precisely by image-based recognition. This is because the considering force information is very important for describing contact motion. In this paper, a modal-power-based haptic motion recognition is proposed; modal power is considered to reveal information on both position and force. Modal power is considered to be one of the defining features of human motion. A motion recognition algorithm based on linear discriminant analysis is proposed to distinguish between similar motions. Haptic information is extracted using a bilateral master-slave system. Then, the observed motion is decomposed in terms of primitive functions in a modal space. The experimental results show the effectiveness of the proposed method.

  14. Speech Emotion Recognition Using Fuzzy Logic Classifier

    Directory of Open Access Journals (Sweden)

    Daniar aghsanavard

    2016-01-01

    Full Text Available Over the last two decades, emotions, speech recognition and signal processing have been one of the most significant issues in the adoption of techniques to detect them. Each method has advantages and disadvantages. This paper tries to suggest fuzzy speech emotion recognition based on the classification of speech's signals in order to better recognition along with a higher speed. In this system, the use of fuzzy logic system with 5 layers, which is the combination of neural progressive network and algorithm optimization of firefly, first, speech samples have been given to input of fuzzy orbit and then, signals will be investigated and primary classified in a fuzzy framework. In this model, a pattern of signals will be created for each class of signals, which results in reduction of signal data dimension as well as easier speech recognition. The obtained experimental results show that our proposed method (categorized by firefly, improves recognition of utterances.

  15. Articulation effects in melody recognition memory.

    Science.gov (United States)

    Wee Hun Lim, Stephen; Goh, Winston D

    2013-09-01

    Various surface features-timbre, tempo, and pitch-influence melody recognition memory, but articulation format effects, if any, remain unknown. For the first time, these effects were examined. In Experiment 1, melodies that remained in the same, or appeared in a different but similar, articulation format from study to test were recognized better than were melodies that were presented in a distinct format at test. A similar articulation format adequately induced matching processes to enhance recognition. Experiment 2 revealed that melodies rated as perceptually dissimilar on the basis of the location of the articulation mismatch did not impair recognition performance, suggesting an important boundary condition for articulation format effects on memory recognition-the matching of the memory trace and recognition probe may depend more on the overall proportion, rather than the temporal location, of the mismatch. The present findings are discussed in terms of a global matching advantage hypothesis.

  16. Face Recognition Based on Facial Features

    Directory of Open Access Journals (Sweden)

    Muhammad Sharif

    2012-08-01

    Full Text Available Commencing from the last decade several different methods have been planned and developed in the prospect of face recognition that is one of the chief stimulating zone in the area of image processing. Face recognitions processes have various applications in the prospect of security systems and crime investigation systems. The study is basically comprised of three phases, i.e., face detection, facial features extraction and face recognition. The first phase is the face detection process where region of interest i.e., features region is extracted. The 2nd phase is features extraction. Here face features i.e., eyes, nose and lips are extracted out commencing the extracted face area. The last module is the face recognition phase which makes use of the extracted left eye for the recognition purpose by combining features of Eigenfeatures and Fisherfeatures.

  17. End-Stop Exemplar Based Recognition

    DEFF Research Database (Denmark)

    Olsen, Søren I.

    2003-01-01

    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.......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...

  18. Discriminant Phase Component for Face Recognition

    Directory of Open Access Journals (Sweden)

    Naser Zaeri

    2012-01-01

    Full Text Available Numerous face recognition techniques have been developed owing to the growing number of real-world applications. Most of current algorithms for face recognition involve considerable amount of computations and hence they cannot be used on devices constrained with limited speed and memory. In this paper, we propose a novel solution for efficient face recognition problem for systems that utilize small memory capacities and demand fast performance. The new technique divides the face images into components and finds the discriminant phases of the Fourier transform of these components automatically using the sequential floating forward search method. A thorough study and comprehensive experiments relating time consumption versus system performance are applied to benchmark face image databases. Finally, the proposed technique is compared with other known methods and evaluated through the recognition rate and the computational time, where we achieve a recognition rate of 98.5% with computational time of 6.4 minutes for a database consisting of 2360 images.

  19. RECOGNITION OF HINDI (ARABIC HANDWRITTEN NUMERALS

    Directory of Open Access Journals (Sweden)

    Rawan I. Zaghloul

    2012-01-01

    Full Text Available Recognition of handwritten numerals has been one of the most challenging topics in image processing. This is due to its contributions in the automation process in several applications. The aim of this study was to build a classifier that can easily recognize offline handwritten Arabic numerals to support those applications that are deal with Hindi (Arabic numerals. A new algorithm for Hindi (Arabic Numeral Recognition is proposed. The proposed algorithm was developed using MATLAB and tested with a large sample of handwritten numeral datasets for different writers in different ages. Pattern recognition techniques are used to identify Hindi (Arabic handwritten numerals. After testing, high recognition rates were achieved, their ranges from 95% for some numerals and up to 99% for others. The proposed algorithm used a powerful set of features which proved to be effective in the recognition of Hindi (Arabic numerals.

  20. Apply lightweight recognition algorithms in optical music recognition

    Science.gov (United States)

    Pham, Viet-Khoi; Nguyen, Hai-Dang; Nguyen-Khac, Tung-Anh; Tran, Minh-Triet

    2015-02-01

    The problems of digitalization and transformation of musical scores into machine-readable format are necessary to be solved since they help people to enjoy music, to learn music, to conserve music sheets, and even to assist music composers. However, the results of existing methods still require improvements for higher accuracy. Therefore, the authors propose lightweight algorithms for Optical Music Recognition to help people to recognize and automatically play musical scores. In our proposal, after removing staff lines and extracting symbols, each music symbol is represented as a grid of identical M ∗ N cells, and the features are extracted and classified with multiple lightweight SVM classifiers. Through experiments, the authors find that the size of 10 ∗ 12 cells yields the highest precision value. Experimental results on the dataset consisting of 4929 music symbols taken from 18 modern music sheets in the Synthetic Score Database show that our proposed method is able to classify printed musical scores with accuracy up to 99.56%.

  1. Novel acoustic features for speech emotion recognition

    Institute of Scientific and Technical Information of China (English)

    ROH Yong-Wan; KIM Dong-Ju; LEE Woo-Seok; HONG Kwang-Seok

    2009-01-01

    This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech. The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform (FFT) spectral entropy, delta FFT spectral entropy, Mel-frequency filter bank (MFB)spectral entropy, and Delta MFB spectral entropy. Spectral-based entropy features are simple. They reflect frequency characteristic and changing characteristic in frequency of speech. We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance. Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results, respectively.These scores are first obtained from a pattern recognition procedure. The pattern recognition phase uses the Gaussian mixture model (GMM). We classify the four emotional states as anger, sadness,happiness and neutrality. The proposed method is evaluated using 45 sentences in each emotion for 30 subjects, 15 males and 15 females. Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy, Zero Crossing Rate (ZCR),linear prediction coefficient (LPC), and pitch parameters. We demonstrate the effectiveness of the proposed approach. One of the proposed features, combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods. We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

  2. Textual emotion recognition for enhancing enterprise computing

    Science.gov (United States)

    Quan, Changqin; Ren, Fuji

    2016-05-01

    The growing interest in affective computing (AC) brings a lot of valuable research topics that can meet different application demands in enterprise systems. The present study explores a sub area of AC techniques - textual emotion recognition for enhancing enterprise computing. Multi-label emotion recognition in text is able to provide a more comprehensive understanding of emotions than single label emotion recognition. A representation of 'emotion state in text' is proposed to encompass the multidimensional emotions in text. It ensures the description in a formal way of the configurations of basic emotions as well as of the relations between them. Our method allows recognition of the emotions for the words bear indirect emotions, emotion ambiguity and multiple emotions. We further investigate the effect of word order for emotional expression by comparing the performances of bag-of-words model and sequence model for multi-label sentence emotion recognition. The experiments show that the classification results under sequence model are better than under bag-of-words model. And homogeneous Markov model showed promising results of multi-label sentence emotion recognition. This emotion recognition system is able to provide a convenient way to acquire valuable emotion information and to improve enterprise competitive ability in many aspects.

  3. Status of pattern recognition with wavelet analysis

    Institute of Scientific and Technical Information of China (English)

    Yuanyan TANG

    2008-01-01

    Pattern recognition has become one of the fastest growing research topics in the fields of computer science and electrical and electronic engineering in the recent years.Advanced research and development in pattern recognition have found numerous applications in such areas as artificial intelligence,information security,biometrics,military science and technology,finance and economics,weather forecast,image processing,communication,biomedical engineering,document processing,robot vision,transportation,and endless other areas,with many encouraging results.The achievement of pattern recognition is most likely to benefit from some new developments of theoretical mathematics including wavelet analysis.This paper aims at a brief survey of pattern recognition with the wavelet theory.It contains the following respects:analysis and detection of singularities with wavelets;wavelet descriptors for shapes of the objects;invariant representation of patterns;handwritten and printed character recognition;texture analysis and classification;image indexing and retrieval;classification and clustering;document analysis with wavelets;iris pattern recognition;face recognition using wavelet transform;hand gestures classification;character processing with B-spline wavelet transform;wavelet-based image fusion,and others.

  4. [Face recognition in patients with schizophrenia].

    Science.gov (United States)

    Doi, Hirokazu; Shinohara, Kazuyuki

    2012-07-01

    It is well known that patients with schizophrenia show severe deficiencies in social communication skills. These deficiencies are believed to be partly derived from abnormalities in face recognition. However, the exact nature of these abnormalities exhibited by schizophrenic patients with respect to face recognition has yet to be clarified. In the present paper, we review the main findings on face recognition deficiencies in patients with schizophrenia, particularly focusing on abnormalities in the recognition of facial expression and gaze direction, which are the primary sources of information of others' mental states. The existing studies reveal that the abnormal recognition of facial expression and gaze direction in schizophrenic patients is attributable to impairments in both perceptual processing of visual stimuli, and cognitive-emotional responses to social information. Furthermore, schizophrenic patients show malfunctions in distributed neural regions, ranging from the fusiform gyrus recruited in the structural encoding of facial stimuli, to the amygdala which plays a primary role in the detection of the emotional significance of stimuli. These findings were obtained from research in patient groups with heterogeneous characteristics. Because previous studies have indicated that impairments in face recognition in schizophrenic patients might vary according to the types of symptoms, it is of primary importance to compare the nature of face recognition deficiencies and the impairments of underlying neural functions across sub-groups of patients.

  5. The neural substrate of gesture recognition.

    Science.gov (United States)

    Villarreal, Mirta; Fridman, Esteban A; Amengual, Alejandra; Falasco, German; Gerschcovich, Eliana Roldan; Gerscovich, Eliana Roldan; Ulloa, Erlinda R; Leiguarda, Ramon C

    2008-01-01

    Previous studies have linked action recognition with a particular pool of neurons located in the ventral premotor cortex, the posterior parietal cortex and the superior temporal sulcus (the mirror neuron system). However, it is still unclear if transitive and intransitive gestures share the same neural substrates during action-recognition processes. In the present study, we used event-related functional magnetic resonance imaging (fMRI) to assess the cortical areas active during recognition of pantomimed transitive actions, intransitive gestures, and meaningless control actions. Perception of all types of gestures engaged the right pre-supplementary motor area (pre-SMA), and bilaterally in the posterior superior temporal cortex, the posterior parietal cortex, occipitotemporal regions and visual cortices. Activation of the posterior superior temporal sulcus/superior temporal gyrus region was found in both hemispheres during recognition of transitive and intransitive gestures, and in the right hemisphere during the control condition; the middle temporal gyrus showed activation in the left hemisphere when subjects recognized transitive and intransitive gestures; activation of the left inferior parietal lobe and intraparietal sulcus (IPS) was mainly observed in the left hemisphere during recognition of the three conditions. The most striking finding was the greater activation of the left inferior frontal gyrus (IFG) during recognition of intransitive actions. Results show that a similar neural substrate, albeit, with a distinct engagement underlies the cognitive processing of transitive and intransitive gestures recognition. These findings suggest that selective disruptions in these circuits may lead to distinct clinical deficits.

  6. Efficient Interaction Recognition through Positive Action Representation

    Directory of Open Access Journals (Sweden)

    Tao Hu

    2013-01-01

    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.

  7. Window Size Impact in Human Activity Recognition

    Directory of Open Access Journals (Sweden)

    Oresti Banos

    2014-04-01

    Full Text Available Signal segmentation is a crucial stage in the activity recognition process; however, this has been rarely and vaguely characterized so far. Windowing approaches are normally used for segmentation, but no clear consensus exists on which window size should be preferably employed. In fact, most designs normally rely on figures used in previous works, but with no strict studies that support them. Intuitively, decreasing the window size allows for a faster activity detection, as well as reduced resources and energy needs. On the contrary, large data windows are normally considered for the recognition of complex activities. In this work, we present an extensive study to fairly characterize the windowing procedure, to determine its impact within the activity recognition process and to help clarify some of the habitual assumptions made during the recognition system design. To that end, some of the most widely used activity recognition procedures are evaluated for a wide range of window sizes and activities. From the evaluation, the interval 1–2 s proves to provide the best trade-off between recognition speed and accuracy. The study, specifically intended for on-body activity recognition systems, further provides designers with a set of guidelines devised to facilitate the system definition and configuration according to the particular application requirements and target activities.

  8. Robust video foreground segmentation and face recognition

    Institute of Scientific and Technical Information of China (English)

    GUAN Ye-peng

    2009-01-01

    Face recognition provides a natural visual interface for human computer interaction (HCI) applications.The process of face recognition,however,is inhibited by variations in the appearance of face images caused by changes in lighting,expression,viewpoint,aging and introduction of occlusion.Although various algorithms have been presented for face recognition,face recognition is still a very challenging topic.A novel approach of real time face recognition for HCI is proposed in the paper.In view of the limits of the popular approaches to foreground segmentation,wavelet multi-scale transform based background subtraction is developed to extract foreground objects.The optimal selection of the threshold is automatically determined,which does not require any complex supervised training or manual experimental calibration.A robust real time face recognition algorithm is presented,which combines the projection matrixes without iteration and kernel Fisher discriminant analysis (KFDA) to overcome some difficulties existing in the real face recognition.Superior performance of the proposed algorithm is demonstrated by comparing with other algorithms through experiments.The proposed algorithm can also be applied to the video image sequences of natural HCI.

  9. Selective networks and recognition automata.

    Science.gov (United States)

    Reeke, G N; Edelman, G M

    1984-01-01

    The results we have presented demonstrate that a network based on a selective principle can function in the absence of forced learning or an a priori program to give recognition, classification, generalization, and association. While Darwin II is not a model of any actual nervous system, it does set out to solve one of the same problems that evolution had to solve--the need to form categories in a bottom-up manner from information in the environment, without incorporating the assumptions of any particular observer. The key features of the model that make this possible are (1) Darwin II incorporates selective networks whose initial specificities enable them to respond without instruction to unfamiliar stimuli; (2) degeneracy provides multiple possibilities of response to any one stimulus, at the same time providing functional redundancy against component failure; (3) the output of Darwin II is a pattern of response, making use of the simultaneous responses of multiple degenerate groups to avoid the need for very high specificity and the combinatorial disaster that would imply; (4) reentry within individual networks vitiates the limitations described by Minsky and Papert for a class of perceptual automata lacking such connections; and (5) reentry between intercommunicating networks with different functions gives rise to new functions, such as association, that either one alone could not display. The two kinds of network are roughly analogous to the two kinds of category formation that people use: Darwin, corresponding to the exemplar description of categories, and Wallace, corresponding to the probabilistic matching description of categories. These principles lead to a new class of pattern-recognizing machine of which Darwin II is just an example. There are a number of obvious extensions to this work that we are pursuing. These include giving Darwin II the capability to deal with stimuli that are in motion, an ability that probably precedes the ability of biological

  10. Isolated digit recognition without time alignment

    Science.gov (United States)

    Gay, Jeffrey Mark

    1994-12-01

    This thesis examines methods for isolated digit recognition without using time alignment. Resource requirements for isolated word recognizers that use time alignment can become prohibitively large as the vocabulary to be classified grows. Thus, methods capable of achieving recognition rates comparable to those obtained with current methods using these techniques are needed. The goals of this research are to find feature sets for speech recognition that perform well without using time alignment, and to identify classifiers that provide good performance with these features. Using the digits from the TI46 database, baseline speaker-independent recognition rates of 95.2% for the complete speaker set and 98.1% for the male speaker set are established using dynamic time warping (DTW). This work begins with features derived from spectrograms of each digit. Based on a critical band frequency scale covering the telephone bandwidth (300-3000 Hz), these critical band energy features are classified alone and in combination with several other feature sets, with several different classifiers. With this method, there is one 'short' feature vector per word. For speaker-independent recognition using the complete speaker set and a multi-layer perceptron (MLP) classifier, a recognition rate of 92.4% is achieved. For the same classifier with the male speaker set, a recognition rate of 97.1% is achieved. For the male speaker set, there is no statistical difference between results using DTW, and those using the MLP and no time alignment. This shows that there are feature sets that may provide high recognition rates for isolated word recognition without the need for time alignment.

  11. WCTFR : WRAPPING CURVELET TRANSFORM BASED FACE RECOGNITION

    Directory of Open Access Journals (Sweden)

    Arunalatha J S

    2015-03-01

    Full Text Available The recognition of a person based on biological features are efficient compared with traditional knowledge based recognition system. In this paper we propose Wrapping Curvelet Transform based Face Recognition (WCTFR. The Wrapping Curvelet Transform (WCT is applied on face images of database and test images to derive coefficients. The obtained coefficient matrix is rearranged to form WCT features of each image. The test image WCT features are compared with database images using Euclidean Distance (ED to compute Equal Error Rate (EER and True Success Rate (TSR. The proposed algorithm with WCT performs better than Curvelet Transform algorithms used in [1], [10] and [11].

  12. A HYBRID METHOD FOR EFFICIENT TARGET RECOGNITION

    Institute of Scientific and Technical Information of China (English)

    Zhang Yanning; Zheng Jiangbin; Zhao Rongchun

    2003-01-01

    An efficient target recognition method for remote sensing image is proposed in this paper, which is based on moment invariant and support vector machine. First, seven Hu's invariant moments are extracted as a feature vector. Then, a support vector machine is used to recognize targets of planes and ships on binary remote sensing images. The experimental results show that the new method can obtain better recognition results. Moreover, it is observed that the range of the binary values of image affects directly the performance of recognition.

  13. Hidden neural networks: application to speech recognition

    DEFF Research Database (Denmark)

    Riis, Søren Kamaric

    1998-01-01

    We evaluate the hidden neural network HMM/NN hybrid on two speech recognition benchmark tasks; (1) task independent isolated word recognition on the Phonebook database, and (2) recognition of broad phoneme classes in continuous speech from the TIMIT database. It is shown how hidden neural networks...... (HNNs) with much fewer parameters than conventional HMMs and other hybrids can obtain comparable performance, and for the broad class task it is illustrated how the HNN can be applied as a purely transition based system, where acoustic context dependent transition probabilities are estimated by neural...

  14. Modelling of DNA-protein recognition

    Science.gov (United States)

    Rein, R.; Garduno, R.; Colombano, S.; Nir, S.; Haydock, K.; Macelroy, R. D.

    1980-01-01

    Computer model-building procedures using stereochemical principles together with theoretical energy calculations appear to be, at this stage, the most promising route toward the elucidation of DNA-protein binding schemes and recognition principles. A review of models and bonding principles is conducted and approaches to modeling are considered, taking into account possible di-hydrogen-bonding schemes between a peptide and a base (or a base pair) of a double-stranded nucleic acid in the major groove, aspects of computer graphic modeling, and a search for isogeometric helices. The energetics of recognition complexes is discussed and several models for peptide DNA recognition are presented.

  15. Robust recognition via information theoretic learning

    CERN Document Server

    He, Ran; Yuan, Xiaotong; Wang, Liang

    2014-01-01

    This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy.The?authors?resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency,?the brief?introduces the additive and multip

  16. Temporal visual cues aid speech recognition

    DEFF Research Database (Denmark)

    Zhou, Xiang; Ross, Lars; Lehn-Schiøler, Tue;

    2006-01-01

    that it is the temporal synchronicity of the visual input that aids parsing of the auditory stream. More specifically, we expected that purely temporal information, which does not convey information such as place of articulation may facility word recognition. METHODS: To test this prediction we used temporal features...... of audio to generate an artificial talking-face video and measured word recognition performance on simple monosyllabic words. RESULTS: When presenting words together with the artificial video we find that word recognition is improved over purely auditory presentation. The effect is significant (p...

  17. Face Recognition Using Kernel Discriminant Analysis

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Linear Discrimiant Analysis (LDA) has demonstrated their success in face recognition. But LDA is difficult to handle the high nonlinear problems, such as changes of large viewpoint and illumination in face recognition. In order to overcome these problems, we investigate Kernel Discriminant Analysis (KDA) for face recognition. This approach adopts the kernel functions to replace the dot products of nonlinear mapping in the high dimensional feature space, and then the nonlinear problem can be solved in the input space conveniently without explicit mapping. Two face databases are used to test KDA approach. The results show that our approach outperforms the conventional PCA(Eigenface) and LDA(Fisherface) approaches.

  18. Recognition of Objects by Using Genetic Programming

    Directory of Open Access Journals (Sweden)

    Nerses Safaryan

    2013-01-01

    Full Text Available This document is devoted to the task of object detection and recognition in digital images by using genetic programming. The goal was to improve and simplify existing approaches. The detection and recognition are achieved by means of extracting the features. A genetic program is used to extract and classify features of objects. Simple features and primitive operators are processed in genetic programming operations. We are trying to detect and to recognize objects in SAR images. Due to the new approach described in this article, five and seven types of objects were recognized with good recognition results.

  19. Fingertip Detection for Hand Pose Recognition

    Directory of Open Access Journals (Sweden)

    M.K. Bhuyan

    2012-03-01

    Full Text Available In this paper, a novel algorithm is proposed for fingertip detection and finger type recognition. The algorithm is applied for locating fingertips in hand region extracted by Bayesian rule based skincolor segmentation. Morphological operations are performed in the segmented hand region by observing key geometric features. A probabilistic modeling of the geometric features of finger movement has made the finger type recognition process significantly robust. Proposed method can be employed in a variety of applications like sign language recognition and human robot interactions.

  20. Traditional facial tattoos disrupt face recognition processes.

    Science.gov (United States)

    Buttle, Heather; East, Julie

    2010-01-01

    Factors that are important to successful face recognition, such as features, configuration, and pigmentation/reflectance, are all subject to change when a face has been engraved with ink markings. Here we show that the application of facial tattoos, in the form of spiral patterns (typically associated with the Maori tradition of a Moko), disrupts face recognition to a similar extent as face inversion, with recognition accuracy little better than chance performance (2AFC). These results indicate that facial tattoos can severely disrupt our ability to recognise a face that previously did not have the pattern.

  1. Real Time Implementation Of Face Recognition System

    Directory of Open Access Journals (Sweden)

    Megha Manchanda

    2014-10-01

    Full Text Available This paper proposes face recognition method using PCA for real time implementation. Nowadays security is gaining importance as it is becoming necessary for people to keep passwords in their mind and carry cards. Such implementations however, are becoming less secure and practical, also is becoming more problematic thus leading to an increasing interest in techniques related to biometrics systems. Face recognition system is amongst important subjects in biometrics systems. This system is very useful for security in particular and has been widely used and developed in many countries. This study aims to achieve face recognition successfully by detecting human face in real time, based on Principal Component Analysis (PCA algorithm.

  2. Pattern recognition and classification an introduction

    CERN Document Server

    Dougherty, Geoff

    2012-01-01

    The use of pattern recognition and classification is fundamental to many of the automated electronic systems in use today. However, despite the existence of a number of notable books in the field, the subject remains very challenging, especially for the beginner. Pattern Recognition and Classification presents a comprehensive introduction to the core concepts involved in automated pattern recognition. It is designed to be accessible to newcomers from varied backgrounds, but it will also be useful to researchers and professionals in image and signal processing and analysis, and in computer visi

  3. Robust speaker recognition in noisy environments

    CERN Document Server

    Rao, K Sreenivasa

    2014-01-01

    This book discusses speaker recognition methods to deal with realistic variable noisy environments. The text covers authentication systems for; robust noisy background environments, functions in real time and incorporated in mobile devices. The book focuses on different approaches to enhance the accuracy of speaker recognition in presence of varying background environments. The authors examine: (a) Feature compensation using multiple background models, (b) Feature mapping using data-driven stochastic models, (c) Design of super vector- based GMM-SVM framework for robust speaker recognition, (d) Total variability modeling (i-vectors) in a discriminative framework and (e) Boosting method to fuse evidences from multiple SVM models.

  4. State Toleration, Religious Recognition and Equality

    DEFF Research Database (Denmark)

    Lægaard, Sune

    2013-01-01

    In debates about multiculturalism, it is widely claimed that ‘toleration is not enough’ and that we need to go ‘beyond toleration’ to some form of politics of recognition in order to satisfactorily address contemporary forms of cultural diversity (e.g. the presence in Europe of Muslim minorities...... of the conceptual argument for going ‘beyond toleration’: at the institutional level, recognition, as well as toleration, may be inadequate and inappropriate from the point of view of multicultural accommodation of cultural difference. My diagnosis therefore is that the toleration-recognition issue is not about...

  5. Recognition of two great contemporaries

    Directory of Open Access Journals (Sweden)

    Milin Melita

    2015-01-01

    Full Text Available The common denominator in the careers of two contemporaries and great men, citizens of Austria-Hungary - Leoš Janáček and Sigmund Freud - was that, in spite of their status as outsiders, they managed to achieve well-deserved recognition. Both non-Germans, they had to surmount a number of obstacles in order to attain their professional goals. The Slavophile Janáček dreamed for a long time of success in Prague, which came at last in 1916, two years before a triumph in Vienna. Freud had serious difficulties in his academic career because of the strengthening of racial prejudices and national hatred which were especially marked at the end of the 19th century. After the dissolution of the Empire things changed for the better for the composer, whose works got an excellent reception in Austria and Germany, whereas the psychiatrist had to leave Vienna after the Anschluss. [Projekat Ministarstva nauke Republike Srbije, br. ON 177004: Serbian Musical Identities within Local and Global Frameworks: Traditions, Changes, Challenges

  6. Aircraft recognition and pose estimation

    Science.gov (United States)

    Hmam, Hatem; Kim, Jijoong

    2000-05-01

    This work presents a geometry based vision system for aircraft recognition and pose estimation using single images. Pose estimation improves the tracking performance of guided weapons with imaging seekers, and is useful in estimating target manoeuvres and aim-point selection required in the terminal phase of missile engagements. After edge detection and straight-line extraction, a hierarchy of geometric reasoning algorithms is applied to form line clusters (or groupings) for image interpretation. Assuming a scaled orthographic projection and coplanar wings, lateral symmetry inherent in the airframe provides additional constraints to further reject spurious line clusters. Clusters that accidentally pass all previous tests are checked against the original image and are discarded. Valid line clusters are then used to deduce aircraft viewing angles. By observing that the leading edges of wings of a number of aircraft of interest are within 45 to 65 degrees from the symmetry axis, a bounded range of aircraft viewing angles can be found. This generic property offers the advantage of not requiring the storage of complete aircraft models viewed from all aspects, and can handle aircraft with flexible wings (e.g. F111). Several aircraft images associated with various spectral bands (i.e. visible and infra-red) are finally used to evaluate the system's performance.

  7. Distributed nestmate recognition in ants.

    Science.gov (United States)

    Esponda, Fernando; Gordon, Deborah M

    2015-05-07

    We propose a distributed model of nestmate recognition, analogous to the one used by the vertebrate immune system, in which colony response results from the diverse reactions of many ants. The model describes how individual behaviour produces colony response to non-nestmates. No single ant knows the odour identity of the colony. Instead, colony identity is defined collectively by all the ants in the colony. Each ant responds to the odour of other ants by reference to its own unique decision boundary, which is a result of its experience of encounters with other ants. Each ant thus recognizes a particular set of chemical profiles as being those of non-nestmates. This model predicts, as experimental results have shown, that the outcome of behavioural assays is likely to be variable, that it depends on the number of ants tested, that response to non-nestmates changes over time and that it changes in response to the experience of individual ants. A distributed system allows a colony to identify non-nestmates without requiring that all individuals have the same complete information and helps to facilitate the tracking of changes in cuticular hydrocarbon profiles, because only a subset of ants must respond to provide an adequate response.

  8. Face Recognition Based on Principal Component Analysis

    Directory of Open Access Journals (Sweden)

    Ali Javed

    2013-02-01

    Full Text Available The purpose of the proposed research work is to develop a computer system that can recognize a person by comparing the characteristics of face to those of known individuals. The main focus is on frontal two dimensional images that are taken in a controlled environment i.e. the illumination and the background will be constant. All the other methods of person’s identification and verification like iris scan or finger print scan require high quality and costly equipment’s but in face recognition we only require a normal camera giving us a 2-D frontal image of the person that will be used for the process of the person’s recognition. Principal Component Analysis technique has been used in the proposed system of face recognition. The purpose is to compare the results of the technique under the different conditions and to find the most efficient approach for developing a facial recognition system

  9. A Multi—View Face Recognition System

    Institute of Scientific and Technical Information of China (English)

    张永越; 彭振云; 等

    1997-01-01

    In many automatic face recognition systems,posture constraining is a key factor preventing them from application.In this paper a series of strategies will be described to achieve a system which enables face recognition under varying pose.These approaches include the multi-view face modeling,the threschold image based face feature detection,the affine transformation based face posture normalization and the template matching based face identification.Combining all of these strategies,a face recognition system with the pose invariance is designed successfully,Using a 75MHZ Pentium PC and with a database of 75 individuals,15 images for each person,and 225 test images with various postures,a very good recognition rate of 96.89% is obtained.

  10. Hand Recognition in Live-Streaming Video

    OpenAIRE

    Mikhail, Belov

    2011-01-01

    The article describes the algorithmic component of the pattern recognition method for extracting hand patterns from a video stream. Methods removing excess information from frames, localizing fragments with a hand and extracting hand contours to classify them are described.

  11. Automatic modulation recognition of communication signals

    CERN Document Server

    Azzouz, Elsayed Elsayed

    1996-01-01

    Automatic modulation recognition is a rapidly evolving area of signal analysis. In recent years, interest from the academic and military research institutes has focused around the research and development of modulation recognition algorithms. Any communication intelligence (COMINT) system comprises three main blocks: receiver front-end, modulation recogniser and output stage. Considerable work has been done in the area of receiver front-ends. The work at the output stage is concerned with information extraction, recording and exploitation and begins with signal demodulation, that requires accurate knowledge about the signal modulation type. There are, however, two main reasons for knowing the current modulation type of a signal; to preserve the signal information content and to decide upon the suitable counter action, such as jamming. Automatic Modulation Recognition of Communications Signals describes in depth this modulation recognition process. Drawing on several years of research, the authors provide a cr...

  12. History of Maternal Recognition of Pregnancy.

    Science.gov (United States)

    Bazer, Fuller W

    2015-01-01

    The mechanism for signaling pregnancy recognition is highly variable among species, and the signaling molecule itself varies between estrogens in pigs to chorionic gonadotrophin in primates. This chapter provides insight into the menstrual cycle of women and estrous cycles of rodents, dog, cat, pigs, sheep, rabbits, and marsupials, as well as the hormones required for pregnancy recognition. Pregnancy recognition involves specific hormones such as prolactin in rodents or interferons in ruminants and estrogens in pigs that in their own way ensure the maintenance of the corpus luteum and its secretion of progesterone which is the hormone of pregnancy. However, these pregnancy recognition signals may also modify gene expression in a cell-specific and temporal manner to ensure the growth and development of the conceptus. This chapter provides some historical aspects of the development of understanding of mechanisms for the establishment and maintenance of pregnancy in several species of mammals.

  13. The Fuzzy Sets Approach to Pattern Recognition

    Science.gov (United States)

    Wilson, T.

    1972-01-01

    The fuzzy set concept is defined and its application to pattern recognition is illustrated. An iterative procedure for learning the equi-membership surfaces and for generating a set of discriminate functions for two pattern classes is given.

  14. Support vector machine for automatic pain recognition

    Science.gov (United States)

    Monwar, Md Maruf; Rezaei, Siamak

    2009-02-01

    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.

  15. Wavelet based approach for facial expression recognition

    Directory of Open Access Journals (Sweden)

    Zaenal Abidin

    2015-03-01

    Full Text Available Facial expression recognition is one of the most active fields of research. Many facial expression recognition methods have been developed and implemented. Neural networks (NNs have capability to undertake such pattern recognition tasks. The key factor of the use of NN is based on its characteristics. It is capable in conducting learning and generalizing, non-linear mapping, and parallel computation. Backpropagation neural networks (BPNNs are the approach methods that mostly used. In this study, BPNNs were used as classifier to categorize facial expression images into seven-class of expressions which are anger, disgust, fear, happiness, sadness, neutral and surprise. For the purpose of feature extraction tasks, three discrete wavelet transforms were used to decompose images, namely Haar wavelet, Daubechies (4 wavelet and Coiflet (1 wavelet. To analyze the proposed method, a facial expression recognition system was built. The proposed method was tested on static images from JAFFE database.

  16. Fuzzy Neural Model for Flatness Pattern Recognition

    Institute of Scientific and Technical Information of China (English)

    JIA Chun-yu; SHAN Xiu-ying; LIU Hong-min; NIU Zhao-ping

    2008-01-01

    For the problems occurring in a least square method model,a fuzzy model,and a neural network model for flatness pattern recognition,a fuzzy neural network model for flatness pattern recognition with only three-input and three-output signals was proposed with Legendre orthodoxy polynomial as basic pattern,based on fuzzy logic expert experiential knowledge and genetic-BP hybrid optimization algorithm.The model not only had definite physical meanings in its inner nodes,but also had strong self-adaptability,anti-interference ability,high recognition precision,and high velocity,thereby meeting the demand of high-precision flatness control for cold strip mill and providing a convenient,practical,and novel method for flatness pattern recognition.

  17. RGB-D-T based Face Recognition

    DEFF Research Database (Denmark)

    Nikisins, Olegs; Nasrollahi, Kamal; Greitans, Modris

    2014-01-01

    Facial images are of critical importance in many real-world applications from gaming to surveillance. The current literature on facial image analysis, from face detection to face and facial expression recognition, are mainly performed in either RGB, Depth (D), or both of these modalities. But......, such analyzes have rarely included Thermal (T) modality. This paper paves the way for performing such facial analyzes using synchronized RGB-D-T facial images by introducing a database of 51 persons including facial images of different rotations, illuminations, and expressions. Furthermore, a face recognition...... algorithm has been developed to use these images. The experimental results show that face recognition using such three modalities provides better results compared to face recognition in any of such modalities in most of the cases....

  18. An Efficient Gait Recognition with Backpack Removal

    Science.gov (United States)

    Lee, Heesung; Hong, Sungjun; Kim, Euntai

    2009-12-01

    Gait-based human identification is a paradigm to recognize individuals using visual cues that characterize their walking motion. An important requirement for successful gait recognition is robustness to variations including different lighting conditions, poses, and walking speed. Deformation of the gait silhouette caused by objects carried by subjects also has a significant effect on the performance of gait recognition systems; a backpack is the most common of these objects. This paper proposes methods for eliminating the effect of a carried backpack for efficient gait recognition. We apply simple, recursive principal component analysis (PCA) reconstructions and error compensation to remove the backpack from the gait representation and then conduct gait recognition. Experiments performed with the CASIA database illustrate the performance of the proposed algorithm.

  19. Gesture recognition for an exergame prototype

    NARCIS (Netherlands)

    Gacem, B.; Vergouw, R.; Verbiest, H.; Cicek, E.; van Oosterhout, T.; Krose, B.; Bakkes, S.

    2011-01-01

    We will demonstrate a prototype exergame aimed at the serious domain of elderly fitness. The exergame incorporates straightforward means to gesture recognition, and utilises a Kinect camera to obtain 2.5D sensory data of the human user.

  20. Hand gesture recognition based on surface electromyography.

    Science.gov (United States)

    Samadani, Ali-Akbar; Kulic, Dana

    2014-01-01

    Human hands are the most dexterous of human limbs and hand gestures play an important role in non-verbal communication. Underlying electromyograms associated with hand gestures provide a wealth of information based on which varying hand gestures can be recognized. This paper develops an inter-individual hand gesture recognition model based on Hidden Markov models that receives surface electromyography (sEMG) signals as inputs and predicts a corresponding hand gesture. The developed recognition model is tested with a dataset of 10 various hand gestures performed by 25 subjects in a leave-one-subject-out cross validation and an inter-individual recognition rate of 79% was achieved. The promising recognition rate demonstrates the efficacy of the proposed approach for discriminating between gesture-specific sEMG signals and could inform the design of sEMG-controlled prostheses and assistive devices.

  1. Facial emotion recognition in remitted depressed women.

    Science.gov (United States)

    Biyik, Utku; Keskin, Duygu; Oguz, Kaya; Akdeniz, Fisun; Gonul, Ali Saffet

    2015-10-01

    Although major depressive disorder (MDD) is primarily characterized by mood symptoms, depressed patients have impairments in facial emotion recognition in many of the basic emotions (anger, fear, happiness, surprise, disgust and sadness). On the other hand, the data in remitted MDD (rMDD) patients is inconsistent and it is not clear that if those impairments persist in remission. To extend the current findings, we applied facial emotion recognition test to a group of remitted depressed women and compared to those of controls. Analyses of variance results showed a significant emotion and group interaction, and in the post hoc analyses, rMDD patients had higher accuracy rate for recognition of sadness compared to those of controls. There were no differences in the reaction time among the patients and controls across the all the basic emotions. The higher recognition rates for sad faces in rMDD patients might contribute to the impairments in social communication and the prognosis of the disease.

  2. BIOMETRIC RECOGNITION: A MODERN ERA FOR SECURITY

    Directory of Open Access Journals (Sweden)

    VIJAY DHIR,

    2010-08-01

    Full Text Available Many varieties of systems require some reliable recognition system that gives the identity of a person. There are many applications that need the identity of a person to operate such as ATM, Laptops, Access to buildings, cellular Phones & some sensitive security locations. In the absence of robust personal recognition schemes, these systems are vulnerable to the wiles of an impostor. Biometric recognition, or simply biometrics, refers to the automatic recognition of individuals based on their physiological and/or behavioral characteristics. By using biometrics it is possible to confirm or establish an ndividual’s identity based on “who she is”, rather than by “what she possesses” (e.g., an ID card or “what she remembers” (e.g., a password. In this paper, we give a brief overview of the field of biometrics and summarize some of its advantages, disadvantages, strengths, limitations, and related privacy concerns.

  3. Gesture Recognition for an Exergame Prototype

    NARCIS (Netherlands)

    Gacem, Brahim; Vergouw, Robert; Verbiest, Harm; Cicek, Emrullah; Van Oosterhout, Tim; Bakkes, Sander; Kröse, Ben

    2011-01-01

    We will demonstrate a prototype exergame aimed at the serious domain of elderly fitness. The exergame incorporates straightforward means to gesture recognition, and utilises a Kinect camera to obtain 2.5D sensory data of the human user.

  4. Parallel Architecture for Face Recognition using MPI

    Directory of Open Access Journals (Sweden)

    Dalia Shouman Ibrahim

    2017-01-01

    Full Text Available The face recognition applications are widely used in different fields like security and computer vision. The recognition process should be done in real time to take fast decisions. Princi-ple Component Analysis (PCA considered as feature extraction technique and is widely used in facial recognition applications by projecting images in new face space. PCA can reduce the dimensionality of the image. However, PCA consumes a lot of processing time due to its high intensive computation nature. Hence, this paper proposes two different parallel architectures to accelerate training and testing phases of PCA algorithm by exploiting the benefits of distributed memory architecture. The experimental results show that the proposed architectures achieve linear speed-up and system scalability on different data sizes from the Facial Recognition Technology (FERET database.

  5. Modulation of pathogen recognition by autophagy

    Directory of Open Access Journals (Sweden)

    Ji Eun eOh

    2012-03-01

    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.

  6. Fast parallel recognition of LR language suffixes

    NARCIS (Netherlands)

    Bertsch, E; Nederhof, M.J.

    2004-01-01

    It is shown that suffix recognition for deterministic context-free languages can be done on a PRAM multi-processor within the upper complexity bounds of the graph reachability problem. (C) 2004 Elsevier B.V. All rights reserved.

  7. Novel Techniques for Dialectal Arabic Speech Recognition

    CERN Document Server

    Elmahdy, Mohamed; Minker, Wolfgang

    2012-01-01

    Novel Techniques for Dialectal Arabic Speech describes approaches to improve automatic speech recognition for dialectal Arabic. Since speech resources for dialectal Arabic speech recognition are very sparse, the authors describe how existing Modern Standard Arabic (MSA) speech data can be applied to dialectal Arabic speech recognition, while assuming that MSA is always a second language for all Arabic speakers. In this book, Egyptian Colloquial Arabic (ECA) has been chosen as a typical Arabic dialect. ECA is the first ranked Arabic dialect in terms of number of speakers, and a high quality ECA speech corpus with accurate phonetic transcription has been collected. MSA acoustic models were trained using news broadcast speech. In order to cross-lingually use MSA in dialectal Arabic speech recognition, the authors have normalized the phoneme sets for MSA and ECA. After this normalization, they have applied state-of-the-art acoustic model adaptation techniques like Maximum Likelihood Linear Regression (MLLR) and M...

  8. Real object recognition using moment invariants

    Indian Academy of Sciences (India)

    Muharrem Mercimek; Kayhan Gulez; Tarik Veli Mumcu

    2005-12-01

    Moments and functions of moments have been extensively employed as invariant global features of images in pattern recognition. In this study, a flexible recognition system that can compute the good features for high classification of 3-D real objects is investigated. For object recognition, regardless of orientation, size and position, feature vectors are computed with the help of nonlinear moment invariant functions. Representations of objects using two-dimensional images that are taken from different angles of view are the main features leading us to our objective. After efficient feature extraction, the main focus of this study, the recognition performance of classifiers in conjunction with moment–based feature sets, is introduced.

  9. CERN receives prestigious Milestone recognition from IEEE

    CERN Multimedia

    2005-01-01

    At a ceremony at CERN, Mr W. Cleon Anderson, President of the Institute of Electrical and Electronics Engineers (IEEE) formally a Milestone plaque in recognition of the invention of electronic particle detectors at CERN

  10. Kannada Character Recognition System A Review

    CERN Document Server

    Indira, K

    2010-01-01

    Intensive research has been done on optical character recognition ocr and a large number of articles have been published on this topic during the last few decades. Many commercial OCR systems are now available in the market, but most of these systems work for Roman, Chinese, Japanese and Arabic characters. There are no sufficient number of works on Indian language character recognition especially Kannada script among 12 major scripts in India. This paper presents a review of existing work on printed Kannada script and their results. The characteristics of Kannada script and Kannada Character Recognition System kcr are discussed in detail. Finally fusion at the classifier level is proposed to increase the recognition accuracy.

  11. HMM based Korean Named Entity Recognition

    Directory of Open Access Journals (Sweden)

    Yi-Gyu Hwang

    2003-02-01

    Full Text Available In this paper, we present a named entity recognition model for Korean Language. Named entity recognition is an essential and important process of Question Answering and Information Extraction system. This paper proposes a HMM based named entity recognition using compound word construction principles. In Korean, above 60% of NE (Named-Entity is a compound word. This compound word may be consisted of proper noun, common noun, or bound noun, etc. There is an intercontextual relationship among nouns which consists NE. NE and surrounding words of NE have a contextual relationship. For considering these relationships, we classified nouns into 4 word classes (Independent Entity, Constituent Entity, Adjacent Entity, Not an Entity. With this classification, our system gets contextual and lexical information by stochastic based machine leaning method from a NE labeled training data. Experimental result shows that this approach is better approach than rulebased in the Korean named-entity recognition.

  12. Viral recognition by the innate immune system: the role of pattern recognition receptors

    OpenAIRE

    Silvia Torres Pedraza; Juan Guillermo Betancur; Silvio Urcuqui-Inchima

    2011-01-01

    Pattern recognition receptors are the main sensors of the innate immune response. Their function is to recognize pathogen-associated molecular patterns, which are molecules essential for the survival of microbial pathogens, but are not produced by the host. The recognition of pathogen-associated molecular patterns by pattern recognition receptors leads to the expression of cytokines, chemokines, and co-stimulatory molecules that eliminate pathogens, such as viruses, for the activation of anti...

  13. Fingerprint recognition using standardized fingerprint model

    OpenAIRE

    Le Hoang Thai; Ha Nhat Tam

    2011-01-01

    Fingerprint recognition is one of most popular and accuracy Biometric technologies. Nowadays, it is used in many real applications. However, recognizing fingerprints in poor quality images is still a very complex problem. In recent years, many algorithms, models are given to improve the accuracy of recognition system. This paper discusses on the standardized fingerprint model which is used to synthesize the template of fingerprints. In this model, after pre-processing step, we find the transf...

  14. Phoneme vs Grapheme Based Automatic Speech Recognition

    OpenAIRE

    Magimai.-Doss, Mathew; Dines, John; Bourlard, Hervé; Hermansky, Hynek

    2004-01-01

    In recent literature, different approaches have been proposed to use graphemes as subword units with implicit source of phoneme information for automatic speech recognition. The major advantage of using graphemes as subword units is that the definition of lexicon is easy. In previous studies, results comparable to phoneme-based automatic speech recognition systems have been reported using context-independent graphemes or context-dependent graphemes with decision trees. In this paper, we study...

  15. Autonomous Environment Recognition by Robotic Manipulators

    OpenAIRE

    Senda, Kei; Okano, Yuzo

    2001-01-01

    This paper discusses methods of autonomus environment recognition and action by a robotic manipulator working with dynamic interaction to the enviroment, e.g., assembling. A method automatically recognizes the contacting situation with the work site from the sensor outputs and the robotic manipulator motion. The autonomous recognition then discriminates the constraint conditions at manopulator hand using the self-organizing map that is a kind of unsupervisedlearning of neural networks. The di...

  16. Facial Expression Recognition Using SVM Classifier

    OpenAIRE

    2015-01-01

    Facial feature tracking and facial actions recognition from image sequence attracted great attention in computer vision field. Computational facial expression analysis is a challenging research topic in computer vision. It is required by many applications such as human-computer interaction, computer graphic animation and automatic facial expression recognition. In recent years, plenty of computer vision techniques have been developed to track or recognize the facial activities in three levels...

  17. A New Database for Speaker Recognition

    DEFF Research Database (Denmark)

    Feng, Ling; Hansen, Lars Kai

    2005-01-01

    In this paper we discuss properties of speech databases used for speaker recognition research and evaluation, and we characterize some popular standard databases. The paper presents a new database called ELSDSR dedicated to speaker recognition applications. The main characteristics of this database...... are: English spoken by non-native speakers, a single session of sentence reading and relatively extensive speech samples suitable for learning person specific speech characteristics....

  18. Enhanced Secure Algorithm for Fingerprint Recognition

    OpenAIRE

    Saleh, Amira Mohammad Abdel-Mawgoud

    2014-01-01

    Fingerprint recognition requires a minimal effort from the user, does not capture other information than strictly necessary for the recognition process, and provides relatively good performance. A critical step in fingerprint identification system is thinning of the input fingerprint image. The performance of a minutiae extraction algorithm relies heavily on the quality of the thinning algorithm. So, a fast fingerprint thinning algorithm is proposed. The algorithm works directly on the gray-s...

  19. Recognition Inventories in Governmental Sector Accounting

    OpenAIRE

    Nataliya Pryadka

    2013-01-01

    The Study covers the research of conditions for recognition of inventories in the governmental sector accounting. The comparative analysis has been performed as to the inventories recognition criteria provided by the National Accounting Provisions (Standards) 123 in the public sector - 'Inventories', Accounting Provision (Standard) 9 - 'Inventories', International Accounting Standard 16 - 'Inventories' in the public sector. It has been found that the common characteristic, in accordance with ...

  20. Neural-Network Object-Recognition Program

    Science.gov (United States)

    Spirkovska, L.; Reid, M. B.

    1993-01-01

    HONTIOR computer program implements third-order neural network exhibiting invariance under translation, change of scale, and in-plane rotation. Invariance incorporated directly into architecture of network. Only one view of each object needed to train network for two-dimensional-translation-invariant recognition of object. Also used for three-dimensional-transformation-invariant recognition by training network on only set of out-of-plane rotated views. Written in C language.

  1. Progressive Wavelet Correlation for Image Recognition

    OpenAIRE

    Stojanovic, Igor

    2013-01-01

    An algorithm for recognition and retrieval of image from image collection is developed. Basis of the algorithm is the progressive wavelet correlation. The final result is the recognition and retrieval of the wanted image, if it is in the image collection. Instructions for the choice of correlation threshold value for obtaining desired results are defined. The areas where the algorithm can be applied are also discussed. To increase efficiency is presented two phases solution. The first phase u...

  2. Foreign Language Analysis and Recognition (FLARE) Progress

    Science.gov (United States)

    2015-02-01

    was considered optimal. The initial phase allows for an image to be uploaded into the Haystack system, but the second stage is prompted by a command...AFRL-RH-WP-TR-2015-0007 FOREIGN LANGUAGE ANALYSIS AND RECOGNITION (FLARE) PROGRESS Brian M. Ore Stephen A. Thorn David M...October 2012 – 30 November 2014 4. TITLE AND SUBTITLE Foreign Language Analysis and Recognition (FLARe) Progress 5a. CONTRACT NUMBER FA8650

  3. Pattern recognition using linguistic fuzzy logic predictors

    Science.gov (United States)

    Habiballa, Hashim

    2016-06-01

    The problem of pattern recognition has been solved with numerous methods in the Artificial Intelligence field. We present an unconventional method based on Lingustic Fuzzy Logic Forecaster which is primarily used for the task of time series analysis and prediction through logical deduction wtih linguistic variables. This method should be used not only to the time series prediction itself, but also for recognition of patterns in a signal with seasonal component.

  4. DWT BASED HMM FOR FACE RECOGNITION

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    A novel Discrete Wavelet Transform (DWT) based Hidden Markov Module (HMM) for face recognition is presented in this letter. To improve the accuracy of HMM based face recognition algorithm, DWT is used to replace Discrete Cosine Transform (DCT) for observation sequence extraction. Extensive experiments are conducted on two public databases and the results show that the proposed method can improve the accuracy significantly, especially when the face database is large and only few training images are available.

  5. Finite Memory Model for Haptic Recognition

    Science.gov (United States)

    1991-12-01

    Slot 4 bu f fer s hort- term storel Slot N Long- ’erm store The model of memory proposed by Atkinson and Shiffrin . Primary memory here is as rehearsal...7 NAVAL POSTGRADUATE SCHOOL Monterey, Califormia AD-A245 342 THESIS Finite Memory Model for Haptic Recognition by Philip G. Beieri December 1991...ELEMEN1 No.) NO. No. ACCESSION NO. I1. TITLE (include Securitn Classification) FINITE MEMORY MODEL FOR HAPTIC RECOGNITION’ 12. PERSONALEAUTHOR(S) Philip

  6. Geometric hashing and object recognition

    Science.gov (United States)

    Stiller, Peter F.; Huber, Birkett

    1999-09-01

    We discuss a new geometric hashing method for searching large databases of 2D images (or 3D objects) to match a query built from geometric information presented by a single 3D object (or single 2D image). The goal is to rapidly determine a small subset of the images that potentially contain a view of the given object (or a small set of objects that potentially match the item in the image). Since this must be accomplished independent of the pose of the object, the objects and images, which are characterized by configurations of geometric features such as points, lines and/or conics, must be treated using a viewpoint invariant formulation. We are therefore forced to characterize these configurations in terms of their 3D and 2D geometric invariants. The crucial relationship between the 3D geometry and its 'residual' in 2D is expressible as a correspondence (in the sense of algebraic geometry). Computing a set of generating equations for the ideal of this correspondence gives a complete characterization of the view of independent relationships between an object and all of its possible images. Once a set of generators is in hand, it can be used to devise efficient recognition algorithms and to give an efficient geometric hashing scheme. This requires exploiting the form and symmetry of the equations. The result is a multidimensional access scheme whose efficiency we examine. Several potential directions for improving this scheme are also discussed. Finally, in a brief appendix, we discuss an alternative approach to invariants for generalized perspective that replaces the standard invariants by a subvariety of a Grassmannian. The advantage of this is that one can circumvent many annoying general position assumptions and arrive at invariant equations (in the Plucker coordinates) that are more numerically robust in applications.

  7. Object recognition by artificial cortical maps.

    Science.gov (United States)

    Plebe, Alessio; Domenella, Rosaria Grazia

    2007-09-01

    Object recognition is one of the most important functions of the human visual system, yet one of the least understood, this despite the fact that vision is certainly the most studied function of the brain. We understand relatively well how several processes in the cortical visual areas that support recognition capabilities take place, such as orientation discrimination and color constancy. This paper proposes a model of the development of object recognition capability, based on two main theoretical principles. The first is that recognition does not imply any sort of geometrical reconstruction, it is instead fully driven by the two dimensional view captured by the retina. The second assumption is that all the processing functions involved in recognition are not genetically determined or hardwired in neural circuits, but are the result of interactions between epigenetic influences and basic neural plasticity mechanisms. The model is organized in modules roughly related to the main visual biological areas, and is implemented mainly using the LISSOM architecture, a recent neural self-organizing map model that simulates the effects of intercortical lateral connections. This paper shows how recognition capabilities, similar to those found in brain ventral visual areas, can develop spontaneously by exposure to natural images in an artificial cortical model.

  8. Oxytocin improves emotion recognition for older males.

    Science.gov (United States)

    Campbell, Anna; Ruffman, Ted; Murray, Janice E; Glue, Paul

    2014-10-01

    Older adults (≥60 years) perform worse than young adults (18-30 years) when recognizing facial expressions of emotion. The hypothesized cause of these changes might be declines in neurotransmitters that could affect information processing within the brain. In the present study, we examined the neuropeptide oxytocin that functions to increase neurotransmission. Research suggests that oxytocin benefits the emotion recognition of less socially able individuals. Men tend to have lower levels of oxytocin and older men tend to have worse emotion recognition than older women; therefore, there is reason to think that older men will be particularly likely to benefit from oxytocin. We examined this idea using a double-blind design, testing 68 older and 68 young adults randomly allocated to receive oxytocin nasal spray (20 international units) or placebo. Forty-five minutes afterward they completed an emotion recognition task assessing labeling accuracy for angry, disgusted, fearful, happy, neutral, and sad faces. Older males receiving oxytocin showed improved emotion recognition relative to those taking placebo. No differences were found for older females or young adults. We hypothesize that oxytocin facilitates emotion recognition by improving neurotransmission in the group with the worst emotion recognition.

  9. Chinese character recognition :history ,status and prospects

    Institute of Scientific and Technical Information of China (English)

    DAI Ruwei; LIU Chenglin; XIAO Baihua

    2007-01-01

    Chinese character recognition (CCR) is an important branch of pattern recognition.It was considered as an extremely difficult problem due to the very large number of categories,complicated structures,similarity between characters,and the variability of fonts or writing styles.Because of its unique technical challenges and great social needs,the last four decades witnessed the intensive research in this field and a rapid increase of successful applications.However,higher recognition performance is continuously needed to improve the existing applications and to exploit new applications.This paper first provides an overview of Chinese character recognition and the properties of Chinese characters.Some important methods and successful results in the history of Chinese character recognition are then summarized.As for classification methods,this article pays special attention to the syntactic-semantic approach for online Chinese character recognition,as well as the metasynthesis approach for discipline crossing.Finally,the remaining problems and the possible solutions are discussed.

  10. A Survey of Protein Fold Recognition Algorithms

    Directory of Open Access Journals (Sweden)

    M. S. Abual-Rub

    2008-01-01

    Full Text Available Problem statement: Predicting the tertiary structure of proteins from their linear sequence is really a big challenge in biology. This challenge is related to the fact that the traditional computational methods are not powerful enough to search for the correct structure in the huge conformational space. This inadequate capability of the computational methods, however, is a major obstacle in facing this problem. Trying to solve the problem of the protein fold recognition, most of the researchers have examined the use of the protein threading technique. This problem is known as NP-hard; researchers have used various methods such as neural networks, Monte Carlo, support vector machine and genetic algorithms to solve it. Some researchers tried the use of the parallel evolutionary methods for protein fold recognition but it is less well known. Approach: We reviewed various algorithms that have been developed for protein structure prediction by threading and fold recognition. Moreover, we provided a survey of parallel evolutionary methods for protein fold recognition. Results: The findings of this survey showed that evolutionary methods can be used to resolve the protein fold recognition problem. Conclusion: There are two aspects of protein fold recognition problem: First is the computational difficulty and second is that current energy functions are still not accurate enough to calculate the free energy of a given conformation.

  11. An Introduction to Face Recognition Technology

    Directory of Open Access Journals (Sweden)

    Shang-Hung Lin

    2000-01-01

    Full Text Available Recently face recognition is attracting much attention in the society of network multimedia information access.  Areas such as network security, content indexing and retrieval, and video compression benefits from face recognition technology because "people" are the center of attention in a lot of video.  Network access control via face recognition not only makes hackers virtually impossible to steal one's "password", but also increases the user-friendliness in human-computer interaction.  Indexing and/or retrieving video data based on the appearances of particular persons will be useful for users such as news reporters, political scientists, and moviegoers.  For the applications of videophone and teleconferencing, the assistance of face recognition also provides a more efficient coding scheme.  In this paper, we give an introductory course of this new information processing technology.  The paper shows the readers the generic framework for the face recognition system, and the variants that are frequently encountered by the face recognizer.  Several famous face recognition algorithms, such as eigenfaces and neural networks, will also be explained.

  12. Age Dependent Face Recognition using Eigenface

    Directory of Open Access Journals (Sweden)

    Hlaing Htake Khaung Tin

    2013-10-01

    Full Text Available Face recognition is the most successful form of human surveillance. Face recognition technology, is being used to improve human efficiency when recognition faces, is one of the fastest growing fields in the biometric industry. In the first stage, the age is classified into eleven categories which distinguish the person oldness in terms of age. In the second stage of the process is face recognition based on the predicted age. Age prediction has considerable potential applications in human computer interaction and multimedia communication. In this paper proposes an Eigen based age estimation algorithm for estimate an image from the database. Eigenface has proven to be a useful and robust cue for age prediction, age simulation, face recognition, localization and tracking. The scheme is based on an information theory approach that decomposes face images into a small set of characteristic feature images called eigenfaces, which may be thought of as the principal components of the initial training set of face images. The eigenface approach used in this scheme has advantages over other face recognition methods in its speed, simplicity, learning capability and robustness to small changes in the face image.

  13. Multispectral Palmprint Recognition Using a Quaternion Matrix

    Directory of Open Access Journals (Sweden)

    Yafeng Li

    2012-04-01

    Full Text Available Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR illuminations were represented by a quaternion matrix, then principal component analysis (PCA and discrete wavelet transform (DWT were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%.

  14. Implicit Recognition Based on Lateralized Perceptual Fluency

    Directory of Open Access Journals (Sweden)

    Iliana M. Vargas

    2012-02-01

    Full Text Available In some circumstances, accurate recognition of repeated images in an explicit memory test is driven by implicit memory. We propose that this “implicit recognition” results from perceptual fluency that influences responding without awareness of memory retrieval. Here we examined whether recognition would vary if images appeared in the same or different visual hemifield during learning and testing. Kaleidoscope images were briefly presented left or right of fixation during divided-attention encoding. Presentation in the same visual hemifield at test produced higher recognition accuracy than presentation in the opposite visual hemifield, but only for guess responses. These correct guesses likely reflect a contribution from implicit recognition, given that when the stimulated visual hemifield was the same at study and test, recognition accuracy was higher for guess responses than for responses with any level of confidence. The dramatic difference in guessing accuracy as a function of lateralized perceptual overlap between study and test suggests that implicit recognition arises from memory storage in visual cortical networks that mediate repetition-induced fluency increments.

  15. The hierarchical brain network for face recognition.

    Science.gov (United States)

    Zhen, Zonglei; Fang, Huizhen; Liu, Jia

    2013-01-01

    Numerous functional magnetic resonance imaging (fMRI) studies have identified multiple cortical regions that are involved in face processing in the human brain. However, few studies have characterized the face-processing network as a functioning whole. In this study, we used fMRI to identify face-selective regions in the entire brain and then explore the hierarchical structure of the face-processing network by analyzing functional connectivity among these regions. We identified twenty-five regions mainly in the occipital, temporal and frontal cortex that showed a reliable response selective to faces (versus objects) across participants and across scan sessions. Furthermore, these regions were clustered into three relatively independent sub-networks in a face-recognition task on the basis of the strength of functional connectivity among them. The functionality of the sub-networks likely corresponds to the recognition of individual identity, retrieval of semantic knowledge and representation of emotional information. Interestingly, when the task was switched to object recognition from face recognition, the functional connectivity between the inferior occipital gyrus and the rest of the face-selective regions were significantly reduced, suggesting that this region may serve as an entry node in the face-processing network. In sum, our study provides empirical evidence for cognitive and neural models of face recognition and helps elucidate the neural mechanisms underlying face recognition at the network level.

  16. Efficient Recognition of Human Faces from Video in Particle Filter

    Institute of Scientific and Technical Information of China (English)

    2006-01-01

    Face recognition from video requires dealing with uncertainty both in tracking and recognition. This paper proposed an effective method for face recognition from video. In order to realize simultaneous tracking and recognition, fisherface-based recognition is combined with tracking into one model. This model is then embedded into particle filter to perform face recognition from video. In order to improve the robustness of tracking, an expectation maximization (EM) algorithm was adopted to update the appearance model. The experimental results show that the proposed method can perform well in tracking and recognition even in poor conditions such as occlusion and remarkable change in lighting.

  17. Sugar recognition by human galactokinase

    Directory of Open Access Journals (Sweden)

    Timson David J

    2003-11-01

    Full Text Available Abstract Background Galactokinase catalyses the first committed step of galactose catabolism in which the sugar is phosphorylated at the expense of MgATP. Recent structural studies suggest that the enzyme makes several contacts with galactose – five side chain and two main chain hydrogen bonds. Furthermore, it has been suggested that inhibition of galactokinase may help sufferers of the genetic disease classical galactosemia which is caused by defects in another enzyme of the pathway galactose-1-phosphate uridyl transferase. Galactokinases from different sources have a range of substrate specificities and a diversity of kinetic mechanisms. Therefore only studies on the human enzyme are likely to be of value in the design of therapeutically useful inhibitors. Results Using recombinant human galactokinase expressed in and purified from E. coli we have investigated the sugar specificity of the enzyme and the kinetic consequences of mutating residues in the sugar-binding site in order to improve our understanding of substrate recognition by this enzyme. D-galactose and 2-deoxy-D-galactose are substrates for the enzyme, but N-acetyl-D-galactosamine, L-arabinose, D-fucose and D-glucose are all not phosphorylated. Mutation of glutamate-43 (which forms a hydrogen bond to the hydroxyl group attached to carbon 6 of galactose to alanine results in only minor changes in the kinetic parameters of the enzyme. Mutation of this residue to glycine causes a ten-fold drop in the turnover number. In contrast, mutation of histidine 44 to either alanine or isoleucine results in insoluble protein following expression in E. coli. Alteration of the residue that makes hydrogen bonds to the hydroxyl attached to carbons 3 and 4 (aspartate 46 results in an enzyme that although soluble is essentially inactive. Conclusions The enzyme is tolerant to small changes at position 2 of the sugar ring, but not at positions 4 and 6. The results from site directed mutagenesis could

  18. Novel acoustic features for speech emotion recognition

    Institute of Scientific and Technical Information of China (English)

    ROH; Yong-Wan; KIM; Dong-Ju; LEE; Woo-Seok; HONG; Kwang-Seok

    2009-01-01

    This paper focuses on acoustic features that effectively improve the recognition of emotion in human speech.The novel features in this paper are based on spectral-based entropy parameters such as fast Fourier transform(FFT) spectral entropy,delta FFT spectral entropy,Mel-frequency filter bank(MFB) spectral entropy,and Delta MFB spectral entropy.Spectral-based entropy features are simple.They reflect frequency characteristic and changing characteristic in frequency of speech.We implement an emotion rejection module using the probability distribution of recognized-scores and rejected-scores.This reduces the false recognition rate to improve overall performance.Recognized-scores and rejected-scores refer to probabilities of recognized and rejected emotion recognition results,respectively.These scores are first obtained from a pattern recognition procedure.The pattern recognition phase uses the Gaussian mixture model(GMM).We classify the four emotional states as anger,sadness,happiness and neutrality.The proposed method is evaluated using 45 sentences in each emotion for 30 subjects,15 males and 15 females.Experimental results show that the proposed method is superior to the existing emotion recognition methods based on GMM using energy,Zero Crossing Rate(ZCR),linear prediction coefficient(LPC),and pitch parameters.We demonstrate the effectiveness of the proposed approach.One of the proposed features,combined MFB and delta MFB spectral entropy improves performance approximately 10% compared to the existing feature parameters for speech emotion recognition methods.We demonstrate a 4% performance improvement in the applied emotion rejection with low confidence score.

  19. Contextual modulation of biases in face recognition.

    Directory of Open Access Journals (Sweden)

    Fatima Maria Felisberti

    Full Text Available BACKGROUND: The ability to recognize the faces of potential cooperators and cheaters is fundamental to social exchanges, given that cooperation for mutual benefit is expected. Studies addressing biases in face recognition have so far proved inconclusive, with reports of biases towards faces of cheaters, biases towards faces of cooperators, or no biases at all. This study attempts to uncover possible causes underlying such discrepancies. METHODOLOGY AND FINDINGS: Four experiments were designed to investigate biases in face recognition during social exchanges when behavioral descriptors (prosocial, antisocial or neutral embedded in different scenarios were tagged to faces during memorization. Face recognition, measured as accuracy and response latency, was tested with modified yes-no, forced-choice and recall tasks (N = 174. An enhanced recognition of faces tagged with prosocial descriptors was observed when the encoding scenario involved financial transactions and the rules of the social contract were not explicit (experiments 1 and 2. Such bias was eliminated or attenuated by making participants explicitly aware of "cooperative", "cheating" and "neutral/indifferent" behaviors via a pre-test questionnaire and then adding such tags to behavioral descriptors (experiment 3. Further, in a social judgment scenario with descriptors of salient moral behaviors, recognition of antisocial and prosocial faces was similar, but significantly better than neutral faces (experiment 4. CONCLUSION: The results highlight the relevance of descriptors and scenarios of social exchange in face recognition, when the frequency of prosocial and antisocial individuals in a group is similar. Recognition biases towards prosocial faces emerged when descriptors did not state the rules of a social contract or the moral status of a behavior, and they point to the existence of broad and flexible cognitive abilities finely tuned to minor changes in social context.

  20. Effects of Recognition on Subsequent Recall: Comments on "Determinants of Recognition and Recall: Accessibility and Generation"

    Science.gov (United States)

    Broadbent, Donald E.; Broadbent, Margaret H. P.

    1977-01-01

    Attempts have been made by Rabinowitz, Mandler, and Patterson (AA 527 084) to show that both recall and recognition involve the accessibility of individual words. Their recall tests preceded recognition tests, or vice versa, thus contaminating each other; a fresh experiment is presented to confirm that this is so. (Editor)

  1. A motivational determinant of facial emotion recognition: regulatory focus affects recognition of emotions in faces.

    Science.gov (United States)

    Sassenrath, Claudia; Sassenberg, Kai; Ray, Devin G; Scheiter, Katharina; Jarodzka, Halszka

    2014-01-01

    Two studies examined an unexplored motivational determinant of facial emotion recognition: observer regulatory focus. It was predicted that a promotion focus would enhance facial emotion recognition relative to a prevention focus because the attentional strategies associated with promotion focus enhance performance on well-learned or innate tasks - such as facial emotion recognition. In Study 1, a promotion or a prevention focus was experimentally induced and better facial emotion recognition was observed in a promotion focus compared to a prevention focus. In Study 2, individual differences in chronic regulatory focus were assessed and attention allocation was measured using eye tracking during the facial emotion recognition task. Results indicated that the positive relation between a promotion focus and facial emotion recognition is mediated by shorter fixation duration on the face which reflects a pattern of attention allocation matched to the eager strategy in a promotion focus (i.e., striving to make hits). A prevention focus did not have an impact neither on perceptual processing nor on facial emotion recognition. Taken together, these findings demonstrate important mechanisms and consequences of observer motivational orientation for facial emotion recognition.

  2. Meta-Recognition: The Theory and Practice of Recognition Score Analysis.

    Science.gov (United States)

    Scheirer, Walter J; Rocha, A; Micheals, Ross J; Boult, Terrance E

    2011-08-01

    In this paper, we define meta-recognition, a performance prediction method for recognition algorithms, and examine the theoretical basis for its postrecognition score analysis form through the use of the statistical extreme value theory (EVT). The ability to predict the performance of a recognition system based on its outputs for each match instance is desirable for a number of important reasons, including automatic threshold selection for determining matches and nonmatches, and automatic algorithm selection or weighting for multi-algorithm fusion. The emerging body of literature on postrecognition score analysis has been largely constrained to biometrics, where the analysis has been shown to successfully complement or replace image quality metrics as a predictor. We develop a new statistical predictor based upon the Weibull distribution, which produces accurate results on a per instance recognition basis across different recognition problems. Experimental results are provided for two different face recognition algorithms, a fingerprint recognition algorithm, a SIFT-based object recognition system, and a content-based image retrieval system.

  3. What Types of Visual Recognition Tasks Are Mediated by the Neural Subsystem that Subserves Face Recognition?

    Science.gov (United States)

    Brooks, Brian E.; Cooper, Eric E.

    2006-01-01

    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…

  4. ALPHABET RECOGNITION OF AMERICAN SIGN LANGUAGE: A HAND GESTURE RECOGNITION APPROACH USING SIFT ALGORITHM

    Directory of Open Access Journals (Sweden)

    Nachamai. M

    2013-01-01

    Full Text Available This paper is a sincere attempt to recognize english alphabets as part of hand gesture recognition, using the SIFT algorithm. The novelty of this approach is, it is a space, size, illumination and rotation invariant approach. The approach has evolved to work well with both the standard American Sign Language (ASL database and home-made database. The problem of alphabet recognition may seem to sound small but the intricacies involved in it cannot be solved using a single algorithm. Hand gesture recognition is a complicated task. A one stop solution is still not evolved for any recognition process. This paper has tried to approach this in a simple but efficient manner using the basic SIFT algorithm for recognition. The efficacy of the approach is proved well through the results obtained, invariably on both the datasets.

  5. Alphabet Recognition of American Sign Language : A Hand Gesture Recognition Approach Using Sift Algorithm

    Directory of Open Access Journals (Sweden)

    Nachamai. M

    2013-02-01

    Full Text Available This paper is a sincere attempt to recognize english alphabets as part of hand gesture recognition, usingthe SIFT algorithm. The novelty of this approach is, it is a space, size, illumination and rotation invariantapproach. The approach has evolved to work well with both the standard American Sign Language (ASLdatabase and home-made database. The problem of alphabet recognition may seem to sound small but theintricacies involved in it cannot be solved using a single algorithm. Hand gesture recognition is acomplicated task. A one stop solution is still not evolved for any recognition process. This paper has triedto approach this in a simple but efficient manner using the basic SIFT algorithm for recognition. Theefficacy of the approach is proved well through the results obtained, invariably on both the datasets.

  6. Practical vision based degraded text recognition system

    Science.gov (United States)

    Mohammad, Khader; Agaian, Sos; Saleh, Hani

    2011-02-01

    Rapid growth and progress in the medical, industrial, security and technology fields means more and more consideration for the use of camera based optical character recognition (OCR) Applying OCR to scanned documents is quite mature, and there are many commercial and research products available on this topic. These products achieve acceptable recognition accuracy and reasonable processing times especially with trained software, and constrained text characteristics. Even though the application space for OCR is huge, it is quite challenging to design a single system that is capable of performing automatic OCR for text embedded in an image irrespective of the application. Challenges for OCR systems include; images are taken under natural real world conditions, Surface curvature, text orientation, font, size, lighting conditions, and noise. These and many other conditions make it extremely difficult to achieve reasonable character recognition. Performance for conventional OCR systems drops dramatically as the degradation level of the text image quality increases. In this paper, a new recognition method is proposed to recognize solid or dotted line degraded characters. The degraded text string is localized and segmented using a new algorithm. The new method was implemented and tested using a development framework system that is capable of performing OCR on camera captured images. The framework allows parameter tuning of the image-processing algorithm based on a training set of camera-captured text images. Novel methods were used for enhancement, text localization and the segmentation algorithm which enables building a custom system that is capable of performing automatic OCR which can be used for different applications. The developed framework system includes: new image enhancement, filtering, and segmentation techniques which enabled higher recognition accuracies, faster processing time, and lower energy consumption, compared with the best state of the art published

  7. Portable Facial Recognition Jukebox Using Fisherfaces (Frj

    Directory of Open Access Journals (Sweden)

    Richard Mo

    2016-03-01

    Full Text Available A portable real-time facial recognition system that is able to play personalized music based on the identified person’s preferences was developed. The system is called Portable Facial Recognition Jukebox Using Fisherfaces (FRJ. Raspberry Pi was used as the hardware platform for its relatively low cost and ease of use. This system uses the OpenCV open source library to implement the computer vision Fisherfaces facial recognition algorithms, and uses the Simple DirectMedia Layer (SDL library for playing the sound files. FRJ is cross-platform and can run on both Windows and Linux operating systems. The source code was written in C++. The accuracy of the recognition program can reach up to 90% under controlled lighting and distance conditions. The user is able to train up to 6 different people (as many as will fit in the GUI. When implemented on a Raspberry Pi, the system is able to go from image capture to facial recognition in an average time of 200ms.

  8. AN ILLUMINATION INVARIANT TEXTURE BASED FACE RECOGNITION

    Directory of Open Access Journals (Sweden)

    K. Meena

    2013-11-01

    Full Text Available Automatic face recognition remains an interesting but challenging computer vision open problem. Poor illumination is considered as one of the major issue, since illumination changes cause large variation in the facial features. To resolve this, illumination normalization preprocessing techniques are employed in this paper to enhance the face recognition rate. The methods such as Histogram Equalization (HE, Gamma Intensity Correction (GIC, Normalization chain and Modified Homomorphic Filtering (MHF are used for preprocessing. Owing to great success, the texture features are commonly used for face recognition. But these features are severely affected by lighting changes. Hence texture based models Local Binary Pattern (LBP, Local Derivative Pattern (LDP, Local Texture Pattern (LTP and Local Tetra Patterns (LTrPs are experimented under different lighting conditions. In this paper, illumination invariant face recognition technique is developed based on the fusion of illumination preprocessing with local texture descriptors. The performance has been evaluated using YALE B and CMU-PIE databases containing more than 1500 images. The results demonstrate that MHF based normalization gives significant improvement in recognition rate for the face images with large illumination conditions.

  9. Segmentation and Recognition of Handwritten Numeric Chains

    Directory of Open Access Journals (Sweden)

    Salim Ouchtati

    2007-01-01

    Full Text Available Automatic reading of numeric chains has been attempted in several application areas such as bank cheque processing, postal code recognition and form processing. Such applications have been very popular in handwriting recognition research, due to the possibility to reduce considerably the manual effort involved in these tasks. In this study we propose an off line system for the recognition of the handwritten numeric chains. Firstly, study was based mainly on the evaluation of neural network performances, trained with the gradient back propagation algorithm. Used parameters to form the input vector of the neural network are extracted on the binary images of the digits by several methods: distribution sequence, Barr features and centred moments of different projections and profiles. Secondly, study was extented for the reading of the handwritten numeric chains constituted of a variable number of digits. Vertical projection was used to segment the numeric chain at isolated digits and every digit (or segment was presented separately to the entry of the system achieved in the first part (recognition system of the isolated handwritten digits. The performances of the proposed system for the used database attain a recognition rate equal to 91.3%.

  10. Gesture recognition by instantaneous surface EMG images

    Science.gov (United States)

    Geng, Weidong; Du, Yu; Jin, Wenguang; Wei, Wentao; Hu, Yu; Li, Jiajun

    2016-01-01

    Gesture recognition in non-intrusive muscle-computer interfaces is usually based on windowed descriptive and discriminatory surface electromyography (sEMG) features because the recorded amplitude of a myoelectric signal may rapidly fluctuate between voltages above and below zero. Here, we present that the patterns inside the instantaneous values of high-density sEMG enables gesture recognition to be performed merely with sEMG signals at a specific instant. We introduce the concept of an sEMG image spatially composed from high-density sEMG and verify our findings from a computational perspective with experiments on gesture recognition based on sEMG images with a classification scheme of a deep convolutional network. Without any windowed features, the resultant recognition accuracy of an 8-gesture within-subject test reached 89.3% on a single frame of sEMG image and reached 99.0% using simple majority voting over 40 frames with a 1,000 Hz sampling rate. Experiments on the recognition of 52 gestures of NinaPro database and 27 gestures of CSL-HDEMG database also validated that our approach outperforms state-of-the-arts methods. Our findings are a starting point for the development of more fluid and natural muscle-computer interfaces with very little observational latency. For example, active prostheses and exoskeletons based on high-density electrodes could be controlled with instantaneous responses. PMID:27845347

  11. Automatic TLI recognition system, general description

    Energy Technology Data Exchange (ETDEWEB)

    Lassahn, G.D.

    1997-02-01

    This report is a general description of an automatic target recognition system developed at the Idaho National Engineering Laboratory for the Department of Energy. A user`s manual is a separate volume, Automatic TLI Recognition System, User`s Guide, and a programmer`s manual is Automatic TLI Recognition System, Programmer`s Guide. This system was designed as an automatic target recognition system for fast screening of large amounts of multi-sensor image data, based on low-cost parallel processors. This system naturally incorporates image data fusion, and it gives uncertainty estimates. It is relatively low cost, compact, and transportable. The software is easily enhanced to expand the system`s capabilities, and the hardware is easily expandable to increase the system`s speed. In addition to its primary function as a trainable target recognition system, this is also a versatile, general-purpose tool for image manipulation and analysis, which can be either keyboard-driven or script-driven. This report includes descriptions of three variants of the computer hardware, a description of the mathematical basis if the training process, and a description with examples of the system capabilities.

  12. Pattern Activation/Recognition Theory of Mind

    Directory of Open Access Journals (Sweden)

    Bertrand edu Castel

    2015-07-01

    Full Text Available In his 2012 book How to Create a Mind, Ray Kurzweil defines a Pattern Recognition Theory of Mind that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call Pattern Activation/Recognition Theory of Mind. While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

  13. Gesture recognition by instantaneous surface EMG images.

    Science.gov (United States)

    Geng, Weidong; Du, Yu; Jin, Wenguang; Wei, Wentao; Hu, Yu; Li, Jiajun

    2016-11-15

    Gesture recognition in non-intrusive muscle-computer interfaces is usually based on windowed descriptive and discriminatory surface electromyography (sEMG) features because the recorded amplitude of a myoelectric signal may rapidly fluctuate between voltages above and below zero. Here, we present that the patterns inside the instantaneous values of high-density sEMG enables gesture recognition to be performed merely with sEMG signals at a specific instant. We introduce the concept of an sEMG image spatially composed from high-density sEMG and verify our findings from a computational perspective with experiments on gesture recognition based on sEMG images with a classification scheme of a deep convolutional network. Without any windowed features, the resultant recognition accuracy of an 8-gesture within-subject test reached 89.3% on a single frame of sEMG image and reached 99.0% using simple majority voting over 40 frames with a 1,000 Hz sampling rate. Experiments on the recognition of 52 gestures of NinaPro database and 27 gestures of CSL-HDEMG database also validated that our approach outperforms state-of-the-arts methods. Our findings are a starting point for the development of more fluid and natural muscle-computer interfaces with very little observational latency. For example, active prostheses and exoskeletons based on high-density electrodes could be controlled with instantaneous responses.

  14. Pattern activation/recognition theory of mind.

    Science.gov (United States)

    du Castel, Bertrand

    2015-01-01

    In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation.

  15. Recognition of Telugu characters using neural networks.

    Science.gov (United States)

    Sukhaswami, M B; Seetharamulu, P; Pujari, A K

    1995-09-01

    The aim of the present work is to recognize printed and handwritten Telugu characters using artificial neural networks (ANNs). Earlier work on recognition of Telugu characters has been done using conventional pattern recognition techniques. We make an initial attempt here of using neural networks for recognition with the aim of improving upon earlier methods which do not perform effectively in the presence of noise and distortion in the characters. The Hopfield model of neural network working as an associative memory is chosen for recognition purposes initially. Due to limitation in the capacity of the Hopfield neural network, we propose a new scheme named here as the Multiple Neural Network Associative Memory (MNNAM). The limitation in storage capacity has been overcome by combining multiple neural networks which work in parallel. It is also demonstrated that the Hopfield network is suitable for recognizing noisy printed characters as well as handwritten characters written by different "hands" in a variety of styles. Detailed experiments have been carried out using several learning strategies and results are reported. It is shown here that satisfactory recognition is possible using the proposed strategy. A detailed preprocessing scheme of the Telugu characters from digitized documents is also described.

  16. TEXT SIGNAGE RECOGNITION IN ANDROID MOBILE DEVICES

    Directory of Open Access Journals (Sweden)

    Oi-Mean Foong

    2013-01-01

    Full Text Available This study presents a Text Signage Recognition (TSR model in Android mobile devices for Visually Impaired People (VIP. Independence navigation is always a challenge to VIP for indoor navigation in unfamiliar surroundings. Assistive Technology such as Android smart devices has great potential to assist VIPs in indoor navigation using built-in speech synthesizer. In contrast to previous TSR research which was deployed in standalone personal computer system using Otsu’s algorithm, we have developed an affordable Text Signage Recognition in Android Mobile Devices using Tesseract OCR engine. The proposed TSR model used the input images from the International Conference on Document Analysis and Recognition (ICDAR 2003 dataset for system training and testing. The TSR model was tested by four volunteers who were blind-folded. The system performance of the TSR model was assessed using different metrics (i.e., Precision, Recall, F-Score and Recognition Formulas to determine its accuracy. Experimental results show that the proposed TSR model has achieved recognition rate satisfactorily.

  17. How fast is famous face recognition?

    Directory of Open Access Journals (Sweden)

    Gladys eBarragan-Jason

    2012-10-01

    Full Text Available The rapid recognition of familiar faces is crucial for social interactions. However the actual speed with which recognition can be achieved remains largely unknown as most studies have been carried out without any speed constraints. Different paradigms have been used, leading to conflicting results, and although many authors suggest that face recognition is fast, the speed of face recognition has not been directly compared to fast visual tasks. In this study, we sought to overcome these limitations. Subjects performed three tasks, a familiarity categorization task (famous faces among unknown faces, a superordinate categorization task (human faces among animal ones and a gender categorization task. All tasks were performed under speed constraints. The results show that, despite the use of speed constraints, subjects were slow when they had to categorize famous faces: minimum reaction time was 467 ms, which is 180 ms more than during superordinate categorization and 160 ms more than in the gender condition. Our results are compatible with a hierarchy of face processing from the superordinate level to the familiarity level. The processes taking place between detection and recognition need to be investigated in detail.

  18. Application of data fusion in computer facial recognition

    Directory of Open Access Journals (Sweden)

    Wang Ai Qiang

    2013-11-01

    Full Text Available The recognition rate of single recognition method is inefficiency in computer facial recognition. We proposed a new confluent facial recognition method using data fusion technology, a variety of recognition algorithm are combined to form the fusion-based face recognition system to improve the recognition rate in many ways. Data fusion considers three levels of data fusion, feature level fusion and decision level fusion. And the data layer uses a simple weighted average algorithm, which is easy to implement. Artificial neural network algorithm was selected in feature layer and fuzzy reasoning algorithm was used in decision layer. Finally, we compared with the BP neural network algorithm in the MATLAB experimental platform. The result shows that the recognition rate has been greatly improved after adopting data fusion technology in computer facial recognition.

  19. Experiences in Pattern Recognition for Machine Olfaction

    Science.gov (United States)

    Bessant, C.

    2011-09-01

    Pattern recognition is essential for translating complex olfactory sensor responses into simple outputs that are relevant to users. Many approaches to pattern recognition have been applied in this field, including multivariate statistics (e.g. discriminant analysis), artificial neural networks (ANNs) and support vector machines (SVMs). Reviewing our experience of using these techniques with many different sensor systems reveals some useful insights. Most importantly, it is clear beyond any doubt that the quantity and selection of samples used to train and test a pattern recognition system are by far the most important factors in ensuring it performs as accurately and reliably as possible. Here we present evidence for this assertion and make suggestions for best practice based on these findings.

  20. Molecular Mechanisms of Cell-cell Recognition

    Institute of Scientific and Technical Information of China (English)

    WANG Jia-Huai

    2004-01-01

    Cell-cell recognition is the key for multicellular organisms to survive. This recognition critically depends on protein-protein interactions from opposing cell surfaces. Recent structural investigations reveal unique features of these cell surface receptors and how they interact. These interactions are specific, but usually relatively weak, with more hydrophilic forces involved in binding. The receptors appear to have specialized ways to present their key interacting elements for ligand-binding from the cell surface. Cell-cell contacts are multivalent. A large group of cell surface molecules are engaged in interactions. Characteristic weak interactions make possible for each individual molecule pair within the group to constantly associate-dissociate-reassociate, such that the cell-cell recognition becomes a dynamic process. The immunological synapse is a good example for immune receptors to be orchestrated in performing immunological function in a collective fashion.

  1. Face Recognition Based on Nonlinear Feature Approach

    Directory of Open Access Journals (Sweden)

    Eimad E.A. Abusham

    2008-01-01

    Full Text Available Feature extraction techniques are widely used to reduce the complexity high dimensional data. Nonlinear feature extraction via Locally Linear Embedding (LLE has attracted much attention due to their high performance. In this paper, we proposed a novel approach for face recognition to address the challenging task of recognition using integration of nonlinear dimensional reduction Locally Linear Embedding integrated with Local Fisher Discriminant Analysis (LFDA to improve the discriminating power of the extracted features by maximize between-class while within-class local structure is preserved. Extensive experimentation performed on the CMU-PIE database indicates that the proposed methodology outperforms Benchmark methods such as Principal Component Analysis (PCA, Fisher Discrimination Analysis (FDA. The results showed that 95% of recognition rate could be obtained using our proposed method.

  2. Recognition bias and the physical attractiveness stereotype.

    Science.gov (United States)

    Rohner, Jean-Christophe; Rasmussen, Anders

    2012-06-01

    Previous studies have found a recognition bias for information consistent with the physical attractiveness stereotype (PAS), in which participants believe that they remember that attractive individuals have positive qualities and that unattractive individuals have negative qualities, regardless of what information actually occurred. The purpose of this research was to examine whether recognition bias for PAS congruent information is replicable and invariant across a variety of conditions (i.e. generalizable). The effects of nine different moderator variables were examined in two experiments. With a few exceptions, the effect of PAS congruence on recognition bias was independent of the moderator variables. The results suggest that the tendency to believe that one remembers information consistent with the physical attractiveness stereotype is a robust phenomenon.

  3. Kin-informative recognition cues in ants

    DEFF Research Database (Denmark)

    Nehring, Volker; Evison, Sophie E F; Santorelli, Lorenzo A

    2011-01-01

    Although social groups are characterized by cooperation, they are also often the scene of conflict. In non-clonal systems, the reproductive interests of group members will differ and individuals may benefit by exploiting the cooperative efforts of other group members. However, such selfish...... behaviour is thought to be rare in one of the classic examples of cooperation--social insect colonies--because the colony-level costs of individual selfishness select against cues that would allow workers to recognize their closest relatives. In accord with this, previous studies of wasps and ants have...... found little or no kin information in recognition cues. Here, we test the hypothesis that social insects do not have kin-informative recognition cues by investigating the recognition cues and relatedness of workers from four colonies of the ant Acromyrmex octospinosus. Contrary to the theoretical...

  4. Robust Speech Recognition Using a Harmonic Model

    Institute of Scientific and Technical Information of China (English)

    许超; 曹志刚

    2004-01-01

    Automatic speech recognition under conditions of a noisy environment remains a challenging problem. Traditionally, methods focused on noise structure, such as spectral subtraction, have been employed to address this problem, and thus the performance of such methods depends on the accuracy in noise estimation. In this paper, an alternative method, using a harmonic-based spectral reconstruction algorithm, is proposed for the enhancement of robust automatic speech recognition. Neither noise estimation nor noise-model training are required in the proposed approach. A spectral subtraction integrated autocorrelation function is proposed to determine the pitch for the harmonic model. Recognition results show that the harmonic-based spectral reconstruction approach outperforms spectral subtraction in the middle- and low-signal noise ratio (SNR) ranges. The advantage of the proposed method is more manifest for non-stationary noise, as the algorithm does not require an assumption of stationary noise.

  5. Robust facial expression recognition via compressive sensing.

    Science.gov (United States)

    Zhang, Shiqing; Zhao, Xiaoming; Lei, Bicheng

    2012-01-01

    Recently, compressive sensing (CS) has attracted increasing attention in the areas of signal processing, computer vision and pattern recognition. In this paper, a new method based on the CS theory is presented for robust facial expression recognition. The CS theory is used to construct a sparse representation classifier (SRC). The effectiveness and robustness of the SRC method is investigated on clean and occluded facial expression images. Three typical facial features, i.e., the raw pixels, Gabor wavelets representation and local binary patterns (LBP), are extracted to evaluate the performance of the SRC method. Compared with the nearest neighbor (NN), linear support vector machines (SVM) and the nearest subspace (NS), experimental results on the popular Cohn-Kanade facial expression database demonstrate that the SRC method obtains better performance and stronger robustness to corruption and occlusion on robust facial expression recognition tasks.

  6. Unstructured Object Recognition using Morphological Learning

    Directory of Open Access Journals (Sweden)

    S. Kar

    2002-07-01

    Full Text Available A technique of object recognition which can detect absence or presence of objects of interest without making explicit use of their underlying geometric structure is deemed suitable for many practical applications. In this work, a method of recognising unstructured objects has been presented, wherein several gray patterns are input as examples to a morphological rule-based learning algorithm. The output of the algorithm are the corresponding gray structuring elements capable of recognising patterns in query images. The learning is carried out offline before recognition of the queries. The technique has been tested to identify fuel pellet surface imperfections. Robustness wrt intensity, orientation, and shape variations of the query patterns is built into the method. Moreover, simplicity of the recognition process leading to reduced computational time makes the method attractive to solve many practical problems.

  7. Emotion recognition and regulation in anorexia nervosa.

    Science.gov (United States)

    Harrison, Amy; Sullivan, Sarah; Tchanturia, Kate; Treasure, Janet

    2009-01-01

    It is recognized that emotional problems lie at the core of eating disorders (EDs) but scant attention has been paid to specific aspects such as emotional recognition, regulation and expression. This study aimed to investigate emotion recognition using the Reading the Mind in the Eyes (RME) task and emotion regulation using the Difficulties in Emotion Regulation Scale (DERS) in 20 women with anorexia nervosa (AN) and 20 female healthy controls (HCs). Women with AN had significantly lower scores on RME and reported significantly more difficulties with emotion regulation than HCs. There was a significant negative correlation between total DERS score and correct answers from the RME. These results suggest that women with AN have difficulties with emotional recognition and regulation. It is uncertain whether these deficits result from starvation and to what extent they might be reversed by weight gain alone. These deficits may need to be targeted in treatment.

  8. Direct Neighborhood Discriminant Analysis for Face Recognition

    Directory of Open Access Journals (Sweden)

    Miao Cheng

    2008-01-01

    Full Text Available Face recognition is a challenging problem in computer vision and pattern recognition. Recently, many local geometrical structure-based techiniques are presented to obtain the low-dimensional representation of face images with enhanced discriminatory power. However, these methods suffer from the small simple size (SSS problem or the high computation complexity of high-dimensional data. To overcome these problems, we propose a novel local manifold structure learning method for face recognition, named direct neighborhood discriminant analysis (DNDA, which separates the nearby samples of interclass and preserves the local within-class geometry in two steps, respectively. In addition, the PCA preprocessing to reduce dimension to a large extent is not needed in DNDA avoiding loss of discriminative information. Experiments conducted on ORL, Yale, and UMIST face databases show the effectiveness of the proposed method.

  9. Recognition of social identity in ants

    DEFF Research Database (Denmark)

    Bos, Nick; d'Ettorre, Patrizia

    2012-01-01

    Recognizing the identity of others, from the individual to the group level, is a hallmark of society. Ants, and other social insects, have evolved advanced societies characterized by efficient social recognition systems. Colony identity is mediated by colony specific signature mixtures, a blend o...... is formed, where in the nervous system it is localized, and the possible role of learning. We combine seemingly contradictory evidence in to a novel, parsimonious theory for the information processing of nestmate recognition cues.......Recognizing the identity of others, from the individual to the group level, is a hallmark of society. Ants, and other social insects, have evolved advanced societies characterized by efficient social recognition systems. Colony identity is mediated by colony specific signature mixtures, a blend...

  10. Structural recognition of ancient Chinese ideographic characters

    Institute of Scientific and Technical Information of China (English)

    Li Ning; Chen Dan

    2014-01-01

    Ancient Chinese characters, typically the ideographic characters on bones and bronze before Shang Dynasty (16th—11th century B.C.), are valuable culture legacy of history. However the recognition of Ancient Chinese characters has been the task of paleography experts for long. With the help of modern computer technique, everyone can expect to be able to recognize the characters and understand the ancient inscriptions. This research is aimed to help people recognize and understand those ancient Chinese characters by combining Chinese paleography theory and computer information processing technology. Based on the analysis of ancient character features, a method for structural character recognition is proposed. The important characteristics of strokes and basic components or radicals used in recognition are introduced in detail. A system was implemented based on above method to show the effectiveness of the method.

  11. Recognition memory for foreign language lexical stress.

    Science.gov (United States)

    Suárez, Lidia; Goh, Winston D

    2013-08-01

    This study investigated whether English speakers retained the lexical stress patterns of newly learned Spanish words. Participants studied spoken Spanish words (e.g., DUcha [shower], ciuDAD [city]; stressed syllables in capital letters) and subsequently performed a recognition task, in which studied words were presented with the same lexical stress pattern (DUcha) or the opposite lexical stress pattern (CIUdad). Participants were able to discriminate same- from opposite-stress words, indicating that lexical stress was encoded and used in the recognition process. Word-form similarity to English also influenced outcomes, with Spanish cognate words and words with trochaic stress (MANgo) being recognized more often and more quickly than Spanish cognate words with iambic stress (soLAR) and noncognates. The results suggest that while segmental and suprasegmental features of the native language influence foreign word recognition, foreign lexical stress patterns are encoded and not discarded in memory.

  12. Hand Gesture Recognition Based on Improved FRNN

    Institute of Scientific and Technical Information of China (English)

    TENG Xiao-long; WANG Xiang-yang; LIU Chong-qing

    2005-01-01

    The trained Gaussian mixture model is used to make skincolour segmentation for the input image sequences. The hand gesture region is extracted, and the relative normalization images are obtained by interpolation operation. To solve the problem of hand gesture recognition, Fuzzy-Rough based nearest neighbour (FRNN) algorithm is applied for classification. For avoiding the costly compute, an improved nearest neighbour classification algorithm based on fuzzy-rough set theory (FRNNC) is proposed. The algorithm employs the represented cluster points instead of the whole training samples, and takes the hand gesture data's fuzziness and the roughness into account, so the compute spending is decreased and the recognition rate is increased. The 30 gestures in Chinese sign language alphabet are used for approving the effectiveness of the proposed algorithm. The recognition rate is 94.96%, which is better than that of KNN (K nearest neighbor)and Fuzzy-KNN (Fuzzy K nearest neighbor).

  13. Arabic Alphabet and Numbers Sign Language Recognition

    Directory of Open Access Journals (Sweden)

    Mahmoud Zaki Abdo

    2015-11-01

    Full Text Available This paper introduces an Arabic Alphabet and Numbers Sign Language Recognition (ArANSLR. It facilitates the communication between the deaf and normal people by recognizing the alphabet and numbers signs of Arabic sign language to text or speech. To achieve this target, the system able to visually recognize gestures from hand image input. The proposed algorithm uses hand geometry and the different shape of a hand in each sign for classifying letters shape by using Hidden Markov Model (HMM. Experiments on real-world datasets showed that the proposed algorithm for Arabic alphabet and numbers sign language recognition is suitability and reliability compared with other competitive algorithms. The experiment results show that the increasing of the gesture recognition rate depends on the increasing of the number of zones by dividing the rectangle surrounding the hand.

  14. Partially Supervised Approach in Signal Recognition

    Directory of Open Access Journals (Sweden)

    Catalina COCIANU

    2009-01-01

    Full Text Available The paper focuses on the potential of principal directions based approaches in signal classification and recognition. In probabilistic models, the classes are represented in terms of multivariate density functions, and an object coming from a certain class is modeled as a random vector whose repartition has the density function corresponding to this class. In cases when there is no statistical information concerning the set of density functions corresponding to the classes involved in the recognition process, usually estimates based on the information extracted from available data are used instead. In the proposed methodology, the characteristics of a class are given by a set of eigen vectors of the sample covariance matrix. The overall dissimilarity of an object X with a given class C is computed as the disturbance of the structure of C, when X is allotted to C. A series of tests concerning the behavior of the proposed recognition algorithm are reported in the final section of the paper.

  15. Accessing Specific Peptide Recognition by Combinatorial Chemistry

    DEFF Research Database (Denmark)

    Li, Ming

    Molecular recognition is at the basis of all processes for life, and plays a central role in many biological processes, such as protein folding, the structural organization of cells and organelles, signal transduction, and the immune response. Hence, my PhD project is entitled “Accessing Specific...... Peptide Recognition by Combinatorial Chemistry”. Molecular recognition is a specific interaction between two or more molecules through noncovalent bonding, such as hydrogen bonding, metal coordination, van der Waals forces, π−π, hydrophobic, or electrostatic interactions. The association involves kinetic....... Combinatorial chemistry was invented in 1980s based on observation of functional aspects of the adaptive immune system. It was employed for drug development and optimization in conjunction with high-throughput synthesis and screening. (chapter 2) Combinatorial chemistry is able to rapidly produce many thousands...

  16. Biologically inspired emotion recognition from speech

    Science.gov (United States)

    Caponetti, Laura; Buscicchio, Cosimo Alessandro; Castellano, Giovanna

    2011-12-01

    Emotion recognition has become a fundamental task in human-computer interaction systems. In this article, we propose an emotion recognition approach based on biologically inspired methods. Specifically, emotion classification is performed using a long short-term memory (LSTM) recurrent neural network which is able to recognize long-range dependencies between successive temporal patterns. We propose to represent data using features derived from two different models: mel-frequency cepstral coefficients (MFCC) and the Lyon cochlear model. In the experimental phase, results obtained from the LSTM network and the two different feature sets are compared, showing that features derived from the Lyon cochlear model give better recognition results in comparison with those obtained with the traditional MFCC representation.

  17. Pattern recognition using inverse resonance filtration

    CERN Document Server

    Sofina, Olga; Kvetnyy, Roman

    2010-01-01

    An approach to textures pattern recognition based on inverse resonance filtration (IRF) is considered. A set of principal resonance harmonics of textured image signal fluctuations eigen harmonic decomposition (EHD) is used for the IRF design. It was shown that EHD is invariant to textured image linear shift. The recognition of texture is made by transfer of its signal into unstructured signal which simple statistical parameters can be used for texture pattern recognition. Anomalous variations of this signal point on foreign objects. Two methods of 2D EHD parameters estimation are considered with the account of texture signal breaks presence. The first method is based on the linear symmetry model that is not sensitive to signal phase jumps. The condition of characteristic polynomial symmetry provides the model stationarity and periodicity. Second method is based on the eigenvalues problem of matrices pencil projection into principal vectors space of singular values decomposition (SVD) of 2D correlation matrix....

  18. Extraversion predicts individual differences in face recognition.

    Science.gov (United States)

    Li, Jingguang; Tian, Moqian; Fang, Huizhen; Xu, Miao; Li, He; Liu, Jia

    2010-07-01

    In daily life, one of the most common social tasks we perform is to recognize faces. However, the relation between face recognition ability and social activities is largely unknown. Here we ask whether individuals with better social skills are also better at recognizing faces. We found that extraverts who have better social skills correctly recognized more faces than introverts. However, this advantage was absent when extraverts were asked to recognize non-social stimuli (e.g., flowers). In particular, the underlying facet that makes extraverts better face recognizers is the gregariousness facet that measures the degree of inter-personal interaction. In addition, the link between extraversion and face recognition ability was independent of general cognitive abilities. These findings provide the first evidence that links face recognition ability to our daily activity in social communication, supporting the hypothesis that extraverts are better at decoding social information than introverts.

  19. Developmental, crosslinguistic perspectives on visual word recognition.

    Science.gov (United States)

    Simpson, Greg B; Kang, Hyewon

    2006-01-01

    In this paper, we argue that a complete understanding of language processing, in this case word-recognition processes, requires consideration both of multiple languages and of developmental processes. To illustrate these goals, we will summarize a 10-year research program exploring word-recognition processes in Korean adults and children. We describe the particular issue to which this research is directed (the relationship between print and the sound system of the language), and describe the characteristics of the Korean writing system that are relevant to this issue. We then outline our research examining the use of lexical and sublexical processes in recognizing Korean words. We use these studies to argue that cross-linguistic and developmental investigations may constrain models of language processes, and must be considered for a complete understanding of word-recognition and reading processes.

  20. Auditory—Spectrum Quantization Based Speech Recognition

    Institute of Scientific and Technical Information of China (English)

    WuYuanqing; HaoJie; 等

    1997-01-01

    Based on the analysis of the physiological and psychological characteristics of human auditory system[1],we can classify human auditory process into two hearing modes:active one and passive one.A novel approach of robust speech recognition,Auditory-spectrum Quantization Based Speech Recognition(AQBSR),is proposed.In this method,we intend to simulate human active hearing mode and locate the effective areas of speech signals in temporal domain and in frequency domain.Adaptive filter banks are used in place of fixed-band filters to extract feature parameters.The effective speech components and their corresponding frequency areas of each word in the vocabulary can be found out during training.In recognition stage,comparison between the unknown sound and the current template is maintained only in the effective areas of the template word.The control experiments show that the AQ BSR method is more robust than traditional systems.

  1. Real-time, face recognition technology

    Energy Technology Data Exchange (ETDEWEB)

    Brady, S.

    1995-11-01

    The Institute for Scientific Computing Research (ISCR) at Lawrence Livermore National Laboratory recently developed the real-time, face recognition technology KEN. KEN uses novel imaging devices such as silicon retinas developed at Caltech or off-the-shelf CCD cameras to acquire images of a face and to compare them to a database of known faces in a robust fashion. The KEN-Online project makes that recognition technology accessible through the World Wide Web (WWW), an internet service that has recently seen explosive growth. A WWW client can submit face images, add them to the database of known faces and submit other pictures that the system tries to recognize. KEN-Online serves to evaluate the recognition technology and grow a large face database. KEN-Online includes the use of public domain tools such as mSQL for its name-database and perl scripts to assist the uploading of images.

  2. Cognitive and artificial representations in handwriting recognition

    Science.gov (United States)

    Lenaghan, Andrew P.; Malyan, Ron

    1996-03-01

    Both cognitive processes and artificial recognition systems may be characterized by the forms of representation they build and manipulate. This paper looks at how handwriting is represented in current recognition systems and the psychological evidence for its representation in the cognitive processes responsible for reading. Empirical psychological work on feature extraction in early visual processing is surveyed to show that a sound psychological basis for feature extraction exists and to describe the features this approach leads to. The first stage of the development of an architecture for a handwriting recognition system which has been strongly influenced by the psychological evidence for the cognitive processes and representations used in early visual processing, is reported. This architecture builds a number of parallel low level feature maps from raw data. These feature maps are thresholded and a region labeling algorithm is used to generate sets of features. Fuzzy logic is used to quantify the uncertainty in the presence of individual features.

  3. Fast Pedestrian Recognition Based on Multisensor Fusion

    Directory of Open Access Journals (Sweden)

    Hongyu Hu

    2012-01-01

    Full Text Available A fast pedestrian recognition algorithm based on multisensor fusion is presented in this paper. Firstly, potential pedestrian locations are estimated by laser radar scanning in the world coordinates, and then their corresponding candidate regions in the image are located by camera calibration and the perspective mapping model. For avoiding time consuming in the training and recognition process caused by large numbers of feature vector dimensions, region of interest-based integral histograms of oriented gradients (ROI-IHOG feature extraction method is proposed later. A support vector machine (SVM classifier is trained by a novel pedestrian sample dataset which adapt to the urban road environment for online recognition. Finally, we test the validity of the proposed approach with several video sequences from realistic urban road scenarios. Reliable and timewise performances are shown based on our multisensor fusing method.

  4. Biologically inspired emotion recognition from speech

    Directory of Open Access Journals (Sweden)

    Buscicchio Cosimo

    2011-01-01

    Full Text Available Abstract Emotion recognition has become a fundamental task in human-computer interaction systems. In this article, we propose an emotion recognition approach based on biologically inspired methods. Specifically, emotion classification is performed using a long short-term memory (LSTM recurrent neural network which is able to recognize long-range dependencies between successive temporal patterns. We propose to represent data using features derived from two different models: mel-frequency cepstral coefficients (MFCC and the Lyon cochlear model. In the experimental phase, results obtained from the LSTM network and the two different feature sets are compared, showing that features derived from the Lyon cochlear model give better recognition results in comparison with those obtained with the traditional MFCC representation.

  5. Investigation of Carbohydrate Recognition via Computer Simulation

    Directory of Open Access Journals (Sweden)

    Quentin R. Johnson

    2015-04-01

    Full Text Available Carbohydrate recognition by proteins, such as lectins and other (biomolecules, can be essential for many biological functions. Recently, interest has arisen due to potential protein and drug design and future bioengineering applications. A quantitative measurement of carbohydrate-protein interaction is thus important for the full characterization of sugar recognition. We focus on the aspect of utilizing computer simulations and biophysical models to evaluate the strength and specificity of carbohydrate recognition in this review. With increasing computational resources, better algorithms and refined modeling parameters, using state-of-the-art supercomputers to calculate the strength of the interaction between molecules has become increasingly mainstream. We review the current state of this technique and its successful applications for studying protein-sugar interactions in recent years.

  6. Target recognition based on modified combination rule

    Institute of Scientific and Technical Information of China (English)

    Chen Tianlu; Que Peiwen

    2006-01-01

    Evidence theory is widely used in the field of target recognition. The invalidation problem of this theory when dealing with highly conflict evidences is a research hotspot. Several alternatives of the combination rule are analyzed and compared. A new combination approach is proposed. Calculate the reliabilities of evidence sources using existing evidences. Construct reliabilities judge matrixes and get the weights of each evidence source. Weight average all inputted evidences. Combine processed evidences with D-S combination rule repeatedly to identify a target. The application in multi-sensor target recognition as well as the comparison with typical alternatives all validated that this approach can dispose highly conflict evidences efficiently and get reasonable recognition results rapidly.

  7. Toward understanding the limits of gait recognition

    Science.gov (United States)

    Liu, Zongyi; Malave, Laura; Osuntogun, Adebola; Sudhakar, Preksha; Sarkar, Sudeep

    2004-08-01

    Most state of the art video-based gait recognition algorithms start from binary silhouettes. These silhouettes, defined as foreground regions, are usually detected by background subtraction methods, which results in holes or missed parts due to similarity of foreground and background color, and boundary errors due to video compression artifacts. Errors in low-level representation make it hard to understand the effect of certain conditions, such as surface and time, on gait recognition. In this paper, we present a part-level, manual silhouette database consisting of 71 subjects, over one gait cycle, with differences in surface, shoe-type, carrying condition, and time. We have a total of about 11,000 manual silhouette frames. The purpose of this manual silhouette database is twofold. First, this is a resource that we make available at http://www.GaitChallenge.org for use by the gait community to test and design better silhouette detection algorithms. These silhouettes can also be used to learn gait dynamics. Second, using the baseline gait recognition algorithm, which was specified along with the HumanID Gait Challenge problem, we show that performance from manual silhouettes is similar and only sometimes better than that from automated silhouettes detected by statistical background subtraction. Low performances when comparing sequences with differences in walking surfaces and time-variation are not fully explained by silhouette quality. We also study the recognition power in each body part and show that recognition based on just the legs is equal to that from the whole silhouette. There is also significant recognition power in the head and torso shape.

  8. Fingerprint Recognition Using Minutia Score Matching

    CERN Document Server

    J, Ravi; R, Venugopal K

    2010-01-01

    The popular Biometric used to authenticate a person is Fingerprint which is unique and permanent throughout a person's life. A minutia matching is widely used for fingerprint recognition and can be classified as ridge ending and ridge bifurcation. In this paper we projected Fingerprint Recognition using Minutia Score Matching method (FRMSM). For Fingerprint thinning, the Block Filter is used, which scans the image at the boundary to preserves the quality of the image and extract the minutiae from the thinned image. The false matching ratio is better compared to the existing algorithm.

  9. Fingerprint recognition using standardized fingerprint model

    CERN Document Server

    Thai, Le Hoang

    2011-01-01

    Fingerprint recognition is one of most popular and accuracy Biometric technologies. Nowadays, it is used in many real applications. However, recognizing fingerprints in poor quality images is still a very complex problem. In recent years, many algorithms, models...are given to improve the accuracy of recognition system. This paper discusses on the standardized fingerprint model which is used to synthesize the template of fingerprints. In this model, after pre-processing step, we find the transformation between templates, adjust parameters, synthesize fingerprint, and reduce noises. Then, we use the final fingerprint to match with others in FVC2004 fingerprint database (DB4) to show the capability of the model.

  10. Performance appraisal and merit recognition exercise 2007

    CERN Multimedia

    HR Department

    2006-01-01

    The 2007 performance appraisal and merit recognition exercise will start in the usual way with annual interviews between staff and their supervisors. This year, these interviews should be held in the period from 8 January 2007 to 16 April 2007. Interconnection with the 5-yearly review, a number of modifications to the procedures relating to the performance appraisal and merit recognition are currently under study. Administrative Circular No. 26 (Procedures governing the Career Development of Staff Members) and the electronic MAPS form in EDH are being reviewed and will be available from January onwards. HR Department will shortly provide further information on this subject. Human Resources Department Tel. 73566

  11. Primitive Based Action Representation and recognition

    DEFF Research Database (Denmark)

    Baby, Sanmohan

    The presented work is aimed at designing a system that will model and recognize actions and its interaction with objects. Such a system is aimed at facilitating robot task learning. Activity modeling and recognition is very important for its potential applications in surveillance, human-machine i......The presented work is aimed at designing a system that will model and recognize actions and its interaction with objects. Such a system is aimed at facilitating robot task learning. Activity modeling and recognition is very important for its potential applications in surveillance, human...

  12. Human action recognition with depth cameras

    CERN Document Server

    Wang, Jiang; Wu, Ying

    2014-01-01

    Action recognition technology has many real-world applications in human-computer interaction, surveillance, video retrieval, retirement home monitoring, and robotics. The commoditization of depth sensors has also opened up further applications that were not feasible before. This text focuses on feature representation and machine learning algorithms for action recognition from depth sensors. After presenting a comprehensive overview of the state of the art, the authors then provide in-depth descriptions of their recently developed feature representations and machine learning techniques, includi

  13. Recognition and Judgement in Social Work

    DEFF Research Database (Denmark)

    Juul, Søren

    2009-01-01

    The purpose of this article is to argue for recognition as a normative ideal for social work and to confront the ideal with the reality found in the social institutions. I shall use the concept "judgement" to describe institutional routines and ways of thinking which constitute barriers...... to recognition. In the first part, I outline the normative ideal and show its relevance for practical social work on the basis of social clients' experiences of disrespect. In the second, I expalin the concept of judgement and criticise the prevailing forms of judgement to be found in the social institutions...

  14. Human recognition at a distance in video

    CERN Document Server

    Bhanu, Bir

    2010-01-01

    Most biometric systems employed for human recognition require physical contact with, or close proximity to, a cooperative subject. Far more challenging is the ability to reliably recognize individuals at a distance, when viewed from an arbitrary angle under real-world environmental conditions. Gait and face data are the two biometrics that can be most easily captured from a distance using a video camera. This comprehensive and logically organized text/reference addresses the fundamental problems associated with gait and face-based human recognition, from color and infrared video data that are

  15. Manifold knowledge extraction and target recognition

    Science.gov (United States)

    Chao, Cai; Hua, Zhou

    2009-10-01

    Advanced mammalian target identification derived from the perception of target's manifold and measurement manifolddistance. It does not rely on object's segmented accuracy, not depend on target's variety model, and adapt to a range of changes on targets. In this paper, based on the existed manifold learning algorithm, set up a new bionic automatic target recognition model, discussed the targets manifold knowledge acquisition and the knowledge expression architecture, gave a manifold knowledge-based new method for automatic target recognition. Experiments show that the new method has a strong adaptability to targets various transform, and has a very high correctly identification probability.

  16. Incorporating Duration Information in Activity Recognition

    Science.gov (United States)

    Chaurasia, Priyanka; Scotney, Bryan; McClean, Sally; Zhang, Shuai; Nugent, Chris

    Activity recognition has become a key issue in smart home environments. The problem involves learning high level activities from low level sensor data. Activity recognition can depend on several variables; one such variable is duration of engagement with sensorised items or duration of intervals between sensor activations that can provide useful information about personal behaviour. In this paper a probabilistic learning algorithm is proposed that incorporates episode, time and duration information to determine inhabitant identity and the activity being undertaken from low level sensor data. Our results verify that incorporating duration information consistently improves the accuracy.

  17. Human gait recognition via deterministic learning.

    Science.gov (United States)

    Zeng, Wei; Wang, Cong

    2012-11-01

    Recognition of temporal/dynamical patterns is among the most difficult pattern recognition tasks. Human gait recognition is a typical difficulty in the area of dynamical pattern recognition. It classifies and identifies individuals by their time-varying gait signature data. Recently, a new dynamical pattern recognition method based on deterministic learning theory was presented, in which a time-varying dynamical pattern can be effectively represented in a time-invariant manner and can be rapidly recognized. In this paper, we present a new model-based approach for human gait recognition via the aforementioned method, specifically for recognizing people by gait. The approach consists of two phases: a training (learning) phase and a test (recognition) phase. In the training phase, side silhouette lower limb joint angles and angular velocities are selected as gait features. A five-link biped model for human gait locomotion is employed to demonstrate that functions containing joint angle and angular velocity state vectors characterize the gait system dynamics. Due to the quasi-periodic and symmetrical characteristics of human gait, the gait system dynamics can be simplified to be described by functions of joint angles and angular velocities of one side of the human body, thus the feature dimension is effectively reduced. Locally-accurate identification of the gait system dynamics is achieved by using radial basis function (RBF) neural networks (NNs) through deterministic learning. The obtained knowledge of the approximated gait system dynamics is stored in constant RBF networks. A gait signature is then derived from the extracted gait system dynamics along the phase portrait of joint angles versus angular velocities. A bank of estimators is constructed using constant RBF networks to represent the training gait patterns. In the test phase, by comparing the set of estimators with the test gait pattern, a set of recognition errors are generated, and the average L(1) norms

  18. Stereo vision with distance and gradient recognition

    Science.gov (United States)

    Kim, Soo-Hyun; Kang, Suk-Bum; Yang, Tae-Kyu

    2007-12-01

    Robot vision technology is needed for the stable walking, object recognition and the movement to the target spot. By some sensors which use infrared rays and ultrasonic, robot can overcome the urgent state or dangerous time. But stereo vision of three dimensional space would make robot have powerful artificial intelligence. In this paper we consider about the stereo vision for stable and correct movement of a biped robot. When a robot confront with an inclination plane or steps, particular algorithms are needed to go on without failure. This study developed the recognition algorithm of distance and gradient of environment by stereo matching process.

  19. FACE RECOGNITION FROM FRONT-VIEW FACE

    Institute of Scientific and Technical Information of China (English)

    WuLifang; ShenLansun

    2003-01-01

    This letter presents a face normalization algorithm based on 2-D face model to rec-ognize faces with variant postures from front-view face.A 2-D face mesh model can be extracted from faces with rotation to left or right and the corresponding front-view mesh model can be estimated according to facial symmetry.Then based on the relationship between the two mesh models,the nrmalized front-view face is formed by gray level mapping.Finally,the face recognition will be finished based on Principal Component Analysis(PCA).Experiments show that better face recognition performance is achieved in this way.

  20. FACE RECOGNITION FROM FRONT-VIEW FACE

    Institute of Scientific and Technical Information of China (English)

    Wu Lifang; Shen Lansun

    2003-01-01

    This letter presents a face normalization algorithm based on 2-D face model to recognize faces with variant postures from front-view face. A 2-D face mesh model can be extracted from faces with rotation to left or right and the corresponding front-view mesh model can be estimated according to the facial symmetry. Then based on the inner relationship between the two mesh models, the normalized front-view face is formed by gray level mapping. Finally, the face recognition will be finished based on Principal Component Analysis (PCA). Experiments show that better face recognition performance is achieved in this way.

  1. Convolution neural networks for ship type recognition

    Science.gov (United States)

    Rainey, Katie; Reeder, John D.; Corelli, Alexander G.

    2016-05-01

    Algorithms to automatically recognize ship type from satellite imagery are desired for numerous maritime applications. This task is difficult, and example imagery accurately labeled with ship type is hard to obtain. Convolutional neural networks (CNNs) have shown promise in image recognition settings, but many of these applications rely on the availability of thousands of example images for training. This work attempts to under- stand for which types of ship recognition tasks CNNs might be well suited. We report the results of baseline experiments applying a CNN to several ship type classification tasks, and discuss many of the considerations that must be made in approaching this problem.

  2. Fungal glycans and the innate immune recognition

    Directory of Open Access Journals (Sweden)

    Rodrigo Tinoco Figueiredo

    2014-10-01

    Full Text Available Polysaccharides such as α- and β-glucans, chitin and glycoproteins extensively modified with both N- and O-linked carbohydrates are the major components of fungal surfaces. The fungal cell wall is an excellent target for the action of antifungal agents, since most of its components are absent from mammalian cells. Recognition of these carbohydrate-containing molecules by the innate immune system triggers inflammatory responses and activation of microbicidal mechanisms by leukocytes. This review will discuss the structure of surface fungal glycoconjugates and polysaccharides and their recognition by innate immune receptors.

  3. Structure and mechanism for DNA lesion recognition

    Institute of Scientific and Technical Information of China (English)

    Wei Yang

    2008-01-01

    A fundamental question in DNA repair is how a lesion is detected when embedded in millions to billions of normal base pairs. Extensive structural and functional studies reveal atomic details of DNA repair protein and nucleic acid interactions. This review summarizes seemingly diverse structural motifs used in lesion recognition and suggests a general mechanism to recognize DNA lesion by the poor base stacking. After initial recognition of this shared struc-tural feature of lesions, different DNA repair pathways use unique verification mechanisms to ensure correct lesion identification and removal.

  4. Affine Invariant Character Recognition by Progressive Removing

    Science.gov (United States)

    Iwamura, Masakazu; Horimatsu, Akira; Niwa, Ryo; Kise, Koichi; Uchida, Seiichi; Omachi, Shinichiro

    Recognizing characters in scene images suffering from perspective distortion is a challenge. Although there are some methods to overcome this difficulty, they are time-consuming. In this paper, we propose a set of affine invariant features and a new recognition scheme called “progressive removing” that can help reduce the processing time. Progressive removing gradually removes less feasible categories and skew angles by using multiple classifiers. We observed that progressive removing and the use of the affine invariant features reduced the processing time by about 60% in comparison to a trivial one without decreasing the recognition rate.

  5. Towards very large vocabulary word recognition

    Science.gov (United States)

    Waibel, A.

    1982-11-01

    In this paper, preliminary considerations and some experimental results are presented in an effort to design Very Large Vocabulary Recognition (VLVR) systems. We will first consider the applicability of current recognition techniques and argue their inadequacy for VLVR. Possible alternate strategies will be explored and their potential usefulness statistically evaluated. Our results indicate that suprasegmental cues such as syllabification, stress patterns, rhythmic patterns, rhythmic patterns and the voiced - unvoiced patterns in the syllables of a word provide powerful mechanisms for search space reduction. Suprasegmental feature could thus operate in a complementary fashion to segmental features.

  6. An Embedded Application for Degraded Text Recognition

    Directory of Open Access Journals (Sweden)

    Thillou Céline

    2005-01-01

    Full Text Available This paper describes a mobile device which tries to give the blind or visually impaired access to text information. Three key technologies are required for this system: text detection, optical character recognition, and speech synthesis. Blind users and the mobile environment imply two strong constraints. First, pictures will be taken without control on camera settings and a priori information on text (font or size and background. The second issue is to link several techniques together with an optimal compromise between computational constraints and recognition efficiency. We will present the overall description of the system from text detection to OCR error correction.

  7. Knowledge based recognition of harbor target

    Institute of Scientific and Technical Information of China (English)

    Zhu Bing; Li Jinzong; Cheng Aijun

    2006-01-01

    A fast knowledge based recognition method of the harbor target in large gray remote-sensing image is presented. First, the distributed features and the inherent feature are analyzed according to the knowledge of harbor targets; then, two methods for extracting the candidate region of harbor are devised in accordance with different sizes of the harbors; after that, thresholds are used to segment the land and the sea with strategies of the segmentation error control; finally, harbor recognition is implemented according to its inherent character (semi-closed region of seawater).

  8. Molecular Recognition Studies on Modified Cyclodextrins

    Institute of Scientific and Technical Information of China (English)

    LIU,Yu; YOU,Chang-Cheng

    2001-01-01

    This account deacribes our research progress in recent years in the areas of the molecular recognition studies on modified cy clodextrins, including positively charged cyclodextrins, cy clodextrin derivatives with hydrophobic substituent, and dimeric cyclodextrins. Calorimetric titration and various spec trometric techniques were employed to determine the complex stability constants, as well as the thermodynamic parameters, for their inclusion complexation with diverse guest molecules. The results obtained have heen discussed from the viewpoint of size/shape-matching, induced-fit, geometric compensation, and multiple recognition. Thermodynamically, the compen satory relationship between △H and T△S was found to be ex hibited in the inclusion complexation of modified cyclodextrin.

  9. A Survey on Human Ear Recognition

    Directory of Open Access Journals (Sweden)

    Suvarnsing Bhable

    2015-11-01

    Full Text Available This paper presents an efficient ear recognition technique which derives benefits from the local features of the ear and attempt to handle the problems due to pose, poor contrast, change in illumination and lack of registration. Recognizing humans by their ear have recently received significant attention in the field of research. Ear is the rich in characteristics. This paper provides a detailed survey of research done in ear detection and recognition. This survey paper is very useful in the current state-of- art for those who are working in this area and also for those who might exploit this new approach.

  10. Amharic Speech Recognition for Speech Translation

    OpenAIRE

    Melese, Michael; Besacier, Laurent; Meshesha, Million

    2016-01-01

    International audience; The state-of-the-art speech translation can be seen as a cascade of Automatic Speech Recognition, Statistical Machine Translation and Text-To-Speech synthesis. In this study an attempt is made to experiment on Amharic speech recognition for Amharic-English speech translation in tourism domain. Since there is no Amharic speech corpus, we developed a read-speech corpus of 7.43hr in tourism domain. The Amharic speech corpus has been recorded after translating standard Bas...

  11. Adaptive Face Recognition via Structed Representation

    Institute of Scientific and Technical Information of China (English)

    ZHANG Yu-hua; ZENG Xiao-ming

    2014-01-01

    In this paper, we propose a face recognition approach-Structed Sparse Representation-based classification when the measurement of the test sample is less than the number training samples of each subject. When this condition is not satisfied, we exploit Nearest Subspace approach to classify the test sample. In order to adapt all the cases, we combine the two approaches to an adaptive classification method-Adaptive approach. The adaptive approach yields greater recognition accuracy than the SRC approach and CRC_RLS approach with low sample rate on the Extend Yale B dataset. And it is more efficient than other two approaches.

  12. Enhancing face recognition by image warping

    OpenAIRE

    García Bueno, Jorge

    2009-01-01

    This project has been developed as an improvement which could be added to the actual computer vision algorithms. It is based on the original idea proposed and published by Rob Jenkins and Mike Burton about the power of the face averages in arti cial recognition. The present project aims to create a new automated procedure applied for face recognition working with average images. Up to now, this algorithm has been used manually. With this study, the averaging and warping process will be done b...

  13. Phoneme Based Speaker—Independent English Command Recognition

    Institute of Scientific and Technical Information of China (English)

    贲俊; 万旺根; 余小清

    2003-01-01

    In this paper we propose a new algorithm of phoneme based speaker-independent English command recognition and develop a speaker-independent English command recognition system. It accelerates the whole system development by using HTK (hide Markov toolkits) and Visual C + + based on the character' istics of speaker-independent speech recognition. In recognition phase we combine the confidence measures with incomplete matching, which considerably improve the quality of recognition. The recognition accuracyis increased by 4.8 % over complete matching without back-end processing when the sige of vocabulary is more than 10.

  14. Radar automatic target recognition (ATR) and non-cooperative target recognition (NCTR)

    CERN Document Server

    Blacknell, David

    2013-01-01

    The ability to detect and locate targets by day or night, over wide areas, regardless of weather conditions has long made radar a key sensor in many military and civil applications. However, the ability to automatically and reliably distinguish different targets represents a difficult challenge. Radar Automatic Target Recognition (ATR) and Non-Cooperative Target Recognition (NCTR) captures material presented in the NATO SET-172 lecture series to provide an overview of the state-of-the-art and continuing challenges of radar target recognition. Topics covered include the problem as applied to th

  15. Good, Evil and Successful Recognition. A Processualist View on Recognitive Attitudes, Relations and Norms

    Directory of Open Access Journals (Sweden)

    Särkelä Arvi-Antti

    2013-06-01

    Full Text Available In this paper I am proposing a “processual” account of struggles for recognition. I read Hegel in the section of “Evil and Its Forgiveness,” in his Phenomenology of Spirit, as arguing for a transition from basically action-theoretic, relational or institutional conceptions of recognition to a processual conception. Furthermore, I will be claiming that John Dewey’s experimentalist social philosophy can be understood as an attempt at working out the implications of this move in Hegel’s thought. Finally, I will try to indicate how to integrate central concepts of the recognition-theoretical vocabulary into such a processual account

  16. Advances in the biometric recognition methods: a survey on iris and fingerprint recognition

    Science.gov (United States)

    Zaeri, Naser; Alkoot, Fuad

    2010-02-01

    Human recognition based on biometrics finds many important applications in many life sectors and in particular in commercial and law enforcement. This paper aims to give a general overview of the advances in the biometric recognition methods. We concentrate on main methods and accessible ideas presented for human recognition systems based on two types of biometrics: iris and fingerprint. We present a quick overview of the landmark papers that laid the foundation in each track then we present the latest updates and important turns and solutions that developed in each track in the last few years.

  17. The role of pattern recognition receptors in the innate recognition of Candida albicans.

    Science.gov (United States)

    Zheng, Nan-Xin; Wang, Yan; Hu, Dan-Dan; Yan, Lan; Jiang, Yuan-Ying

    2015-01-01

    Candida albicans is both a commensal microorganism in healthy individuals and a major fungal pathogen causing high mortality in immunocompromised patients. Yeast-hypha morphological transition is a well known virulence trait of C. albicans. Host innate immunity to C. albicans critically requires pattern recognition receptors (PRRs). In this review, we summarize the PRRs involved in the recognition of C. albicans in epithelial cells, endothelial cells, and phagocytic cells separately. We figure out the differential recognition of yeasts and hyphae, the findings on PRR-deficient mice, and the discoveries on human PRR-related single nucleotide polymorphisms (SNPs).

  18. DATABASES FOR RECOGNITION OF HANDWRITTEN ARABIC CHEQUES

    NARCIS (Netherlands)

    Alohali, Y.; Cheriet, M.; Suen, C.Y.

    2004-01-01

    This paper describes an effort toward building Arabic cheque databases for research in recognition of handwritten Arabic cheques. Databases of Arabic legal amounts, Arabic sub­ words, courtesy amounts, Indian digits, and Arabic cheques are provided. This paper highlights the characteristics of the A

  19. Evaluation of context effects in sentence recognition

    NARCIS (Netherlands)

    Bronkhorst, A.W.; Brand, T.; Wagener, K.

    2002-01-01

    It was investigated whether the model for context effects, developed earlier by Bronkhorst et al. [J. Acoust. Soc. Am. 93, 499-509 (1993)], can be applied to results of sentence tests, used for the evaluation of speech recognition. Data for two German sentence tests, that differed with respect to th

  20. ORNL Biometric Eye Model for Iris Recognition

    Energy Technology Data Exchange (ETDEWEB)

    Santos-Villalobos, Hector J [ORNL; Barstow, Del R [ORNL; Karakaya, Mahmut [ORNL; Chaum, Edward [University of Tennessee, Knoxville (UTK); Boehnen, Chris Bensing [ORNL

    2012-01-01

    Iris recognition has been proven to be an accurate and reliable biometric. However, the recognition of non-ideal iris images such as off angle images is still an unsolved problem. We propose a new biometric targeted eye model and a method to reconstruct the off-axis eye to its frontal view allowing for recognition using existing methods and algorithms. This allows for existing enterprise level algorithms and approaches to be largely unmodified by using our work as a pre-processor to improve performance. In addition, we describe the `Limbus effect' and its importance for an accurate segmentation of off-axis irides. Our method uses an anatomically accurate human eye model and ray-tracing techniques to compute a transformation function, which reconstructs the iris to its frontal, non-refracted state. Then, the same eye model is used to render a frontal view of the reconstructed iris. The proposed method is fully described and results from synthetic data are shown to establish an upper limit on performance improvement and establish the importance of the proposed approach over traditional linear elliptical unwrapping methods. Our results with synthetic data demonstrate the ability to perform an accurate iris recognition with an image taken as much as 70 degrees off-axis.

  1. RECOGNITION AND VERIFICATION OF TOUCHING HANDWRITTEN NUMERALS

    NARCIS (Netherlands)

    Zhou, J.; Kryzak, A.; Suen, C.Y.

    2004-01-01

    In the field of financial document processing, recognition of touching handwritten numerals has been limited by lack of good benchmarking databases and low reliability of algorithms. This paper addresses the efforts toward solving the two problems. Two databases IRIS-Bell\\\\\\'98 and TNIST are built/o

  2. Iris Recognition: The Consequences of Image Compression

    Directory of Open Access Journals (Sweden)

    Bishop DanielA

    2010-01-01

    Full Text Available Iris recognition for human identification is one of the most accurate biometrics, and its employment is expanding globally. The use of portable iris systems, particularly in law enforcement applications, is growing. In many of these applications, the portable device may be required to transmit an iris image or template over a narrow-bandwidth communication channel. Typically, a full resolution image (e.g., VGA is desired to ensure sufficient pixels across the iris to be confident of accurate recognition results. To minimize the time to transmit a large amount of data over a narrow-bandwidth communication channel, image compression can be used to reduce the file size of the iris image. In other applications, such as the Registered Traveler program, an entire iris image is stored on a smart card, but only 4 kB is allowed for the iris image. For this type of application, image compression is also the solution. This paper investigates the effects of image compression on recognition system performance using a commercial version of the Daugman iris2pi algorithm along with JPEG-2000 compression, and links these to image quality. Using the ICE 2005 iris database, we find that even in the face of significant compression, recognition performance is minimally affected.

  3. Pattern recognition receptors in antifungal immunity.

    Science.gov (United States)

    Plato, Anthony; Hardison, Sarah E; Brown, Gordon D

    2015-03-01

    Receptors of the innate immune system are the first line of defence against infection, being able to recognise and initiate an inflammatory response to invading microorganisms. The Toll-like (TLR), NOD-like (NLR), RIG-I-like (RLR) and C-type lectin-like receptors (CLR) are four receptor families that contribute to the recognition of a vast range of species, including fungi. Many of these pattern recognition receptors (PRRs) are able to initiate innate immunity and polarise adaptive responses upon the recognition of fungal cell wall components and other conserved molecular patterns, including fungal nucleic acids. These receptors induce effective mechanisms of fungal clearance in normal hosts, but medical interventions, immunosuppression or genetic predisposition can lead to susceptibility to fungal infections. In this review, we highlight the importance of PRRs in fungal infection, specifically CLRs, which are the major PRR involved. We will describe specific PRRs in detail, the importance of receptor collaboration in fungal recognition and clearance, and describe how genetic aberrations in PRRs can contribute to disease pathology.

  4. Affect Recognition in Adults with ADHD

    Science.gov (United States)

    Miller, Meghan; Hanford, Russell B.; Fassbender, Catherine; Duke, Marshall; Schweitzer, Julie B.

    2011-01-01

    Objective: This study compared affect recognition abilities between adults with and without ADHD. Method: The sample consisted of 51 participants (34 men, 17 women) divided into 3 groups: ADHD-combined type (ADHD-C; n = 17), ADHD-predominantly inattentive type (ADHD-I; n = 16), and controls (n = 18). The mean age was 34 years. Affect recognition…

  5. Vintage High School Citizenship Recognition Program.

    Science.gov (United States)

    Napa Valley Unified School District, Napa, CA.

    THE FOLLOWING IS THE FULL TEXT OF THIS DOCUMENT: Recognition of good citizenship is one component of the Vintage High School Student Incentive Program which could be easily adapted for any school. The only direct cost is for postage to mail congratulatory letters home and a small initial cost for printing award certificates. On a rotating basis,…

  6. Face Detection and Modeling for Recognition

    Science.gov (United States)

    2002-01-01

    facial components show the important role of hair and face outlines in human face recognition. . . 8 1.6 Caricatures of (a) Vincent Van Gogh ; (b) Jim... Vincent Van Gogh ; (b) Jim Carrey; (c) Arnold Schwarzenegger; (d) Einstein; (e) G. W. Bush; and (f) Bill Gates. Images are down- loaded from [9], [10

  7. Probabilistic recognition of human faces from video

    DEFF Research Database (Denmark)

    Zhou, Saohua; Krüger, Volker; Chellappa, Rama

    2003-01-01

    of the identity variable produces the recognition result. The model formulation is very general and it allows a variety of image representations and transformations. Experimental results using videos collected by NIST/USF and CMU illustrate the effectiveness of this approach for both still-to-video and video...

  8. Face recognition increases during saccade preparation.

    Directory of Open Access Journals (Sweden)

    Hai Lin

    Full Text Available Face perception is integral to human perception system as it underlies social interactions. Saccadic eye movements are frequently made to bring interesting visual information, such as faces, onto the fovea for detailed processing. Just before eye movement onset, the processing of some basic features, such as the orientation, of an object improves at the saccade landing point. Interestingly, there is also evidence that indicates faces are processed in early visual processing stages similar to basic features. However, it is not known whether this early enhancement of processing includes face recognition. In this study, three experiments were performed to map the timing of face presentation to the beginning of the eye movement in order to evaluate pre-saccadic face recognition. Faces were found to be similarly processed as simple objects immediately prior to saccadic movements. Starting ∼ 120 ms before a saccade to a target face, independent of whether or not the face was surrounded by other faces, the face recognition gradually improved and the critical spacing of the crowding decreased as saccade onset was approaching. These results suggest that an upcoming saccade prepares the visual system for new information about faces at the saccade landing site and may reduce the background in a crowd to target the intended face. This indicates an important role of pre-saccadic eye movement signals in human face recognition.

  9. The irre cell recognition module (IRM) proteins.

    Science.gov (United States)

    Fischbach, Karl-Friedrich; Linneweber, Gerit Arne; Andlauer, Till Felix Malte; Hertenstein, Alexander; Bonengel, Bernhard; Chaudhary, Kokil

    2009-01-01

    One of the most challenging problems in developmental neurosciences is to understand the establishment and maintenance of specific membrane contacts between axonal, dendritic, and glial processes in the neuropils, which eventually secure neuronal connectivity. However, underlying cell recognition events are pivotal in other tissues as well. This brief review focuses on the pleiotropic functions of a small, evolutionarily conserved group of proteins of the immunoglobulin superfamily involved in cell recognition. In Drosophila, this protein family comprises Irregular chiasm C/Roughest (IrreC/Rst), Kin of irre (Kirre), and their interacting protein partners, Sticks and stones (SNS) and Hibris (Hbs). For simplicity, we propose to name this ensemble of proteins the irre cell recognition module (IRM) after the first identified member of this family. Here, we summarize evidence that the IRM proteins function together in various cellular interactions, including myoblast fusion, cell sorting, axonal pathfinding, and target recognition in the optic neuropils of Drosophila. Understanding IRM protein function will help to unravel the epigenetic rules by which the intricate neurite networks in sensory neuropils are formed.

  10. Emotional context influences micro-expression recognition.

    Directory of Open Access Journals (Sweden)

    Ming Zhang

    Full Text Available Micro-expressions are often embedded in a flow of expressions including both neutral and other facial expressions. However, it remains unclear whether the types of facial expressions appearing before and after the micro-expression, i.e., the emotional context, influence micro-expression recognition. To address this question, the present study used a modified METT (Micro-Expression Training Tool paradigm that required participants to recognize the target micro-expressions presented briefly between two identical emotional faces. The results of Experiments 1 and 2 showed that negative context impaired the recognition of micro-expressions regardless of the duration of the target micro-expression. Stimulus-difference between the context and target micro-expression was accounted for in Experiment 3. Results showed that a context effect on micro-expression recognition persists even when the stimulus similarity between the context and target micro-expressions was controlled. Therefore, our results not only provided evidence for the context effect on micro-expression recognition but also suggested that the context effect might result from both the stimulus and valence differences.

  11. SOFIR: Securely Outsourced Forensic Image Recognition

    NARCIS (Netherlands)

    Bösch, Christoph; Peter, Andreas; Hartel, Pieter; Jonker, Willem

    2014-01-01

    Forensic image recognition tools are used by law enforcement agencies all over the world to automatically detect illegal images on confiscated equipment. This detection is commonly done with the help of a strictly confidential database consisting of hash values of known illegal images. To detect and

  12. Parametric Primitives for Hand Gesture Recognition

    DEFF Research Database (Denmark)

    Baby, Sanmohan; Krüger, Volker

    2009-01-01

    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 an ac...

  13. Compact Acoustic Models for Embedded Speech Recognition

    Directory of Open Access Journals (Sweden)

    Lévy Christophe

    2009-01-01

    Full Text Available Speech recognition applications are known to require a significant amount of resources. However, embedded speech recognition only authorizes few KB of memory, few MIPS, and small amount of training data. In order to fit the resource constraints of embedded applications, an approach based on a semicontinuous HMM system using state-independent acoustic modelling is proposed. A transformation is computed and applied to the global model in order to obtain each HMM state-dependent probability density functions, authorizing to store only the transformation parameters. This approach is evaluated on two tasks: digit and voice-command recognition. A fast adaptation technique of acoustic models is also proposed. In order to significantly reduce computational costs, the adaptation is performed only on the global model (using related speaker recognition adaptation techniques with no need for state-dependent data. The whole approach results in a relative gain of more than 20% compared to a basic HMM-based system fitting the constraints.

  14. Material Recognition for Content Based Image Retrieval

    NARCIS (Netherlands)

    Geusebroek, J.M.

    2002-01-01

    One of the open problems in content-based Image Retrieval is the recognition of material present in an image. Knowledge about the set of materials present gives important semantic information about the scene under consideration. For example, detecting sand, sky, and water certainly classifies the im

  15. Facial expression recognition in perceptual color space.

    Science.gov (United States)

    Lajevardi, Seyed Mehdi; Wu, Hong Ren

    2012-08-01

    This paper introduces a tensor perceptual color framework (TPCF) for facial expression recognition (FER), which is based on information contained in color facial images. The TPCF enables multi-linear image analysis in different color spaces and demonstrates that color components provide additional information for robust FER. Using this framework, the components (in either RGB, YCbCr, CIELab or CIELuv space) of color images are unfolded to two-dimensional (2- D) tensors based on multi-linear algebra and tensor concepts, from which the features are extracted by Log-Gabor filters. The mutual information quotient (MIQ) method is employed for feature selection. These features are classified using a multi-class linear discriminant analysis (LDA) classifier. The effectiveness of color information on FER using low-resolution and facial expression images with illumination variations is assessed for performance evaluation. Experimental results demonstrate that color information has significant potential to improve emotion recognition performance due to the complementary characteristics of image textures. Furthermore, the perceptual color spaces (CIELab and CIELuv) are better overall for facial expression recognition than other color spaces by providing more efficient and robust performance for facial expression recognition using facial images with illumination variation.

  16. Pattern Recognition by Retina-Like Devices.

    Science.gov (United States)

    Weiman, Carl F. R.; Rothstein, Jerome

    This study has investigated some pattern recognition capabilities of devices consisting of arrays of cooperating elements acting in parallel. The problem of recognizing straight lines in general position on the quadratic lattice has been completely solved by applying parallel acting algorithms to a special code for lines on the lattice. The…

  17. Image enhancement method for fingerprint recognition system.

    Science.gov (United States)

    Li, Shunshan; Wei, Min; Tang, Haiying; Zhuang, Tiange; Buonocore, Michael

    2005-01-01

    Image enhancement plays an important role in Fingerprint Recognition System. In this paper fingerprint image enhancement method, a refined Gabor filter, is presented. This enhancement method can connect the ridge breaks, ensures the maximal gray values located at the ridge center and has the ability to compensate for the nonlinear deformations. The result shows it can improve the performance of image enhancement.

  18. Recognition criteria vary with fluctuating uncertainty.

    Science.gov (United States)

    Solomon, Joshua A; Cavanagh, Patrick; Gorea, Andrei

    2012-08-06

    In distinct experiments we examined memories for orientation and size. After viewing a randomly oriented Gabor patch (or a plain white disk of random size), observers were given unlimited time to reproduce as faithfully as possible the orientation (or size) of that standard stimulus with an adjustable Gabor patch (or disk). Then, with this match stimulus still in view, a recognition probe was presented. On half the trials, this probe was identical to the standard. We expected observers to classify the probe (a same/different task) on the basis of its difference from the match, which should have served as an explicit memory of the standard. Observers did better than that. Larger differences were classified as "same" when probe and standard were indeed identical. In some cases, recognition performance exceeded that of a simulated observer subject to the same matching errors, but forced to adopt the single most advantageous criterion difference between the probe and match. Recognition must have used information that was not or could not be exploited in the reproduction phase. One possible source for that information is observers' confidence in their reproduction (e.g., in their memory of the standard). Simulations confirm the enhancement of recognition performance when decision criteria are adjusted trial-by-trial, on the basis of the observer's estimated reproduction error.

  19. Teaching Recognition Skills to Improve Products.

    Science.gov (United States)

    Knight, G. William; And Others

    1990-01-01

    First year dental students (n=86) in a conservative restorations course were taught a discrimination learning paradigm to improve production quality. Evaluation of Class 1 amalgam preparations indicates the improved recognition skills corresponded with improved cavity preparation, supporting the use of this teaching model. (Author/MSE)

  20. Recognition of aircraft using HRR features

    NARCIS (Netherlands)

    Kossen, A.S.

    2008-01-01

    Automated target recognition (ATR) based on high resolution radar (HRR) features can be used to increase the confidence in aircraft class. Standard radar systems are not designed for performing classification and uses additional identification systems. It is shown that with the use of features the a

  1. Semantic description and recognition of patterns

    Institute of Scientific and Technical Information of China (English)

    杨立; 戴汝为

    1996-01-01

    An algebraic semantic approach for the description and recognition of patterns is presented.Specifically,patterns are assumed as algebraic structures,and semantic constraints are given in the form of equational specifications.By such an idea,to recogniz a pattern is to check the validity of an equational conjecture by term rewriting.Such an approach is demonstrated through examples.

  2. Pedestrian recognition using automotive radar sensors

    Science.gov (United States)

    Bartsch, A.; Fitzek, F.; Rasshofer, R. H.

    2012-09-01

    The application of modern series production automotive radar sensors to pedestrian recognition is an important topic in research on future driver assistance systems. The aim of this paper is to understand the potential and limits of such sensors in pedestrian recognition. This knowledge could be used to develop next generation radar sensors with improved pedestrian recognition capabilities. A new raw radar data signal processing algorithm is proposed that allows deep insights into the object classification process. The impact of raw radar data properties can be directly observed in every layer of the classification system by avoiding machine learning and tracking. This gives information on the limiting factors of raw radar data in terms of classification decision making. To accomplish the very challenging distinction between pedestrians and static objects, five significant and stable object features from the spatial distribution and Doppler information are found. Experimental results with data from a 77 GHz automotive radar sensor show that over 95% of pedestrians can be classified correctly under optimal conditions, which is compareable to modern machine learning systems. The impact of the pedestrian's direction of movement, occlusion, antenna beam elevation angle, linear vehicle movement, and other factors are investigated and discussed. The results show that under real life conditions, radar only based pedestrian recognition is limited due to insufficient Doppler frequency and spatial resolution as well as antenna side lobe effects.

  3. Effects of Cognitive Load on Speech Recognition

    Science.gov (United States)

    Mattys, Sven L.; Wiget, Lukas

    2011-01-01

    The effect of cognitive load (CL) on speech recognition has received little attention despite the prevalence of CL in everyday life, e.g., dual-tasking. To assess the effect of CL on the interaction between lexically-mediated and acoustically-mediated processes, we measured the magnitude of the "Ganong effect" (i.e., lexical bias on phoneme…

  4. Speech recognition employing biologically plausible receptive fields

    DEFF Research Database (Denmark)

    Fereczkowski, Michal; Bothe, Hans-Heinrich

    2011-01-01

    The main idea of the project is to build a widely speaker-independent, biologically motivated automatic speech recognition (ASR) system. The two main differences between our approach and current state-of-the-art ASRs are that i) the features used here are based on the responses of neuronlike spec...

  5. Using local alignments for relation recognition

    NARCIS (Netherlands)

    S. Katrenko; P. Adriaans; M. van Someren

    2010-01-01

    This paper discusses the problem of marrying structural similarity with semantic relatedness for Information Extraction from text. Aiming at accurate recognition of relations, we introduce local alignment kernels and explore various possibilities of using them for this task. We give a definition of

  6. Towards physical activity recognition using smartphone sensors

    NARCIS (Netherlands)

    Shoaib, Muhammad; Scholten, Hans; Havinga, P.J.M.

    2013-01-01

    In recent years, the use of a smartphone accelerometer in physical activity recognition has been well studied. However, the role of a gyroscope and a magnetometer is yet to be explored, both when used alone as well as in combination with an accelerometer. For this purpose, we investigate the role of

  7. Facial Action Units Recognition: A Comparative Study

    NARCIS (Netherlands)

    Popa, M.C.; Rothkrantz, L.J.M.; Wiggers, P.; Braspenning, R.A.C.; Shan, C.

    2011-01-01

    Many approaches to facial expression recognition focus on assessing the six basic emotions (anger, disgust, happiness, fear, sadness, and surprise). Real-life situations proved to produce many more subtle facial expressions. A reliable way of analyzing the facial behavior is the Facial Action Coding

  8. Illumination-invariant hand gesture recognition

    Science.gov (United States)

    Mendoza-Morales, América I.; Miramontes-Jaramillo, Daniel; Kober, Vitaly

    2015-09-01

    In recent years, human-computer interaction (HCI) has received a lot of interest in industry and science because it provides new ways to interact with modern devices through voice, body, and facial/hand gestures. The application range of the HCI is from easy control of home appliances to entertainment. Hand gesture recognition is a particularly interesting problem because the shape and movement of hands usually are complex and flexible to be able to codify many different signs. In this work we propose a three step algorithm: first, detection of hands in the current frame is carried out; second, hand tracking across the video sequence is performed; finally, robust recognition of gestures across subsequent frames is made. Recognition rate highly depends on non-uniform illumination of the scene and occlusion of hands. In order to overcome these issues we use two Microsoft Kinect devices utilizing combined information from RGB and infrared sensors. The algorithm performance is tested in terms of recognition rate and processing time.

  9. Iconic and multi-stroke gesture recognition

    NARCIS (Netherlands)

    Willems, D.J.M.; Niels, R.M.J.; Gerven, M.A.J. van; Vuurpijl, L.G.

    2009-01-01

    Many handwritten gestures, characters, and symbols comprise multiple pendown strokes separated by penup strokes. In this paper, a large number of features known from the literature are explored for the recognition of such multi-stroke gestures. Features are computed from a global gesture shape. From

  10. Recognition of Prior Learning: The Participants' Perspective

    Science.gov (United States)

    Miguel, Marta C.; Ornelas, José H.; Maroco, João P.

    2016-01-01

    The current narrative on lifelong learning goes beyond formal education and training, including learning at work, in the family and in the community. Recognition of prior learning is a process of evaluation of those skills and knowledge acquired through life experience, allowing them to be formally recognized by the qualification systems. It is a…

  11. Colour measurement and white blood cell recognition

    CERN Document Server

    Gelsema, E S

    1972-01-01

    As a part of a collaboration with NEMCH aimed at the automation of the differential white blood cell count, studies have been made of the different possibilities for using colour to help in the recognition process. Results are presented comparing data obtained with a microspectrophotometer and with a simulated three-colour scanner.

  12. Emotion recognition a pattern analysis approach

    CERN Document Server

    Konar, Amit

    2014-01-01

    Offers both foundations and advances on emotion recognition in a single volumeProvides a thorough and insightful introduction to the subject by utilizing computational tools of diverse domainsInspires young researchers to prepare themselves for their own researchDemonstrates direction of future research through new technologies, such as Microsoft Kinect, EEG systems etc.

  13. Risk Recognition and Intimate Partner Violence

    Science.gov (United States)

    Witte, Tricia H.; Kendra, Rachel

    2010-01-01

    The objective of this study was to determine whether female victims of physical forms of intimate partner violence (IPV) displayed deficits in risk recognition, or the ability to detect danger, in physically violent dating encounters. A total of 182 women watched a video depicting a psychologically and physically aggressive encounter between…

  14. Conditional Random Fields for Activity Recognition

    Science.gov (United States)

    2008-04-01

    are important for accurate recognition. Huynh and Schiele used features such as fast Fourier transform coefficients computed over windows of...Friedman. The Elements of Statistical Learning. Springer, August 2001. [40] P.J. Hubert. Robust Statistics. Wiley, 1981. [41] Tâm Huynh and Bernt Schiele

  15. Transfer learning for bimodal biometrics recognition

    Science.gov (United States)

    Dan, Zhiping; Sun, Shuifa; Chen, Yanfei; Gan, Haitao

    2013-10-01

    Biometrics recognition aims to identify and predict new personal identities based on their existing knowledge. As the use of multiple biometric traits of the individual may enables more information to be used for recognition, it has been proved that multi-biometrics can produce higher accuracy than single biometrics. However, a common problem with traditional machine learning is that the training and test data should be in the same feature space, and have the same underlying distribution. If the distributions and features are different between training and future data, the model performance often drops. In this paper, we propose a transfer learning method for face recognition on bimodal biometrics. The training and test samples of bimodal biometric images are composed of the visible light face images and the infrared face images. Our algorithm transfers the knowledge across feature spaces, relaxing the assumption of same feature space as well as same underlying distribution by automatically learning a mapping between two different but somewhat similar face images. According to the experiments in the face images, the results show that the accuracy of face recognition has been greatly improved by the proposed method compared with the other previous methods. It demonstrates the effectiveness and robustness of our method.

  16. Early recognition of basal cell naevus syndrome

    NARCIS (Netherlands)

    Veenstra-Knol, HE; Scheewe, JH; van der Vlist, GJ; van Doorn, ME; Ausems, MGEM

    2005-01-01

    The basal cell naevus syndrome is an autosomal dominant syndrome characterised by major manifestations such as basal cell carcinomas, jaw cysts, palmar or plantar pits, and intracranial calcifications. Early recognition is important in order to reduce morbidity due to cutaneous and cerebral malignan

  17. Employee Recognition and Performance: A Field Experiment

    NARCIS (Netherlands)

    C. Bradler (Christiane); A.J. Dur (Robert); S. Neckermann (Susanne); J.A. Non (Arjan)

    2013-01-01

    textabstractThis paper reports the results from a controlled field experiment designed to investigate the causal effect of public recognition on employee performance. We hired more than 300 employees to work on a three-hour data-entry task. In a random sample of work groups, workers unexpectedly rec

  18. Optical correlation recognition based on LCOS

    Science.gov (United States)

    Tang, Mingchuan; Wu, Jianhong

    2013-08-01

    Vander-Lugt correlator[1] plays an important role in optical pattern recognition due to the characteristics of accurate positioning and high signal-to-noise ratio. The ideal Vander-Lugt correlator should have the ability of outputting strong and sharp correlation peak in allusion to the true target, in the existing Spatial Light Modulators[2], Liquid Crystal On Silicon(LCOS) has been the most competitive candidate for the matched filter owing to the continuous phase modulation peculiarity. Allowing for the distortions of the target to be identified including rotations, scaling changes, perspective changes, which can severely impact the correlation recognition results, herein, we present a modified Vander-Lugt correlator based on the LCOS by means of applying an iterative algorithm to the design of the filter so that the correlator can invariant to the distortions while maintaining good performance. The results of numerical simulation demonstrate that the filter could get the similar recognition results for all the training images. And the experiment shows that the modified correlator achieves the 180° rotating tolerance significantly improving the recognition efficiency of the correlator.

  19. Symposium 'The politics of international recognition'

    NARCIS (Netherlands)

    Agne, Hans; Bartelson, Jens; Erman, Eva; Lindemann, Thomas; Herborth, Benjamin; Kessler, Oliver; Chwaszcza, Christine; Fabry, Mikulas; Krasner, Stephen D.

    2013-01-01

    Recognition plays a multifaceted role in international theory. In rarely communicating literatures, the term is invoked to explain creation of new states and international structures; policy choices by state and non-state actors; and normative justifiability, or lack thereof, of foreign and internat

  20. Hidden Conditional Random Fields for Action Recognition

    NARCIS (Netherlands)

    Chen, L.; van der Aa, N.P.; Tan, R.T.; Veltkamp, R.C.

    2014-01-01

    In the field of action recognition, the design of features has been explored extensively, but the choice of action classification methods is limited. Commonly used classification methods like k-Nearest Neighbors and Support Vector Machines assume conditional independency between features. In contras

  1. Grip-Pattern Recognition for Smart Guns

    NARCIS (Netherlands)

    Kauffman, J.A.; Bazen, A.M.; Gerez, S.H.; Veldhuis, R.N.J.

    2003-01-01

    This paper describes the design, implementation and evaluation of a user-verification system for a smart gun, which is based on grip-pattern recognition. An existing pressure sensor consisting of an array of 44 x 44 piezoresistive elements has been used. An interface has been developed to acquire pr

  2. The recognition of equivariant bifurcation problems

    Institute of Scientific and Technical Information of China (English)

    李养成

    1996-01-01

    The orbit of an equivariant bifurcation problem with multiparameter is characterized under the action of the group of unipotent equivalences. When the unipotent tangent space is invariant under unipotent equivalences, the recognition problem can be solved by just using linear algebra. Sufficient conditions for a subspace to be intrinsic subspace under unipotent equivalences are given.

  3. A new approach for sclera vein recognition

    Science.gov (United States)

    Thomas, N. L.; Du, Yingzi; Zhou, Zhi

    2010-04-01

    The vein structure in the sclera is stable over time, unique to each person, and well suited for human identification. A few researchers have performed sclera vein pattern recognition and reported promising initial results. Sclera recognition poses several challenges: the vein structure moves and deforms with the movement of the eye; images of sclera patterns are often defocused and/or saturated; and, most importantly, the vein structure in the sclera is multi-layered and has complex non-linear deformation. In this paper, we proposed a new method for sclera recognition: First, we developed a color-based sclera region estimation scheme for sclera segmentation. Second, we designed a Gabor wavelet-based sclera pattern enhancement method, and an adaptive thresholding method to emphasize and binarize the sclera vein patterns. Third, we proposed a line descriptor-based feature extraction, registration, and matching method that is illumination-, scale-, orientation-, and deformation-invariant, and can mitigate the multi-layered deformation effects exhibited in the sclera and tolerate segmentation error. It is empirically verified using the UBIRIS database that the proposed method can perform accurate sclera recognition.

  4. Unpacking Recognition and Esteem in School Pedagogies

    Science.gov (United States)

    Wulf, Christoph; Bittner, Martin; Clemens, Iris; Kellermann, Ingrid

    2012-01-01

    The article focuses on pedagogical practices of recognition and esteem (Wertschatzung) and on the question of how those practices can be appropriately studied and epistemologically grasped. The investigation involves an inner-city elementary school in a socio-economically problematic district. With regard to the communication forms in this…

  5. Molecular recognition: The I's have it

    Science.gov (United States)

    Taylor, Mark S.

    2014-12-01

    Rotaxanes with cyclodextrin end groups have been used as a platform to investigate anion binding in water, revealing that halogen bonding can serve as the basis for molecular recognition in aqueous solvents, which may have implications in medicinal chemistry and beyond.

  6. Music Education Intervention Improves Vocal Emotion Recognition

    Science.gov (United States)

    Mualem, Orit; Lavidor, Michal

    2015-01-01

    The current study is an interdisciplinary examination of the interplay among music, language, and emotions. It consisted of two experiments designed to investigate the relationship between musical abilities and vocal emotional recognition. In experiment 1 (N = 24), we compared the influence of two short-term intervention programs--music and…

  7. Employee recognition and performance: A field experiment

    NARCIS (Netherlands)

    Bradler, C.; Dur, R.; Neckermann, S.; Non, J.A.

    2013-01-01

    This paper reports the results from a controlled field experiment designed to investigate the causal effect of public recognition on employee performance. We hired more than 300 employees to work on a three-hour data-entry task. In a random sample of work groups, workers unexpectedly received recogn

  8. A human benchmark for language recognition

    NARCIS (Netherlands)

    Orr, R.; Leeuwen, D.A. van

    2009-01-01

    In this study, we explore a human benchmark in language recognition, for the purpose of comparing human performance to machine performance in the context of the NIST LRE 2007. Humans are categorised in terms of language proficiency, and performance is presented per proficiency. Themain challenge in

  9. Plastic Antibodies: Molecular Recognition with Imprinted Polymers

    Science.gov (United States)

    Rushton, Gregory T.; Furmanski, Brian; Shimizu, Ken D.

    2005-01-01

    Synthetic polymers are prepared and tested in a study for their molecular recognition properties of an adenine derivative, ethyl adenine-9-acetate (EA9A), within two laboratory periods. The procedure introduces undergraduate chemistry students to noncovalent molecular imprinting as well as the analytical techniques for assessing their recognition…

  10. Recognition of International Education in Japanese Teachers

    Science.gov (United States)

    Yoshida, Masami

    2017-01-01

    Education for international understanding in Japan was focused to develop its own national identity as well as to recognize its coexistence through intercultural education. Then, we have investigated the opinions of Japanese school teachers in terms of their recognition of the necessary content to introduce school instruction of intercultural…

  11. Influence of motion on face recognition.

    Science.gov (United States)

    Bonfiglio, Natale S; Manfredi, Valentina; Pessa, Eliano

    2012-02-01

    The influence of motion information and temporal associations on recognition of non-familiar faces was investigated using two groups which performed a face recognition task. One group was presented with regular temporal sequences of face views designed to produce the impression of motion of the face rotating in depth, the other group with random sequences of the same views. In one condition, participants viewed the sequences of the views in rapid succession with a negligible interstimulus interval (ISI). This condition was characterized by three different presentation times. In another condition, participants were presented a sequence with a 1-sec. ISI among the views. That regular sequences of views with a negligible ISI and a shorter presentation time were hypothesized to give rise to better recognition, related to a stronger impression of face rotation. Analysis of data from 45 participants showed a shorter presentation time was associated with significantly better accuracy on the recognition task; however, differences between performances associated with regular and random sequences were not significant.

  12. Face recognition increases during saccade preparation.

    Science.gov (United States)

    Lin, Hai; Rizak, Joshua D; Ma, Yuan-ye; Yang, Shang-chuan; Chen, Lin; Hu, Xin-tian

    2014-01-01

    Face perception is integral to human perception system as it underlies social interactions. Saccadic eye movements are frequently made to bring interesting visual information, such as faces, onto the fovea for detailed processing. Just before eye movement onset, the processing of some basic features, such as the orientation, of an object improves at the saccade landing point. Interestingly, there is also evidence that indicates faces are processed in early visual processing stages similar to basic features. However, it is not known whether this early enhancement of processing includes face recognition. In this study, three experiments were performed to map the timing of face presentation to the beginning of the eye movement in order to evaluate pre-saccadic face recognition. Faces were found to be similarly processed as simple objects immediately prior to saccadic movements. Starting ∼ 120 ms before a saccade to a target face, independent of whether or not the face was surrounded by other faces, the face recognition gradually improved and the critical spacing of the crowding decreased as saccade onset was approaching. These results suggest that an upcoming saccade prepares the visual system for new information about faces at the saccade landing site and may reduce the background in a crowd to target the intended face. This indicates an important role of pre-saccadic eye movement signals in human face recognition.

  13. Humoral pattern recognition and the complement system.

    Science.gov (United States)

    Degn, S E; Thiel, S

    2013-08-01

    In the context of immunity, pattern recognition is the art of discriminating friend from foe and innocuous from noxious. The basis of discrimination is the existence of evolutionarily conserved patterns on microorganisms, which are intrinsic to these microorganisms and necessary for their function and existence. Such immutable or slowly evolving patterns are ideal handles for recognition and have been targeted by early cellular immune defence mechanisms such as Toll-like receptors, NOD-like receptors, RIG-I-like receptors, C-type lectin receptors and by humoral defence mechanisms such as the complement system. Complement is a proteolytic cascade system comprising around 35 different soluble and membrane-bound proteins. It constitutes a central part of the innate immune system, mediating several major innate effector functions and modulating adaptive immune responses. The complement cascade proceeds via controlled, limited proteolysis and conformational changes of constituent proteins through three activation pathways: the classical pathway, the alternative pathway and the lectin pathway, which converge in common effector functions. Here, we review the nature of the pattern recognition molecules involved in complement activation, as well as their close relatives with no or unknown capacity for activating complement. We proceed to examine the composition of the pattern recognition complexes involved in complement activation, focusing on those of the lectin pathway, and arrive at a new model for their mechanism of operation, supported by recently emerging evidence.

  14. Conformal Predictions in Multimedia Pattern Recognition

    Science.gov (United States)

    Nallure Balasubramanian, Vineeth

    2010-01-01

    The fields of pattern recognition and machine learning are on a fundamental quest to design systems that can learn the way humans do. One important aspect of human intelligence that has so far not been given sufficient attention is the capability of humans to express when they are certain about a decision, or when they are not. Machine learning…

  15. Object recognition with hierarchical discriminant saliency networks.

    Science.gov (United States)

    Han, Sunhyoung; Vasconcelos, Nuno

    2014-01-01

    The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

  16. Chemical mediation of coral larval settlement by crustose coralline algae.

    Science.gov (United States)

    Tebben, J; Motti, C A; Siboni, Nahshon; Tapiolas, D M; Negri, A P; Schupp, P J; Kitamura, Makoto; Hatta, Masayuki; Steinberg, P D; Harder, T

    2015-06-04

    The majority of marine invertebrates produce dispersive larvae which, in order to complete their life cycles, must attach and metamorphose into benthic forms. This process, collectively referred to as settlement, is often guided by habitat-specific cues. While the sources of such cues are well known, the links between their biological activity, chemical identity, presence and quantification in situ are largely missing. Previous work on coral larval settlement in vitro has shown widespread induction by crustose coralline algae (CCA) and in particular their associated bacteria. However, we found that bacterial biofilms on CCA did not initiate ecologically realistic settlement responses in larvae of 11 hard coral species from Australia, Guam, Singapore and Japan. We instead found that algal chemical cues induce identical behavioral responses of larvae as per live CCA. We identified two classes of CCA cell wall-associated compounds--glycoglycerolipids and polysaccharides--as the main constituents of settlement inducing fractions. These algae-derived fractions induce settlement and metamorphosis at equivalent concentrations as present in CCA, both in small scale laboratory assays and under flow-through conditions, suggesting their ability to act in an ecologically relevant fashion to steer larval settlement of corals. Both compound classes were readily detected in natural samples.

  17. Doping graphene films via chemically mediated charge transfer

    Directory of Open Access Journals (Sweden)

    Ishikawa Ryousuke

    2011-01-01

    Full Text Available Abstract Transparent conductive films (TCFs are critical components of a myriad of technologies including flat panel displays, light-emitting diodes, and solar cells. Graphene-based TCFs have attracted a lot of attention because of their high electrical conductivity, transparency, and low cost. Carrier doping of graphene would potentially improve the properties of graphene-based TCFs for practical industrial applications. However, controlling the carrier type and concentration of dopants in graphene films is challenging, especially for the synthesis of p-type films. In this article, a new method for doping graphene using the conjugated organic molecule, tetracyanoquinodimethane (TCNQ, is described. Notably, TCNQ is well known as a powerful electron accepter and is expected to favor electron transfer from graphene into TCNQ molecules, thereby leading to p-type doping of graphene films. Small amounts of TCNQ drastically improved the resistivity without degradation of optical transparency. Our carrier doping method based on charge transfer has a huge potential for graphene-based TCFs.

  18. Visual body recognition in a prosopagnosic patient.

    Science.gov (United States)

    Moro, V; Pernigo, S; Avesani, R; Bulgarelli, C; Urgesi, C; Candidi, M; Aglioti, S M

    2012-01-01

    Conspicuous deficits in face recognition characterize prosopagnosia. Information on whether agnosic deficits may extend to non-facial body parts is lacking. Here we report the neuropsychological description of FM, a patient affected by a complete deficit in face recognition in the presence of mild clinical signs of visual object agnosia. His deficit involves both overt and covert recognition of faces (i.e. recognition of familiar faces, but also categorization of faces for gender or age) as well as the visual mental imagery of faces. By means of a series of matching-to-sample tasks we investigated: (i) a possible association between prosopagnosia and disorders in visual body perception; (ii) the effect of the emotional content of stimuli on the visual discrimination of faces, bodies and objects; (iii) the existence of a dissociation between identity recognition and the emotional discrimination of faces and bodies. Our results document, for the first time, the co-occurrence of body agnosia, i.e. the visual inability to discriminate body forms and body actions, and prosopagnosia. Moreover, the results show better performance in the discrimination of emotional face and body expressions with respect to body identity and neutral actions. Since FM's lesions involve bilateral fusiform areas, it is unlikely that the amygdala-temporal projections explain the relative sparing of emotion discrimination performance. Indeed, the emotional content of the stimuli did not improve the discrimination of their identity. The results hint at the existence of two segregated brain networks involved in identity and emotional discrimination that are at least partially shared by face and body processing.

  19. Integration trumps selection in object recognition.

    Science.gov (United States)

    Saarela, Toni P; Landy, Michael S

    2015-03-30

    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 [4], 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 [9]. 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.

  20. A neuromorphic system for video object recognition.

    Science.gov (United States)

    Khosla, Deepak; Chen, Yang; Kim, Kyungnam

    2014-01-01

    Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS), is inspired by computational neuroscience models of feed-forward object detection and classification pipelines for processing visual data. The NEOVUS architecture is inspired by the ventral (what) and dorsal (where) streams of the mammalian visual pathway and integrates retinal processing, object detection based on form and motion modeling, and object classification based on convolutional neural networks. The object recognition performance and energy use of the NEOVUS was evaluated by the Defense Advanced Research Projects Agency (DARPA) under the Neovision2 program using three urban area video datasets collected from a mix of stationary and moving platforms. These datasets are challenging and include a large number of objects of different types in cluttered scenes, with varying illumination and occlusion conditions. In a systematic evaluation of five different teams by DARPA on these datasets, the NEOVUS demonstrated the best performance with high object recognition accuracy and the lowest energy consumption. Its energy use was three orders of magnitude lower than two independent state of the art baseline computer vision systems. The dynamic power requirement for the complete system mapped to commercial off-the-shelf (COTS) hardware that includes a 5.6 Megapixel color camera processed by object detection and classification algorithms at 30 frames per second was measured at 21.7 Watts (W), for an effective energy consumption of 5.45 nanoJoules (nJ) per bit of incoming video. These unprecedented results show that the NEOVUS has the potential to revolutionize automated video object recognition toward enabling practical low-power and mobile video processing

  1. A Novel Neural Network Based Method Developed for Digit Recognition Applied to Automatic Speed Sign Recognition

    Directory of Open Access Journals (Sweden)

    Hanene Rouabeh

    2016-02-01

    Full Text Available This Paper presents a new hybrid technique for digit recognition applied to the speed limit sign recognition task. The complete recognition system consists in the detection and recognition of the speed signs in RGB images. A pretreatment is applied to extract the pictogram from a detected circular road sign, and then the task discussed in this work is employed to recognize digit candidates. To realize a compromise between performances, reduced execution time and optimized memory resources, the developed method is based on a conjoint use of a Neural Network and a Decision Tree. A simple Network is employed firstly to classify the extracted candidates into three classes and secondly a small Decision Tree is charged to determine the exact information. This combination is used to reduce the size of the Network as well as the memory resources utilization. The evaluation of the technique and the comparison with existent methods show the effectiveness.

  2. Recognition and Exteriority: Towards a Recognition-Theoretic Account of Globalization

    Directory of Open Access Journals (Sweden)

    Sebastian Purcell

    2011-06-01

    Full Text Available This essay aims to extend Paul Ricœur’s account of recognition to address some of the concerns of globalization, especially those voiced by Enrique Dussel. The extension is accomplished in two parts.  First, Dussel’s account of spatial existence as dwelling is reviewed as it is pertinent to the concerns of globalization.  Next, it is demonstrated that each of the aspects of Ricœur’s account of recognition may be given a spatial re-articulation.  The results thus establish an outline of how recognition theory might address some of the concerns of globalization.  The essay concludes with several consequences for the modification of recognition politics as one finds it in the late work of Ricœur and in Axel Honneth’s ongoing inquiries. 

  3. Traffic Sign Recognition with High Accuracy Using Mixture of Experts

    Directory of Open Access Journals (Sweden)

    Reza Azad

    2014-06-01

    Full Text Available Traffic signs provide the driver various information for safe and efficient navigation. Automatic recognition of traffic signs is, therefore, important for automated driving or driver assistance systems.In this paper, a new and efficient traffic sign recognition system based on extracting diverse feature set, and applying mixture of experts'architecture on the extracted featuresis proposed.In the result part, the proposed approach is evaluated on the German traffic sign recognition and Grigorescu traffic signsbenchmark and high recognition rate is achieved.Comparison with some of the most related methods indicates that the proposed novel model yields excellent recognition rate in traffic sign recognition that is the recognition rate of 99.94% for the training set and 98.50% for the test set.In addition, experimental results have demonstrated our method robust in successful recognition of traffic signs even with variant lighting.

  4. The Elementary Private School Recognition Program: Mike Mulligan's View.

    Science.gov (United States)

    Lodish, Richard

    1986-01-01

    Describes the goals, the selection criteria, and the selection process of the Elementary Private School Recognition Program. Includes a listing, by states, of the 60 private elementary schools selected for 1985-86 recognition. (IW)

  5. Arabic Speech Recognition System using CMU-Sphinx4

    CERN Document Server

    Satori, H; Chenfour, N

    2007-01-01

    In this paper we present the creation of an Arabic version of Automated Speech Recognition System (ASR). This system is based on the open source Sphinx-4, from the Carnegie Mellon University. Which is a speech recognition system based on discrete hidden Markov models (HMMs). We investigate the changes that must be made to the model to adapt Arabic voice recognition. Keywords: Speech recognition, Acoustic model, Arabic language, HMMs, CMUSphinx-4, Artificial intelligence.

  6. Semantic information can facilitate covert face recognition in congenital prosopagnosia.

    Science.gov (United States)

    Rivolta, Davide; Schmalzl, Laura; Coltheart, Max; Palermo, Romina

    2010-11-01

    People with congenital prosopagnosia have never developed the ability to accurately recognize faces. This single case investigation systematically investigates covert and overt face recognition in "C.," a 69 year-old woman with congenital prosopagnosia. Specifically, we: (a) describe the first assessment of covert face recognition in congenital prosopagnosia using multiple tasks; (b) show that semantic information can contribute to covert recognition; and (c) provide a theoretical explanation for the mechanisms underlying covert face recognition.

  7. Framework of Pattern Recognition Model Based on the Cognitive Psychology

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    According to the fundamental theory of visual cognition mechanism and cognitive psychology,the visual pattern recognition model is introduced briefly.Three pattern recognition models,i.e.template-based matching model,prototype-based matching model and feature-based matching model are built and discussed separately.In addition,the influence of object background information and visual focus point to the result of pattern recognition is also discussed with the example of recognition for fuzzy letters and figures.

  8. Comparison of Emotion Recognition from Facial Expression and Music

    OpenAIRE

    Gašpar, Tina; Labor, Marina; Jurić, Iva; Dumančić, Dijana; Ilakovac, Vesna; Heffer, Marija

    2011-01-01

    The recognition of basic emotions in everyday communication involves interpretation of different visual and auditory clues. The ability to recognize emotions is not clearly determined as their presentation is usually very short (micro expressions), whereas the recognition itself does not have to be a conscious process. We assumed that the recognition from facial expressions is selected over the recognition of emotions communicated through music. In order to compare the success rate in recogni...

  9. Indirect readout in protein-peptide recognition: a different story from classical biomolecular recognition.

    Science.gov (United States)

    Yu, Hua; Zhou, Peng; Deng, Maolin; Shang, Zhicai

    2014-07-28

    Protein-peptide interactions are prevalent and play essential roles in many living activities. Peptides recognize their protein partners by direct nonbonded interactions and indirect adjustment of conformations. Although processes of protein-peptide recognition have been comprehensively studied in both sequences and structures recently, flexibility of peptides and the configuration entropy penalty in recognition did not get enough attention. In this study, 20 protein-peptide complexes and their corresponding unbound peptides were investigated by molecular dynamics simulations. Energy analysis revealed that configurational entropy penalty introduced by restriction of the degrees of freedom of peptides in indirect readout process of protein-peptide recognition is significant. Configurational entropy penalty has become the main content of the indirect readout energy in protein-peptide recognition instead of deformation energy which is the main source of the indirect readout energy in classical biomolecular recognition phenomena, such as protein-DNA binding. These results provide us a better understanding of protein-peptide recognition and give us some implications in peptide ligand design.

  10. Recognition memory in developmental prosopagnosia: electrophysiological evidence for abnormal routes to face recognition.

    Science.gov (United States)

    Burns, Edwin J; Tree, Jeremy J; Weidemann, Christoph T

    2014-01-01

    DUAL PROCESS MODELS OF RECOGNITION MEMORY PROPOSE TWO DISTINCT ROUTES FOR RECOGNIZING A FACE: recollection and familiarity. Recollection is characterized by the remembering of some contextual detail from a previous encounter with a face whereas familiarity is the feeling of finding a face familiar without any contextual details. The Remember/Know (R/K) paradigm is thought to index the relative contributions of recollection and familiarity to recognition performance. Despite researchers measuring face recognition deficits in developmental prosopagnosia (DP) through a variety of methods, none have considered the distinct contributions of recollection and familiarity to recognition performance. The present study examined recognition memory for faces in eight individuals with DP and a group of controls using an R/K paradigm while recording electroencephalogram (EEG) data at the scalp. Those with DP were found to produce fewer correct "remember" responses and more false alarms than controls. EEG results showed that posterior "remember" old/new effects were delayed and restricted to the right posterior (RP) area in those with DP in comparison to the controls. A posterior "know" old/new effect commonly associated with familiarity for faces was only present in the controls whereas individuals with DP exhibited a frontal "know" old/new effect commonly associated with words, objects and pictures. These results suggest that individuals with DP do not utilize normal face-specific routes when making face recognition judgments but instead process faces using a pathway more commonly associated with objects.

  11. Recognition Memory in Developmental Prosopagnosia: Electrophysiological Evidence for Abnormal Routes to Face Recognition

    Directory of Open Access Journals (Sweden)

    Edwin James Burns

    2014-08-01

    Full Text Available Dual process models of recognition memory propose two distinct routes for recognizing a face: recollection and familiarity. Recollection is characterized by the remembering of some contextual detail from a previous encounter with a face whereas familiarity is the feeling of finding a face familiar without any contextual details. The Remember/Know (R/K paradigm is thought to index the relative contributions of recollection and familiarity to recognition performance. Despite researchers measuring face recognition deficits in developmental prosopagnosia (DP through a variety of methods, none have considered the distinct contributions of recollection and familiarity to recognition performance. The present study examined recognition memory for faces in 8 individuals with DP and a group of controls using an R/K paradigm while recording electroencephalogram (EEG data at scalp. Those with DP were found to produce fewer correct remember responses and more false alarms than controls. EEG results showed that posterior remember old/new effects were delayed and restricted to the right posterior area in those with DP in comparison to the controls. A posterior know old/new effect commonly associated with familiarity for faces was only present in the controls whereas individuals with DP exhibited a frontal know old/new effect commonly associated with words, objects and pictures. These results suggest that individuals with DP do not utilize normal face specific routes when making face recognition judgments but instead process faces using a pathway more commonly associated with objects.

  12. Setting a world record in 3D face recognition

    NARCIS (Netherlands)

    Spreeuwers, Luuk

    2015-01-01

    Biometrics - recognition of persons based on how they look or behave, is the main subject of research at the Chair of Biometric Pattern Recognition (BPR) of the Services, Cyber Security and Safety Group (SCS) of the EEMCS Faculty at the University of Twente. Examples are finger print recognition, ir

  13. Recognition without Identification for Words, Pseudowords and Nonwords

    Science.gov (United States)

    Arndt, Jason; Lee, Karen; Flora, David B.

    2008-01-01

    Three experiments examined whether the representations underlying recognition memory familiarity can be episodic in nature. Recognition without identification [Cleary, A. M., & Greene, R. L. (2000). Recognition without identification. "Journal of Experimental Psychology: Learning, Memory, and Cognition," 26, 1063-1069; Peynircioglu, Z. F. (1990).…

  14. An Optical Character Recognition for Handwritten Devanagari Script

    Directory of Open Access Journals (Sweden)

    Trupti R. Zalke

    2015-01-01

    Full Text Available Optical Character Recognition is process of recognition of character from scanned document and lots of OCR now available in the market. But most of these systems work for Roman, Chinese, Japanese and Arabic characters . There are no sufficient number of work on Indian language script like Devanagari so this paper present a review on optical character recognition on handwritten Devanagari script.

  15. Automatic TLI recognition system, user`s guide

    Energy Technology Data Exchange (ETDEWEB)

    Lassahn, G.D.

    1997-02-01

    This report describes how to use an automatic target recognition system (version 14). In separate volumes are a general description of the ATR system, Automatic TLI Recognition System, General Description, and a programmer`s manual, Automatic TLI Recognition System, Programmer`s Guide.

  16. Recognition and Accountability: Sole Parent Postgraduates in University Conditions

    Science.gov (United States)

    Hook, Genine A.

    2015-01-01

    This paper aims to examine some of ways sole parents sought recognition as postgraduate students in Australian universities. Judith Butler's theory of recognition notes that recognition is always partial and any account we give of ourselves must be given to another. Participants articulated that supervisors were critical in the process of…

  17. Object Recognition with Stereo Vision and Geometric Hashing

    NARCIS (Netherlands)

    Dijck, van Hendrikus Alfonsus Ludovicus

    1999-01-01

    The subject of this thesis is the automatic recognition of objects from digital images. The discussion is restricted to recognition of man made objects that can be described by deterministic, structural models. Applications of this kind of recognition tasks can be found in industry. Object recogniti

  18. Relations among Early Object Recognition Skills: Objects and Letters

    Science.gov (United States)

    Augustine, Elaine; Jones, Susan S.; Smith, Linda B.; Longfield, Erica

    2015-01-01

    Human visual object recognition is multifaceted and comprised of several domains of expertise. Developmental relations between young children's letter recognition and their 3-dimensional object recognition abilities are implicated on several grounds but have received little research attention. Here, we ask how preschoolers' success in recognizing…

  19. 46 CFR 8.220 - Recognition of a classification society.

    Science.gov (United States)

    2010-10-01

    ... 46 Shipping 1 2010-10-01 2010-10-01 false Recognition of a classification society. 8.220 Section 8... INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.220 Recognition of a classification society. (a) A classification society must be recognized by the Commandant before it may receive...

  20. Recognition and Toleration: Conflicting Approaches to Diversity in Education?

    Science.gov (United States)

    Laegaard, Sune

    2010-01-01

    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…

  1. Phonological modeling for continuous speech recognition in Korean

    CERN Document Server

    Lee, W I; Lee, J H; Lee, WonIl; Lee, Geunbae; Lee, Jong-Hyeok

    1996-01-01

    A new scheme to represent phonological changes during continuous speech recognition is suggested. A phonological tag coupled with its morphological tag is designed to represent the conditions of Korean phonological changes. A pairwise language model of these morphological and phonological tags is implemented in Korean speech recognition system. Performance of the model is verified through the TDNN-based speech recognition experiments.

  2. Electrolarynx Voice Recognition Utilizing Pulse Coupled Neural Network

    Directory of Open Access Journals (Sweden)

    Fatchul Arifin

    2010-08-01

    Full Text Available The laryngectomies patient has no ability to speak normally because their vocal chords have been removed. The easiest option for the patient to speak again is by using electrolarynx speech. This tool is placed on the lower chin. Vibration of the neck while speaking is used to produce sound. Meanwhile, the technology of "voice recognition" has been growing very rapidly. It is expected that the technology of "voice recognition" can also be used by laryngectomies patients who use electrolarynx.This paper describes a system for electrolarynx speech recognition. Two main parts of the system are feature extraction and pattern recognition. The Pulse Coupled Neural Network – PCNN is used to extract the feature and characteristic of electrolarynx speech. Varying of β (one of PCNN parameter also was conducted. Multi layer perceptron is used to recognize the sound patterns. There are two kinds of recognition conducted in this paper: speech recognition and speaker recognition. The speech recognition recognizes specific speech from every people. Meanwhile, speaker recognition recognizes specific speech from specific person. The system ran well. The "electrolarynx speech recognition" has been tested by recognizing of “A” and "not A" voice. The results showed that the system had 94.4% validation. Meanwhile, the electrolarynx speaker recognition has been tested by recognizing of “saya” voice from some different speakers. The results showed that the system had 92.2% validation. Meanwhile, the best β parameter of PCNN for electrolarynx recognition is 3.

  3. Cross-linguistic emotion recognition : Dutch, Korean and American English

    NARCIS (Netherlands)

    Choi, J.P.; Broersma, M.; Goudbeek, M.B.

    2012-01-01

    This study investigates the occurrence of asymmetries in cross-linguistic recognition of emotion in speech. Theories on emotion recognition do not consider asymmetries in the cross-linguistic recognition of emotion. To study perceptual asymmetries, a fully crossed design was used, with speakers and

  4. The Role of Perceptual Load in Object Recognition

    Science.gov (United States)

    Lavie, Nilli; Lin, Zhicheng; Zokaei, Nahid; Thoma, Volker

    2009-01-01

    Predictions from perceptual load theory (Lavie, 1995, 2005) regarding object recognition across the same or different viewpoints were tested. Results showed that high perceptual load reduces distracter recognition levels despite always presenting distracter objects from the same view. They also showed that the levels of distracter recognition were…

  5. Improved Open-Microphone Speech Recognition

    Science.gov (United States)

    Abrash, Victor

    2002-01-01

    Many current and future NASA missions make extreme demands on mission personnel both in terms of work load and in performing under difficult environmental conditions. In situations where hands are impeded or needed for other tasks, eyes are busy attending to the environment, or tasks are sufficiently complex that ease of use of the interface becomes critical, spoken natural language dialog systems offer unique input and output modalities that can improve efficiency and safety. They also offer new capabilities that would not otherwise be available. For example, many NASA applications require astronauts to use computers in micro-gravity or while wearing space suits. Under these circumstances, command and control systems that allow users to issue commands or enter data in hands-and eyes-busy situations become critical. Speech recognition technology designed for current commercial applications limits the performance of the open-ended state-of-the-art dialog systems being developed at NASA. For example, today's recognition systems typically listen to user input only during short segments of the dialog, and user input outside of these short time windows is lost. Mistakes detecting the start and end times of user utterances can lead to mistakes in the recognition output, and the dialog system as a whole has no way to recover from this, or any other, recognition error. Systems also often require the user to signal when that user is going to speak, which is impractical in a hands-free environment, or only allow a system-initiated dialog requiring the user to speak immediately following a system prompt. In this project, SRI has developed software to enable speech recognition in a hands-free, open-microphone environment, eliminating the need for a push-to-talk button or other signaling mechanism. The software continuously captures a user's speech and makes it available to one or more recognizers. By constantly monitoring and storing the audio stream, it provides the spoken

  6. Transfer-Appropriate Processing in Recognition Memory: Perceptual and Conceptual Effects on Recognition Memory Depend on Task Demands

    Science.gov (United States)

    Parks, Colleen M.

    2013-01-01

    Research examining the importance of surface-level information to familiarity in recognition memory tasks is mixed: Sometimes it affects recognition and sometimes it does not. One potential explanation of the inconsistent findings comes from the ideas of dual process theory of recognition and the transfer-appropriate processing framework, which…

  7. Combined Hand Gesture — Speech Model for Human Action Recognition

    Directory of Open Access Journals (Sweden)

    Sheng-Tzong Cheng

    2013-12-01

    Full Text Available This study proposes a dynamic hand gesture detection technology to effectively detect dynamic hand gesture areas, and a hand gesture recognition technology to improve the dynamic hand gesture recognition rate. Meanwhile, the corresponding relationship between state sequences in hand gesture and speech models is considered by integrating speech recognition technology with a multimodal model, thus improving the accuracy of human behavior recognition. The experimental results proved that the proposed method can effectively improve human behavior recognition accuracy and the feasibility of system applications. Experimental results verified that the multimodal gesture-speech model provided superior accuracy when compared to the single modal versions.

  8. Combined hand gesture--speech model for human action recognition.

    Science.gov (United States)

    Cheng, Sheng-Tzong; Hsu, Chih-Wei; Li, Jian-Pan

    2013-12-12

    This study proposes a dynamic hand gesture detection technology to effectively detect dynamic hand gesture areas, and a hand gesture recognition technology to improve the dynamic hand gesture recognition rate. Meanwhile, the corresponding relationship between state sequences in hand gesture and speech models is considered by integrating speech recognition technology with a multimodal model, thus improving the accuracy of human behavior recognition. The experimental results proved that the proposed method can effectively improve human behavior recognition accuracy and the feasibility of system applications. Experimental results verified that the multimodal gesture-speech model provided superior accuracy when compared to the single modal versions.

  9. White matter tracts critical for recognition of sarcasm.

    Science.gov (United States)

    Davis, Cameron L; Oishi, Kenichi; Faria, Andreia V; Hsu, John; Gomez, Yessenia; Mori, Susumu; Hillis, Argye E

    2016-01-01

    Failure to recognize sarcasm can lead to important miscommunications. Few previous studies have identified brain lesions associated with impaired recognition of sarcasm. We tested the hypothesis that percent damage to specific white matter tracts, age, and education together predict accuracy in sarcasm recognition. Using multivariable linear regression, with age, education, and percent damage to each of eight white matter tracts as independent variables, and percent accuracy on sarcasm recognition as the dependent variable, we developed a model for predicting sarcasm recognition. Percent damage to the sagittal stratum had the greatest weight and was the only independent predictor of sarcasm recognition.

  10. 3D face recognition algorithm based on detecting reliable components

    Institute of Scientific and Technical Information of China (English)

    Huang Wenjun; Zhou Xuebing; Niu Xiamu

    2007-01-01

    Fisherfaces algorithm is a popular method for face recognition. However, there exist some unstable components that degrade recognition performance. In this paper, we propose a method based on detecting reliable components to overcome the problem and introduce it to 3D face recognition. The reliable components are detected within the binary feature vector, which is generated from the Fisherfaces feature vector based on statistical properties, and is used for 3D face recognition as the final feature vector. Experimental results show that the reliable components feature vector is much more effective than the Fisherfaces feature vector for face recognition.

  11. The Phase Spectra Based Feature for Robust Speech Recognition

    Directory of Open Access Journals (Sweden)

    Abbasian ALI

    2009-07-01

    Full Text Available Speech recognition in adverse environment is one of the major issue in automatic speech recognition nowadays. While most current speech recognition system show to be highly efficient for ideal environment but their performance go down extremely when they are applied in real environment because of noise effected speech. In this paper a new feature representation based on phase spectra and Perceptual Linear Prediction (PLP has been suggested which can be used for robust speech recognition. It is shown that this new features can improve the performance of speech recognition not only in clean condition but also in various levels of noise condition when it is compared to PLP features.

  12. Face Recognition (Patterns Matching & Bio-Metrics

    Directory of Open Access Journals (Sweden)

    Jignesh Dhirubhai Hirapara

    2012-08-01

    Full Text Available Government agencies are investing a considerable amount of resources into improving security systems as result of recent terrorist events that dangerously exposed flaws and weaknesses in today’s safety mechanisms. Badge or password-based authentication procedures are too easy to hack. Biometrics represents a valid alternative but they suffer of drawbacks as well. Iris scanning, for example, is very reliable but too intrusive; fingerprints are socially accepted, but not applicable to non-con sentient people. On the other hand, face recognition represents a good compromise between what’s socially acceptable and what’s reliable, even when operating under controlled conditions. In last decade, many algorithms based on linear/nonlinear methods, neural networks, wavelets, etc. have been proposed. Nevertheless, Face Recognition Vendor Test 2002 shown that most of these approaches encountered problems in outdoor conditions. This lowered their reliability compared to state of the art biometrics.

  13. Simulink Component Recognition Using Image Processing

    Directory of Open Access Journals (Sweden)

    Ramya R

    2015-02-01

    Full Text Available ABSTRACT In early stages of engineering design pen-and-paper sketches are often used to quickly convey concepts and ideas. Free-form drawing is often preferable to using computer interfaces due to its ease of use fluidity and lack of constraints. The objective of this project is to create a trainable sketched Simulink component recognizer and classifying the individual Simulink components from the input block diagram. The recognized components will be placed on the new Simulink model window after which operations can be performed over them. Noise from the input image is removed by Median filter the segmentation process is done by K-means clustering algorithm and recognition of individual Simulink components from the input block diagram is done by Euclidean distance. The project aims to devise an efficient way to segment a control system block diagram into individual components for recognition.

  14. Image Pixel Fusion for Human Face Recognition

    CERN Document Server

    Bhowmik, Mrinal Kanti; Nasipuri, Mita; Basu, Dipak Kumar; Kundu, Mahantapas

    2010-01-01

    In this paper we present a technique for fusion of optical and thermal face images based on image pixel fusion approach. Out of several factors, which affect face recognition performance in case of visual images, illumination changes are a significant factor that needs to be addressed. Thermal images are better in handling illumination conditions but not very consistent in capturing texture details of the faces. Other factors like sunglasses, beard, moustache etc also play active role in adding complicacies to the recognition process. Fusion of thermal and visual images is a solution to overcome the drawbacks present in the individual thermal and visual face images. Here fused images are projected into an eigenspace and the projected images are classified using a radial basis function (RBF) neural network and also by a multi-layer perceptron (MLP). In the experiments Object Tracking and Classification Beyond Visible Spectrum (OTCBVS) database benchmark for thermal and visual face images have been used. Compar...

  15. Euro Banknote Recognition System for Blind People

    Directory of Open Access Journals (Sweden)

    Larisa Dunai Dunai

    2017-01-01

    Full Text Available This paper presents the development of a portable system with the aim of allowing blind people to detect and recognize Euro banknotes. The developed device is based on a Raspberry Pi electronic instrument and a Raspberry Pi camera, Pi NoIR (No Infrared filter dotted with additional infrared light, which is embedded into a pair of sunglasses that permit blind and visually impaired people to independently handle Euro banknotes, especially when receiving their cash back when shopping. The banknote detection is based on the modified Viola and Jones algorithms, while the banknote value recognition relies on the Speed Up Robust Features (SURF technique. The accuracies of banknote detection and banknote value recognition are 84% and 97.5%, respectively.

  16. Euro Banknote Recognition System for Blind People.

    Science.gov (United States)

    Dunai Dunai, Larisa; Chillarón Pérez, Mónica; Peris-Fajarnés, Guillermo; Lengua Lengua, Ismael

    2017-01-20

    This paper presents the development of a portable system with the aim of allowing blind people to detect and recognize Euro banknotes. The developed device is based on a Raspberry Pi electronic instrument and a Raspberry Pi camera, Pi NoIR (No Infrared filter) dotted with additional infrared light, which is embedded into a pair of sunglasses that permit blind and visually impaired people to independently handle Euro banknotes, especially when receiving their cash back when shopping. The banknote detection is based on the modified Viola and Jones algorithms, while the banknote value recognition relies on the Speed Up Robust Features (SURF) technique. The accuracies of banknote detection and banknote value recognition are 84% and 97.5%, respectively.

  17. Locally Linear Discriminate Embedding for Face Recognition

    Directory of Open Access Journals (Sweden)

    Eimad E. Abusham

    2009-01-01

    Full Text Available A novel method based on the local nonlinear mapping is presented in this research. The method is called Locally Linear Discriminate Embedding (LLDE. LLDE preserves a local linear structure of a high-dimensional space and obtains a compact data representation as accurately as possible in embedding space (low dimensional before recognition. For computational simplicity and fast processing, Radial Basis Function (RBF classifier is integrated with the LLDE. RBF classifier is carried out onto low-dimensional embedding with reference to the variance of the data. To validate the proposed method, CMU-PIE database has been used and experiments conducted in this research revealed the efficiency of the proposed methods in face recognition, as compared to the linear and non-linear approaches.

  18. Eigen-Gradients for Traffic Sign Recognition

    Directory of Open Access Journals (Sweden)

    Sheila Esmeralda Gonzalez-Reyna

    2013-01-01

    Full Text Available Traffic sign detection and recognition systems include a variety of applications like autonomous driving, road sign inventory, and driver support systems. Machine learning algorithms provide useful tools for traffic sign identification tasks. However, classification algorithms depend on the preprocessing stage to obtain high accuracy rates. This paper proposes a road sign characterization method based on oriented gradient maps and the Karhunen-Loeve transform in order to improve classification performance. Dimensionality reduction may be important for portable applications on resource constrained devices like FPGAs; therefore, our approach focuses on achieving a good classification accuracy by using a reduced amount of attributes compared to some state-of-the-art methods. The proposed method was tested using German Traffic Sign Recognition Benchmark, reaching a dimensionality reduction of 99.3% and a classification accuracy of 95.9% with a Multi-Layer Perceptron.

  19. Robust Face Recognition through Local Graph Matching

    Directory of Open Access Journals (Sweden)

    Ehsan Fazl-Ersi

    2007-09-01

    Full Text Available A novel face recognition method is proposed, in which face images are represented by a set of local labeled graphs, each containing information about the appearance and geometry of a 3-tuple of face feature points, extracted using Local Feature Analysis (LFA technique. Our method automatically learns a model set and builds a graph space for each individual. A two-stage method for optimal matching between the graphs extracted from a probe image and the trained model graphs is proposed. The recognition of each probe face image is performed by assigning it to the trained individual with the maximum number of references. Our approach achieves perfect result on the ORL face set and an accuracy rate of 98.4% on the FERET face set, which shows the superiority of our method over all considered state-of-the-art methods. I

  20. Face Recognition using Eigenfaces and Neural Networks

    Directory of Open Access Journals (Sweden)

    Mohamed Rizon

    2006-01-01

    Full Text Available In this study, we develop a computational model to identify the face of an unknown person’s by applying eigenfaces. The eigenfaces has been applied to extract the basic face of the human face images. The eigenfaces is then projecting onto human faces to identify unique features vectors. This significant features vector can be used to identify an unknown face by using the backpropagation neural network that utilized euclidean distance for classification and recognition. The ORL database for this investigation consists of 40 people with various 400 face images had been used for the learning. The eigenfaces including implemented Jacobi’s method for eigenvalues and eigenvectors has been performed. The classification and recognition using backpropagation neural network showed impressive positive result to classify face images.

  1. Active Appearance Model Based Hand Gesture Recognition

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    This paper addresses the application of hand gesture recognition in monocular image sequences using Active Appearance Model (AAM). For this work, the proposed algorithm is conposed of constructing AAMs and fitting the models to the interest region. In training stage, according to the manual labeled feature points, the relative AAM is constructed and the corresponding average feature is obtained. In recognition stage, the interesting hand gesture region is firstly segmented by skin and movement cues.Secondly, the models are fitted to the image that includes the hand gesture, and the relative features are extracted.Thirdly, the classification is done by comparing the extracted features and average features. 30 different gestures of Chinese sign language are applied for testing the effectiveness of the method. The Experimental results are given indicating good performance of the algorithm.

  2. Enhanced Face Recognition using Data Fusion

    Directory of Open Access Journals (Sweden)

    Alaa Eleyan

    2012-12-01

    Full Text Available In this paper we scrutinize the influence of fusion on the face recognition performance. In pattern recognition task, benefiting from different uncorrelated observations and performing fusion at feature and/or decision levels improves the overall performance. In features fusion approach, we fuse (concatenate the feature vectors obtained using different feature extractors for the same image. Classification is then performed using different similarity measures. In decisions fusion approach, the fusion is performed at decisions level, where decisions from different algorithms are fused using majority voting. The proposed method was tested using face images having different facial expressions and conditions obtained from ORL and FRAV2D databases. Simulations results show that the performance of both feature and decision fusion approaches outperforms the single performances of the fused algorithms significantly.

  3. A connectionist computational method for face recognition

    Directory of Open Access Journals (Sweden)

    Pujol Francisco A.

    2016-06-01

    Full Text Available In this work, a modified version of the elastic bunch graph matching (EBGM algorithm for face recognition is introduced. First, faces are detected by using a fuzzy skin detector based on the RGB color space. Then, the fiducial points for the facial graph are extracted automatically by adjusting a grid of points to the result of an edge detector. After that, the position of the nodes, their relation with their neighbors and their Gabor jets are calculated in order to obtain the feature vector defining each face. A self-organizing map (SOM framework is shown afterwards. Thus, the calculation of the winning neuron and the recognition process are performed by using a similarity function that takes into account both the geometric and texture information of the facial graph. The set of experiments carried out for our SOM-EBGM method shows the accuracy of our proposal when compared with other state-of the-art methods.

  4. Chinese handwriting recognition an algorithmic perspective

    CERN Document Server

    Su, Tonghua

    2013-01-01

    This book provides an algorithmic perspective on the recent development of Chinese handwriting recognition. Two technically sound strategies, the segmentation-free and integrated segmentation-recognition strategy, are investigated and algorithms that have worked well in practice are primarily focused on. Baseline systems are initially presented for these strategies and are subsequently expanded on and incrementally improved. The sophisticated algorithms covered include: 1) string sample expansion algorithms which synthesize string samples from isolated characters or distort realistic string samples; 2) enhanced feature representation algorithms, e.g. enhanced four-plane features and Delta features; 3) novel learning algorithms, such as Perceptron learning with dynamic margin, MPE training and distributed training; and lastly 4) ensemble algorithms, that is, combining the two strategies using both parallel structure and serial structure. All the while, the book moves from basic to advanced algorithms, helping ...

  5. Speech emotion recognition with unsupervised feature learning

    Institute of Scientific and Technical Information of China (English)

    Zheng-wei HUANG; Wen-tao XUE; Qi-rong MAO

    2015-01-01

    Emotion-based features are critical for achieving high performance in a speech emotion recognition (SER) system. In general, it is difficult to develop these features due to the ambiguity of the ground-truth. In this paper, we apply several unsupervised feature learning algorithms (including K-means clustering, the sparse auto-encoder, and sparse restricted Boltzmann machines), which have promise for learning task-related features by using unlabeled data, to speech emotion recognition. We then evaluate the performance of the proposed approach and present a detailed analysis of the effect of two important factors in the model setup, the content window size and the number of hidden layer nodes. Experimental results show that larger content windows and more hidden nodes contribute to higher performance. We also show that the two-layer network cannot explicitly improve performance compared to a single-layer network.

  6. Intangible Wealth, between Recognition and Evaluation

    Directory of Open Access Journals (Sweden)

    Florentina Moisescu

    2016-07-01

    Full Text Available The theme of this work is the recognition, assessment and importance of intangible property in the financial statements of an enterprise. The paper presents an insight into intangible assets recognition of causality, with highlight relevant aspects of how education contribute in a decisive manner, through the generation and dissemination of knowledge in order to achieve specific strategic goals of economic policy. This issue has also been a challenge and it still represents one for companies that have intangible assets overstated or that have kept in their balance sheet intangible assets without aproperly assessed market value. The paper also addresses the issue by restricting the proposed theoretical aspects in favor of those which are directly related to the accounting practice in line with International Accounting Standards and with the accounting regulations of our country.

  7. Euro Banknote Recognition System for Blind People

    Science.gov (United States)

    Dunai Dunai, Larisa; Chillarón Pérez, Mónica; Peris-Fajarnés, Guillermo; Lengua Lengua, Ismael

    2017-01-01

    This paper presents the development of a portable system with the aim of allowing blind people to detect and recognize Euro banknotes. The developed device is based on a Raspberry Pi electronic instrument and a Raspberry Pi camera, Pi NoIR (No Infrared filter) dotted with additional infrared light, which is embedded into a pair of sunglasses that permit blind and visually impaired people to independently handle Euro banknotes, especially when receiving their cash back when shopping. The banknote detection is based on the modified Viola and Jones algorithms, while the banknote value recognition relies on the Speed Up Robust Features (SURF) technique. The accuracies of banknote detection and banknote value recognition are 84% and 97.5%, respectively. PMID:28117703

  8. Circular object recognition based on shape parameters

    Institute of Scientific and Technical Information of China (English)

    Chen Aijun; Li Jinzong; Zhu Bing

    2007-01-01

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

  9. Audio-visual affective expression recognition

    Science.gov (United States)

    Huang, Thomas S.; Zeng, Zhihong

    2007-11-01

    Automatic affective expression recognition has attracted more and more attention of researchers from different disciplines, which will significantly contribute to a new paradigm for human computer interaction (affect-sensitive interfaces, socially intelligent environments) and advance the research in the affect-related fields including psychology, psychiatry, and education. Multimodal information integration is a process that enables human to assess affective states robustly and flexibly. In order to understand the richness and subtleness of human emotion behavior, the computer should be able to integrate information from multiple sensors. We introduce in this paper our efforts toward machine understanding of audio-visual affective behavior, based on both deliberate and spontaneous displays. Some promising methods are presented to integrate information from both audio and visual modalities. Our experiments show the advantage of audio-visual fusion in affective expression recognition over audio-only or visual-only approaches.

  10. Urban building recognition during significant temporal variations

    DEFF Research Database (Denmark)

    Nguyen, Phuong Giang; Andersen, Hans Jørgen

    2008-01-01

    features (Multi-scale Oriented Patches) in [2], which extract features of patches around interest points. To speed up the searching process, we employ the vocabulary tree based search technique in [12]. Our final system shows high performance in recognizing buildings under significant temporal variations......In literature, existing researches on building recognition mainly concentrate on scales, rotations, and viewpoints variance. In urban environment, large temporal variations of weather and lighting conditions should also be considered as major challenges for robust recognition. For instances......, there are differences between images captured during daytime and nighttime, especially significant changes in building appearances between seasons because of the differences in light setting. To date, these large temporal variation issues have not been fully investigated. In this paper, we therefore focus...

  11. Enhanced Approximated SURF Model For Object Recognition

    Directory of Open Access Journals (Sweden)

    S. Sangeetha

    2014-02-01

    Full Text Available Computer vision applications like camera calibration, 3D reconstruction, and object recognition and image registration are becoming widely popular now a day. In this paper an enhanced model for speeded up robust features (SURF is proposed by which the object recognition process will become three times faster than common SURF model The main idea is to use efficient data structures for both, the detector and the descriptor. The detection of interest regions is considerably speed-up by using an integral image for scale space computation. The descriptor which is based on orientation histograms is accelerated by the use of an integral orientation histogram. We present an analysis of the computational costs comparing both parts of our approach to the conventional method. Extensive experiments show a speed-up by a factor of eight while the matching and repeatability performance is decreased only slightly.

  12. Average Gait Differential Image Based Human Recognition

    Directory of Open Access Journals (Sweden)

    Jinyan Chen

    2014-01-01

    Full Text Available The difference between adjacent frames of human walking contains useful information for human gait identification. Based on the previous idea a silhouettes difference based human gait recognition method named as average gait differential image (AGDI is proposed in this paper. The AGDI is generated by the accumulation of the silhouettes difference between adjacent frames. The advantage of this method lies in that as a feature image it can preserve both the kinetic and static information of walking. Comparing to gait energy image (GEI, AGDI is more fit to representation the variation of silhouettes during walking. Two-dimensional principal component analysis (2DPCA is used to extract features from the AGDI. Experiments on CASIA dataset show that AGDI has better identification and verification performance than GEI. Comparing to PCA, 2DPCA is a more efficient and less memory storage consumption feature extraction method in gait based recognition.

  13. Mental transformation in a visual recognition task.

    Science.gov (United States)

    Bartusevicius, E; Vanagas, V; Radil-Weiss, T

    1981-01-01

    Rectangular geometrical patterns with equal number of lines, identical relations between their vertical and horizontal components, identical angles, line crossing knots and free ends of lines were presented tachistoscopically to human subjects with a restricted recognition time caused by backward masking. Symmetrical linear transformation with respect to the Y or X axes and rotations of the patterns were performed and the correctness of their reproduction was measured in psychophysical experiments. A mental pattern transformation was a fast operation (under 100 ms) not directly linked to a graphic or a verbal expression of the results of reproduction. Mental transformation is probably determined by the recognition process. Symmetrical transformations are easier than rotational, whereas the most difficult is a detection of a pattern differing in its form from those considered within a predetermined group of samples.

  14. Hierarchical Neural Network Structures for Phoneme Recognition

    CERN Document Server

    Vasquez, Daniel; Minker, Wolfgang

    2013-01-01

    In this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are evaluated on the phoneme recognition task where a  Hybrid Hidden Markov Model/Artificial Neural Network paradigm is used. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron. Additionally, the output of the first level serves as a second level input. The computational speed of the phoneme recognizer can be substantially increased by removing redundant information still contained at the first level output. Several techniques based on temporal and phonetic criteria have been investigated to remove this redundant information. The computational time could be reduced by 57% whilst keeping the system accuracy comparable to the baseline hierarchical approach.

  15. Automatic stereoscopic system for person recognition

    Science.gov (United States)

    Murynin, Alexander B.; Matveev, Ivan A.; Kuznetsov, Victor D.

    1999-06-01

    A biometric access control system based on identification of human face is presented. The system developed performs remote measurements of the necessary face features. Two different scenarios of the system behavior are implemented. The first one assumes the verification of personal data entered by visitor from console using keyboard or card reader. The system functions as an automatic checkpoint, that strictly controls access of different visitors. The other scenario makes it possible to identify visitors without any person identifier or pass. Only person biometrics are used to identify the visitor. The recognition system automatically finds necessary identification information preliminary stored in the database. Two laboratory models of recognition system were developed. The models are designed to use different information types and sources. In addition to stereoscopic images inputted to computer from cameras the models can use voice data and some person physical characteristics such as person's height, measured by imaging system.

  16. Recognition of Words from the EEG Laplacian

    CERN Document Server

    de Barros, J Acacio; de Mendonça, J P R F; Suppes, P

    2012-01-01

    Recent works on the relationship between the electro-encephalogram (EEG) data and psychological stimuli show that EEG recordings can be used to recognize an auditory stimulus presented to a subject. The recognition rate is, however, strongly affected by technical and physiological artifacts. In this work, subjects were presented seven auditory simuli in the form of English words (first, second, third, left, right, yes, and no), and the time-locked electric field was recorded with a 64 channel Neuroscan EEG system. We used the surface Laplacian operator to eliminate artifacts due to sources located at regions far from the electrode. Our intent with the Laplacian was to improve the recognition rates of auditory stimuli from the electric field. To compute the Laplacian, we used a spline interpolation from spherical harmonics. The EEG Laplacian of the electric field were average over trials for the same auditory stimulus, and with those averages we constructed prototypes and test samples. In addition to the Lapla...

  17. Action Recognition Using Discriminative Structured Trajectory Groups

    KAUST Repository

    Atmosukarto, Indriyati

    2015-01-06

    In this paper, we develop a novel framework for action recognition in videos. The framework is based on automatically learning the discriminative trajectory groups that are relevant to an action. Different from previous approaches, our method does not require complex computation for graph matching or complex latent models to localize the parts. We model a video as a structured bag of trajectory groups with latent class variables. We model action recognition problem in a weakly supervised setting and learn discriminative trajectory groups by employing multiple instance learning (MIL) based Support Vector Machine (SVM) using pre-computed kernels. The kernels depend on the spatio-temporal relationship between the extracted trajectory groups and their associated features. We demonstrate both quantitatively and qualitatively that the classification performance of our proposed method is superior to baselines and several state-of-the-art approaches on three challenging standard benchmark datasets.

  18. Probabilistic view clustering in object recognition

    Science.gov (United States)

    Camps, Octavia I.; Christoffel, Douglas W.; Pathak, Anjali

    1992-11-01

    To recognize objects and to determine their poses in a scene we need to find correspondences between the features extracted from the image and those of the object models. Models are commonly represented by describing a few characteristic views of the object representing groups of views with similar properties. Most feature-based matching schemes assume that all the features that are potentially visible in a view will appear with equal probability, and the resulting matching algorithms have to allow for 'errors' without really understanding what they mean. PREMIO is an object recognition system that uses CAD models of 3D objects and knowledge of surface reflectance properties, light sources, sensor characteristics, and feature detector algorithms to estimate the probability of the features being detectable and correctly matched. The purpose of this paper is to describe the predictions generated by PREMIO, how they are combined into a single probabilistic model, and illustrative examples showing its use in object recognition.

  19. In search of a recognition memory engram

    Science.gov (United States)

    Brown, M.W.; Banks, P.J.

    2015-01-01

    A large body of data from human and animal studies using psychological, recording, imaging, and lesion techniques indicates that recognition memory involves at least two separable processes: familiarity discrimination and recollection. Familiarity discrimination for individual visual stimuli seems to be effected by a system centred on the perirhinal cortex of the temporal lobe. The fundamental change that encodes prior occurrence within the perirhinal cortex is a reduction in the responses of neurones when a stimulus is repeated. Neuronal network modelling indicates that a system based on such a change in responsiveness is potentially highly efficient in information theoretic terms. A review is given of findings indicating that perirhinal cortex acts as a storage site for recognition memory of objects and that such storage depends upon processes producing synaptic weakening. PMID:25280908

  20. Bimodal Emotion Recognition from Speech and Text

    Directory of Open Access Journals (Sweden)

    Weilin Ye

    2014-01-01

    Full Text Available This paper presents an approach to emotion recognition from speech signals and textual content. In the analysis of speech signals, thirty-seven acoustic features are extracted from the speech input. Two different classifiers Support Vector Machines (SVMs and BP neural network are adopted to classify the emotional states. In text analysis, we use the two-step classification method to recognize the emotional states. The final emotional state is determined based on the emotion outputs from the acoustic and textual analyses. In this paper we have two parallel classifiers for acoustic information and two serial classifiers for textual information, and a final decision is made by combing these classifiers in decision level fusion. Experimental results show that the emotion recognition accuracy of the integrated system is better than that of either of the two individual approaches.