'What ever happened to breakdancing?' : transnational b-boy/b-girl networks, underground video magazines and imagined affinities

In 1997, Paul Gilroy was able to write: "I have been asking myself, whatever happened to breakdancing" (21), a form of vernacular dance associated with urban youth that emerged in the 1970s. However, in the last decade, breakdancing has experienced a massive renaissance in movies (You Got Served), commercials ("Gotta Have My Pops!") and documentaries (the acclaimed Freshest Kids). In this thesis, 1 explore the historical development of global b-boy/bgirl culture through a qualitative study involving dancers and their modes of communication. Widespread circulation of breakdancing images peaked in the mid-1980s, and subsequently b-boy/b-girl culture largely disappeared from the mediated landscape. The dance did not reemerge into the mainstream of North American popular culture until the late 1990s. 1 argue that the development of major transnational networks between b-boys and b-girls during the 1990s was a key factor in the return of 'b-boying/b-girling' (known formerly as breakdancing). Street dancers toured, traveled and competed internationally throughout this decade. They also began to create 'underground' video documentaries and travel video 'magazines.' These video artefacts circulated extensively around the globe through alternative distribution channels (including the backpacks of traveling dancers). 1 argue that underground video artefacts helped to produce 'imagined affinities' between dancers in various nations. Imagined affinities are identifications expressed by a cultural producer who shares an embodied activity with other practitioners through either mediated texts or travels through new places. These 'imagined affinities' helped to sustain b-boy/b-girl culture by generating visual/audio representations of popularity for the dance movement across geographical regions.

Human skeletal muscle pyruvate dehydrogenase phosphatase activity and expression : the effect of aerobic capacity

Activation of pyruvate dehydrogenase (PDH), which converts pyruvate into acetyl-CoA, is accomplished by a pair of specific phosphatases (PDP 1 & 2). A cross-sectional study investigating the effect of aerobic capacity on PDP activity and expression found that: 1) PDP activity and PDP! protein expression were positively correlated with most aerobic capacity measures in males (n=lS), but not females (n=12); 2) only males showed a positive correlation between PDP activity and PDPl protein expression (r=0.47; p=O.05), indicating that the increase in PDP activity in males is largely explained by increased PDPl protein expression, but that females rely on another level for PDP activity regulation; and 3) PDP} and Ela protein expression increase in unison when expressed relative to the E2 core. These data suggest that with increased aerobic capacity there is an increased capacity for carbohydrate oxidation through PDH, via El a, and an increased ability to activate PDH, via PDP, when exercising maximally.

Behavioural and neural correlates of emotion recognition as a function of psychopathic personality traits

Psychopathy is associated with well-known characteristics such as a lack of empathy and impulsive behaviour, but it has also been associated with impaired recognition of emotional facial expressions. The use of event-related potentials (ERPs) to examine this phenomenon could shed light on the specific time course and neural activation associated with emotion recognition processes as they relate to psychopathic traits. In the current study we examined the PI , N170, and vertex positive potential (VPP) ERP components and behavioural performance with respect to scores on the Self-Report Psychopathy (SRP-III) questionnaire. Thirty undergraduates completed two tasks, the first of which required the recognition and categorization of affective face stimuli under varying presentation conditions. Happy, angry or fearful faces were presented under with attention directed to the mouth, nose or eye region and varied stimulus exposure duration (30, 75, or 150 ms). We found that behavioural performance to be unrelated to psychopathic personality traits in all conditions, but there was a trend for the Nl70 to peak later in response to fearful and happy facial expressions for individuals high in psychopathic traits. However, the amplitude of the VPP was significantly negatively associated with psychopathic traits, but only in response to stimuli presented under a nose-level fixation. Finally, psychopathic traits were found to be associated with longer N170 latencies in response to stimuli presented under the 30 ms exposure duration. In the second task, participants were required to inhibit processing of irrelevant affective and scrambled face distractors while categorizing unrelated word stimuli as living or nonliving. Psychopathic traits were hypothesized to be positively associated with behavioural performance, as it was proposed that individuals high in psychopathic traits would be less likely to automatically attend to task-irrelevant affective distractors, facilitating word categorization. Thus, decreased interference would be reflected in smaller N170 components, indicating less neural activity associated with processing of distractor faces. We found that overall performance decreased in the presence of angry and fearful distractor faces as psychopathic traits increased. In addition, the amplitude of the N170 decreased and the latency increased in response to affective distractor faces for individuals with higher levels of psychopathic traits. Although we failed to find the predicted behavioural deficit in emotion recognition in Task 1 and facilitation effect in Task 2, the findings of increased N170 and VPP latencies in response to emotional faces are consistent wi th the proposition that abnormal emotion recognition processes may in fact be inherent to psychopathy as a continuous personality trait.

Analyse de mouvements faciaux à partir d'images vidéo

Lors d'une intervention conversationnelle, le langage est supporté par une communication non-verbale qui joue un rôle central dans le comportement social humain en permettant de la rétroaction et en gérant la synchronisation, appuyant ainsi le contenu et la signification du discours. En effet, 55% du message est véhiculé par les expressions faciales, alors que seulement 7% est dû au message linguistique et 38% au paralangage. L'information concernant l'état émotionnel d'une personne est généralement inférée par les attributs faciaux. Cependant, on ne dispose pas vraiment d'instruments de mesure spécifiquement dédiés à ce type de comportements. En vision par ordinateur, on s'intéresse davantage au développement de systèmes d'analyse automatique des expressions faciales prototypiques pour les applications d'interaction homme-machine, d'analyse de vidéos de réunions, de sécurité, et même pour des applications cliniques. Dans la présente recherche, pour appréhender de tels indicateurs observables, nous essayons d'implanter un système capable de construire une source consistante et relativement exhaustive d'informations visuelles, lequel sera capable de distinguer sur un visage les traits et leurs déformations, permettant ainsi de reconnaître la présence ou absence d'une action faciale particulière. Une réflexion sur les techniques recensées nous a amené à explorer deux différentes approches. La première concerne l'aspect apparence dans lequel on se sert de l'orientation des gradients pour dégager une représentation dense des attributs faciaux. Hormis la représentation faciale, la principale difficulté d'un système, qui se veut être général, est la mise en œuvre d'un modèle générique indépendamment de l'identité de la personne, de la géométrie et de la taille des visages. La démarche qu'on propose repose sur l'élaboration d'un référentiel prototypique à partir d'un recalage par SIFT-flow dont on démontre, dans cette thèse, la supériorité par rapport à un alignement conventionnel utilisant la position des yeux. Dans une deuxième approche, on fait appel à un modèle géométrique à travers lequel les primitives faciales sont représentées par un filtrage de Gabor. Motivé par le fait que les expressions faciales sont non seulement ambigües et incohérentes d'une personne à une autre mais aussi dépendantes du contexte lui-même, à travers cette approche, on présente un système personnalisé de reconnaissance d'expressions faciales, dont la performance globale dépend directement de la performance du suivi d'un ensemble de points caractéristiques du visage. Ce suivi est effectué par une forme modifiée d'une technique d'estimation de disparité faisant intervenir la phase de Gabor. Dans cette thèse, on propose une redéfinition de la mesure de confiance et introduisons une procédure itérative et conditionnelle d'estimation du déplacement qui offrent un suivi plus robuste que les méthodes originales.

Recognition of Facial Expressions with Autoencoders and Convolutional-Nets

Les humains communiquent via différents types de canaux: les mots, la voix, les gestes du corps, des émotions, etc. Pour cette raison, un ordinateur doit percevoir ces divers canaux de communication pour pouvoir interagir intelligemment avec les humains, par exemple en faisant usage de microphones et de webcams. Dans cette thèse, nous nous intéressons à déterminer les émotions humaines à partir d’images ou de vidéo de visages afin d’ensuite utiliser ces informations dans différents domaines d’applications. Ce mémoire débute par une brève introduction à l'apprentissage machine en s’attardant aux modèles et algorithmes que nous avons utilisés tels que les perceptrons multicouches, réseaux de neurones à convolution et autoencodeurs. Elle présente ensuite les résultats de l'application de ces modèles sur plusieurs ensembles de données d'expressions et émotions faciales. Nous nous concentrons sur l'étude des différents types d’autoencodeurs (autoencodeur débruitant, autoencodeur contractant, etc) afin de révéler certaines de leurs limitations, comme la possibilité d'obtenir de la coadaptation entre les filtres ou encore d’obtenir une courbe spectrale trop lisse, et étudions de nouvelles idées pour répondre à ces problèmes. Nous proposons également une nouvelle approche pour surmonter une limite des autoencodeurs traditionnellement entrainés de façon purement non-supervisée, c'est-à-dire sans utiliser aucune connaissance de la tâche que nous voulons finalement résoudre (comme la prévision des étiquettes de classe) en développant un nouveau critère d'apprentissage semi-supervisé qui exploite un faible nombre de données étiquetées en combinaison avec une grande quantité de données non-étiquetées afin d'apprendre une représentation adaptée à la tâche de classification, et d'obtenir une meilleure performance de classification. Finalement, nous décrivons le fonctionnement général de notre système de détection d'émotions et proposons de nouvelles idées pouvant mener à de futurs travaux.

Identification des corrélats neuronaux associés à la clôture perceptive des objets : une étude en potentiels évoqués

La capacité du système visuel humain à compléter une image partiellement dévoilée et à en dériver une forme globale à partir de ses fragments visibles incomplets est un phénomène qui suscite, jusqu’à nos jours, l’intérêt de nombreux scientifiques œuvrant dans différents milieux de recherche tels que l’informatique, l’ingénierie en intelligence artificielle, la perception et les neurosciences. Dans le cadre de la présente thèse, nous nous sommes intéressés spécifiquement sur les substrats neuronaux associés à ce phénomène de clôture perceptive. La thèse actuelle a donc pour objectif général d’explorer le décours spatio-temporel des corrélats neuronaux associés à la clôture perceptive au cours d’une tâche d’identification d’objets. Dans un premier temps, le premier article visera à caractériser la signature électrophysiologique liée à la clôture perceptive chez des personnes à développement typique dans le but de déterminer si les processus de clôture perceptive reflèteraient l’interaction itérative entre les mécanismes de bas et de haut-niveau et si ceux-ci seraient sollicités à une étape précoce ou tardive lors du traitement visuel de l’information. Dans un deuxième temps, le second article a pour objectif d’explorer le décours spatio-temporel des mécanismes neuronaux sous-tendant la clôture perceptive dans le but de déterminer si les processus de clôture perceptive des personnes présentant un trouble autistique se caractérisent par une signature idiosyncrasique des changements d’amplitude des potentiels évoqués (PÉs). En d’autres termes, nous cherchons à déterminer si la clôture perceptive en autisme est atypique et nécessiterait davantage la contribution des mécanismes de bas-niveau et/ou de haut-niveau. Les résultats du premier article indiquent que le phénomène de clôture perceptive est associé temporellement à l’occurrence de la composante de PÉs N80 et P160 tel que révélé par des différences significatives claires entre des objets et des versions méconnaissables brouillées. Nous proposons enfin que la clôture perceptive s’avère un processus de transition reflétant les interactions proactives entre les mécanismes neuronaux œuvrant à apparier l’input sensoriel fragmenté à une représentation d’objets en mémoire plausible. Les résultats du second article révèlent des effets précoces de fragmentation et d’identification obtenus au niveau de composantes de potentiels évoqués N80 et P160 et ce, en toute absence d’effets au niveau des composantes tardives pour les individus avec autisme de haut niveau et avec syndrome d’Asperger. Pour ces deux groupes du trouble du spectre autistique, les données électrophysiologiques suggèrent qu’il n’y aurait pas de pré-activation graduelle de l’activité des régions corticales, entre autres frontales, aux moments précédant et menant vers l’identification d’objets fragmentés. Pour les participants autistes et avec syndrome d’Asperger, les analyses statistiques démontrent d’ailleurs une plus importante activation au niveau des régions postérieures alors que les individus à développement typique démontrent une activation plus élevée au niveau antérieur. Ces résultats pourraient suggérer que les personnes du spectre autistique se fient davantage aux processus perceptifs de bas-niveau pour parvenir à compléter les images d’objets fragmentés. Ainsi, lorsque confrontés aux images d’objets partiellement visibles pouvant sembler ambiguës, les individus avec autisme pourraient démontrer plus de difficultés à générer de multiples prédictions au sujet de l’identité d’un objet qu’ils perçoivent. Les implications théoriques et cliniques, les limites et perspectives futures de ces résultats sont discutées.

Diversity and antimicrobial activity of Lactic Acid Bacteria from the gut of marine fish Rastrelliger kanagurta against fish, shrimp and human pathogens

Emergence of antibiotic resistance among aquaculture pathogens has made it necessary to look into environment friendly, effective and sustainable methods such as probiotic and immunostimulants among others.. In the present study, LAB were isolated from the gut of fish species namely Rastrelliger kanagurta and analyzed for their antibacterial activity against various fish, shrimp and human pathogens. Different LAB species such as Lactobacillus plantarum, L. bulgaricus, L. brevis and L. viridiscens were encountered in the gut of R. kanagurta. Several strains showed good activity against fish, shrimp and human pathogens. LAB from the gut of such marine species may be developed as possible probiont for environment friendly health management of fresh water, estuarine and marine species currently exploited in aquaculture

Ontology based Framework for News Extraction in Visual Media

Anticipating the increase in video information in future, archiving of news is an important activity in the visual media industry. When the volume of archives increases, it will be difficult for journalists to find the appropriate content using current search tools. This paper provides the details of the study we conducted about the news extraction systems used in different news channels in Kerala. Semantic web technologies can be used effectively since news archiving share many of the characteristics and problems of WWW. Since visual news archives of different media resources follow different metadata standards, interoperability between the resources is also an issue. World Wide Web Consortium has proposed a draft for an ontology framework for media resource which addresses the intercompatiblity issues. In this paper, the w3c proposed framework and its drawbacks is also discussed

The Use of Grouping in Visual Object Recognition.

The report describes a recognition system called GROPER, which performs grouping by using distance and relative orientation constraints that estimate the likelihood of different edges in an image coming from the same object. The thesis presents both a theoretical analysis of the grouping problem and a practical implementation of a grouping system. GROPER also uses an indexing module to allow it to make use of knowledge of different objects, any of which might appear in an image. We test GROPER by comparing it to a similar recognition system that does not use grouping.

Geometry and Photometry in 3D Visual Recognition

The report addresses the problem of visual recognition under two sources of variability: geometric and photometric. The geometric deals with the relation between 3D objects and their views under orthographic and perspective projection. The photometric deals with the relation between 3D matte objects and their images under changing illumination conditions. Taken together, an alignment-based method is presented for recognizing objects viewed from arbitrary viewing positions and illuminated by arbitrary settings of light sources.

Object Recognition with Pictorial Structures

This thesis presents a statistical framework for object recognition. The framework is motivated by the pictorial structure models introduced by Fischler and Elschlager nearly 30 years ago. The basic idea is to model an object by a collection of parts arranged in a deformable configuration. The appearance of each part is modeled separately, and the deformable configuration is represented by spring-like connections between pairs of parts. These models allow for qualitative descriptions of visual appearance, and are suitable for generic recognition problems. The problem of detecting an object in an image and the problem of learning an object model using training examples are naturally formulated under a statistical approach. We present efficient algorithms to solve these problems in our framework. We demonstrate our techniques by training models to represent faces and human bodies. The models are then used to locate the corresponding objects in novel images.

Computer Analysis of Visual Properties of Curved Objects

A method is presented for the visual analysis of objects by computer. It is particularly well suited for opaque objects with smoothly curved surfaces. The method extracts information about the object's surface properties, including measures of its specularity, texture, and regularity. It also aids in determining the object's shape. The application of this method to a simple recognition task ??e recognition of fruit ?? discussed. The results on a more complex smoothly curved object, a human face, are also considered.

Surface Reflectance Recognition and Real-World Illumination Statistics

Humans distinguish materials such as metal, plastic, and paper effortlessly at a glance. Traditional computer vision systems cannot solve this problem at all. Recognizing surface reflectance properties from a single photograph is difficult because the observed image depends heavily on the amount of light incident from every direction. A mirrored sphere, for example, produces a different image in every environment. To make matters worse, two surfaces with different reflectance properties could produce identical images. The mirrored sphere simply reflects its surroundings, so in the right artificial setting, it could mimic the appearance of a matte ping-pong ball. Yet, humans possess an intuitive sense of what materials typically "look like" in the real world. This thesis develops computational algorithms with a similar ability to recognize reflectance properties from photographs under unknown, real-world illumination conditions. Real-world illumination is complex, with light typically incident on a surface from every direction. We find, however, that real-world illumination patterns are not arbitrary. They exhibit highly predictable spatial structure, which we describe largely in the wavelet domain. Although they differ in several respects from the typical photographs, illumination patterns share much of the regularity described in the natural image statistics literature. These properties of real-world illumination lead to predictable image statistics for a surface with given reflectance properties. We construct a system that classifies a surface according to its reflectance from a single photograph under unknown illuminination. Our algorithm learns relationships between surface reflectance and certain statistics computed from the observed image. Like the human visual system, we solve the otherwise underconstrained inverse problem of reflectance estimation by taking advantage of the statistical regularity of illumination. For surfaces with homogeneous reflectance properties and known geometry, our system rivals human performance.

A Detailed Look at Scale and Translation Invariance in a Hierarchical Neural Model of Visual Object Recognition

The HMAX model has recently been proposed by Riesenhuber & Poggio as a hierarchical model of position- and size-invariant object recognition in visual cortex. It has also turned out to model successfully a number of other properties of the ventral visual stream (the visual pathway thought to be crucial for object recognition in cortex), and particularly of (view-tuned) neurons in macaque inferotemporal cortex, the brain area at the top of the ventral stream. The original modeling study only used ``paperclip'' stimuli, as in the corresponding physiology experiment, and did not explore systematically how model units' invariance properties depended on model parameters. In this study, we aimed at a deeper understanding of the inner workings of HMAX and its performance for various parameter settings and ``natural'' stimulus classes. We examined HMAX responses for different stimulus sizes and positions systematically and found a dependence of model units' responses on stimulus position for which a quantitative description is offered. Interestingly, we find that scale invariance properties of hierarchical neural models are not independent of stimulus class, as opposed to translation invariance, even though both are affine transformations within the image plane.

View-Based Strategies for 3D Object Recognition

A persistent issue of debate in the area of 3D object recognition concerns the nature of the experientially acquired object models in the primate visual system. One prominent proposal in this regard has expounded the use of object centered models, such as representations of the objects' 3D structures in a coordinate frame independent of the viewing parameters [Marr and Nishihara, 1978]. In contrast to this is another proposal which suggests that the viewing parameters encountered during the learning phase might be inextricably linked to subsequent performance on a recognition task [Tarr and Pinker, 1989; Poggio and Edelman, 1990]. The 'object model', according to this idea, is simply a collection of the sample views encountered during training. Given that object centered recognition strategies have the attractive feature of leading to viewpoint independence, they have garnered much of the research effort in the field of computational vision. Furthermore, since human recognition performance seems remarkably robust in the face of imaging variations [Ellis et al., 1989], it has often been implicitly assumed that the visual system employs an object centered strategy. In the present study we examine this assumption more closely. Our experimental results with a class of novel 3D structures strongly suggest the use of a view-based strategy by the human visual system even when it has the opportunity of constructing and using object-centered models. In fact, for our chosen class of objects, the results seem to support a stronger claim: 3D object recognition is 2D view-based.