yes / We describe a method for deriving the linear cortical magnification factor from positional error across the visual field. We compared magnification obtained from this method between normally sighted individuals and amblyopic individuals, who receive atypical visual input during development. The cortical magnification factor was derived for each subject from positional error at 32 locations in the visual field, using an established model of conformal mapping between retinal and cortical coordinates. Magnification of the normally sighted group matched estimates from previous physiological and neuroimaging studies in humans, confirming the validity of the approach. The estimate of magnification for the amblyopic group was significantly lower than the normal group: by 4.4 mm deg 1 at 18 eccentricity, assuming a constant scaling factor for both groups. These estimates, if correct, suggest a role for early visual experience in establishing retinotopic mapping in cortex. We discuss the implications of altered cortical magnification for cortical size, and consider other neural changes that may account for the amblyopic results.

Dans le monde industriel comme dans le monde scientifique, le développement de capteurs a toujours répondu à la volonté d’observer l’inobservable. La caméra rapide fait partie de ceux-là puisqu’elle permet de dévoiler des dynamiques invisibles, de la formation de fissure au vol du moustique. Dans un environnement extrêmement concurrentiel, ces caméras sont principalement limitées par le nombre d’images acquises par seconde. Le but de cette thèse est d’augmenter la capacité de dévoiler la dynamique invisible en enrichissant l’acquisition initiale par des modèles dynamiques. La problématique consiste alors à élaborer des méthodes permettant de relier en temps réel un modèle et la perception d’un système réel. Les bénéfices de cette utilisation offrent ainsi la possibilité de faire de l’interpolation, de la prédiction et de l’identification. Cette thèse est composée de trois parties. La première est axée sur la philosophie du traitement vidéo et propose d’utiliser des modèles élémentaires et génériques. Un algorithme d’estimation de grands mouvements est proposé mais l’approche actuellement proposée n’est pas assez générique pour être exploitée dans un contexte industriel. La deuxième partie propose d’utiliser des méthodes d’assimilation de données séquentielle basées sur la famille des filtres de Kalman afin d’associer un modèle avec des observations par caméras rapides pour des systèmes mécaniques. La troisième partie est une application à l’analyse modale expérimentale non linéaire. Deux schémas d’assimilation temps réel multicapteurs sont présentés et leur mise en œuvre est illustrée pour de la reconstruction 3D et de la magnification. / The development of sensors has always followed the ambition of industrial and scientific people to observe the unobservable. High speed cameras are part of this adventure, revealing invisible dynamics such as cracks formation or subtle mosquito flight. Industrial high speed vision is a very competitive domain in which cameras stand out through their acquisition speed. This thesis aims to broaden their capacity by augmenting the initial acquisition with dynamic models. This work proposes to develop methods linking in real time a model with a real system. Aimed benefits are interpolation, prediction and identification. Three parts are developed. The first one is based on video processing and submits to use kinematic elementary and generic models. An algorithm of motion estimation for large movements is proposed but the generic nature does not allow a sufficient knowledge to be conclusive. The second part proposes using sequential data assimilation methods known as Kalman filters. A scheme to assimilate video data with a mechanical model is successfully implemented. An application of data assimilation in modal analysis is developed. Two multi sensors real time assimilation schemes for nonlinear modal identification are proposed. These schemes are integrated in two applications on 3D reconstruction and motion magnification.

Este trabalho parte de uma pesquisa etnográfica junto ao povo A\'uw Xavante falante de uma língua do tronco lingüístico MarcoJê, habitando hoje regiões do leste do estado do Mato Grosso (Brasil) realizada entre os anos 2008 e 2010. A partir dos dados obtidos em campo e do debate com a produção etnográfica e antropológica sobre os A\'uwXavante em particular e sobre os povos ameríndios em geral, considerando também outras contribuições teóricas, abordo as concepções a\'uwxavante de gente e pessoa em seus mais variados aspectos, buscando compreender o processo de sua contínua constituição. Tomo a experiência da captura do etnógrafo pelos sujeitos à pesquisa como base para esta compreensão ainda que seja apenas uma parte do todo que aqui apresento. Capturado, o etnógrafo adquire uma potência de tornarse gente, através de sua predação, familiarização e magnificação. Com isso, abordo questões que dizem respeito ao parentesco, ao páraparentesco (como as metades agâmicas e as classes de idade), aos rituais, à relação transformista entre humanidade e nãohumanidade, à constituição política da pessoa e aos cargos cosmopolíticos. / This work is based on an ethnographic research amongst the A\'uwXavante people who speak a language of the MacroJê linguistic trunk, now inhabiting areas of eastern Mato Grosso (Brasil) conducted between the years 2008 and 2010. From data obtained in the field and in discussion with ethnographic and anthropological production about the A\'uwXavante in particular and the amerindians in general, also considering other theoretical contributions, I address the a\'uwxavante conceptions of humanity and personhood in their many aspects, seeking to understand the process of its ongoing constitution. I take the experience of the ethnographer being captured by the subjects of research as a basis for that comprehention although it is only a part of the whole presented here. Captured, the ethnographer aqquires a potency of becomming human through the predation, familiarization and magnification. With that, I address issues councerning kinship, parakinship (such as agamic moieties and age classes), rituals, the transformist relation between humanity and nonhumanity, the political constitution of the self and cosmpolitical offices.

The evolutionary history of the South African papionins is a useful analog for the emergence of hominids in South Africa. However, the taxonomic relationships of the papionins are unclear. This study uses low-magnification stereomicroscopy to examine dental microwear and uses the microwear signals to explore the existing classification of these papionins. The results from the species and site level analyses are equivocal. However, the genera and time period results show clear evidence for a dietary change between the extinct and extant forms of Papio and Parapapio. This adds an additional tool for distinguishing these two groups. The dietary changes witnessed in the papionins are likely found in the hominids from the Plio-Pleistocene. Using the papionin analog, hominid dietary evolution may be explored.

Darbe tiriamos eismo įvykio schemos braižymo ir eismo įvykio deklaracijos užpildymo automatizavimo galimybės. Tirtos šios kryptys: • GPS ir elektroninių žemėlapių panaudojimas • Atstumo matuoklių panaudojimas • Lustinių kortelių skaitytuvų panaudojimas • Automatinis ataskaitų generavimas Sukurta eksperimentinė eismo įvykių registravimo sistema, skirta bandymų rezultatams pademonstruoti. / The subject of investigation of the work is the prospects and possibilities of automation in composing traffic accident declaration. The suggestions provided: • The employment of GPS and e-maps • Usage of distance measurement devices • Appliance of chip card readers • Automatic formation of reports An experimental traffic accident registration system, demonstrating the outcomes of the research was created.

Nightly surveys of the skies detect thousands of new gravitational microlensing events every year. With the increasing number of telescopes, and advancements of the tech- nologies used, the detection rate is growing. Of these events, those that display the characteristics of a binary lens are of particular interest. They require special atten- tion with follow-up observations if possible, as such events can lead to new planetary detections. To characterise a new planetary event, high-cadence, accurate observations are optimal. However, without the ability of repeat observations, identification that any event may be planetary needs to happen before it finishes. I have developed a system that automatically retrieves all microlensing survey data and follow-up observations, models the events as single lenses, and publishes the results live to a web site. With minimal human interaction, the modelling system is able to identify and initialize binary events, and perform a thorough search of the seven dimensional parameter space of a binary lens. These results are also presented live through the web site, enabling observers an up to date view of the latest binary solutions. The real-time modelling of the system enables a prompt analysis of ongoing events, providing observers with the information, to determine if further observations are desired for the modelled events. An archive of all modelled binary lens events is maintained and accessible through the website. To date the archive contains 68 unique events’ binary lens solutions from the 2014 observing season. The system developed has been validated through model comparisons of previously published work, and is in use during the current observing season. This year it has played a role in identifying new planetary candidate events, confirming proposed solutions, and providing alternate viable solutions to previously presented solutions.

Este trabalho parte de uma pesquisa etnográfica junto ao povo A\'uw Xavante falante de uma língua do tronco lingüístico MarcoJê, habitando hoje regiões do leste do estado do Mato Grosso (Brasil) realizada entre os anos 2008 e 2010. A partir dos dados obtidos em campo e do debate com a produção etnográfica e antropológica sobre os A\'uwXavante em particular e sobre os povos ameríndios em geral, considerando também outras contribuições teóricas, abordo as concepções a\'uwxavante de gente e pessoa em seus mais variados aspectos, buscando compreender o processo de sua contínua constituição. Tomo a experiência da captura do etnógrafo pelos sujeitos à pesquisa como base para esta compreensão ainda que seja apenas uma parte do todo que aqui apresento. Capturado, o etnógrafo adquire uma potência de tornarse gente, através de sua predação, familiarização e magnificação. Com isso, abordo questões que dizem respeito ao parentesco, ao páraparentesco (como as metades agâmicas e as classes de idade), aos rituais, à relação transformista entre humanidade e nãohumanidade, à constituição política da pessoa e aos cargos cosmopolíticos. / This work is based on an ethnographic research amongst the A\'uwXavante people who speak a language of the MacroJê linguistic trunk, now inhabiting areas of eastern Mato Grosso (Brasil) conducted between the years 2008 and 2010. From data obtained in the field and in discussion with ethnographic and anthropological production about the A\'uwXavante in particular and the amerindians in general, also considering other theoretical contributions, I address the a\'uwxavante conceptions of humanity and personhood in their many aspects, seeking to understand the process of its ongoing constitution. I take the experience of the ethnographer being captured by the subjects of research as a basis for that comprehention although it is only a part of the whole presented here. Captured, the ethnographer aqquires a potency of becomming human through the predation, familiarization and magnification. With that, I address issues councerning kinship, parakinship (such as agamic moieties and age classes), rituals, the transformist relation between humanity and nonhumanity, the political constitution of the self and cosmpolitical offices.

Medical images, like any other digital data, require compression in order to reduce disk space needed for storage and time needed for transmission. The lossless compression methods of still images can shorten the file only to a very limited degree. The application of fractal compression to medical images would allow obtaining much higher compression ratios. While the fractal magnification – an inseparable feature of the fractal compression – would be very useful in presenting the reconstructed image in a highly readable form. However, like all irreversible methods, the fractal compression is connected with the problem of information loss, which is especially troublesome in the medical imaging. A very time consuming encoding process, which can last even several hours, is another bothersome drawback of the fractal compression. Based on a survey of literature and own cogitations, the author attempts to provide an adapted to the needs of medical imaging solution that will overcome the unfavorable ailments of the fractal compression methods. The thesis does not provide only theoretical deliberations but also gives implementation of the proposed algorithm, which is used to test the suitability of the fractal compression to medical imaging. The results of the work are more than satisfying – the fidelity of the images compressed with the proposed fractal compression method meets the requirements imposed on the medical images and the fractal magnification outperforms other magnification techniques.

Neural Networks are at the core of computer vision solutions for various applications. With the advent of deep neural networks Facial Expression Recognition (FER) has been a very ineluctable and challenging task in the field of computer vision. Micro-expressions (ME) have been quite prominently used in security, psychotherapy, neuroscience and have a wide role in several related disciplines. However, due to the subtle movements of facial muscles, the micro-expressions are difficult to detect and identify. Due to the above, emotion detection and classification have always been hot research topics. The recently adopted networks to train FERs are yet to focus on issues caused due to overfitting, effectuated by insufficient data for training and expression unrelated variations like gender bias, face occlusions and others. Association of FER with the Speech Emotion Recognition (SER) triggered the development of multimodal neural networks for emotion classification in which the application of sensors played a significant role as they substantially increased the accuracy by providing high quality inputs, further elevating the efficiency of the system. This thesis relates to the exploration of different principles behind application of deep neural networks with a strong focus towards Convolutional Neural Networks (CNN) and Generative Adversarial Networks (GAN) in regards to their applications to emotion recognition. A Motion Magnification algorithm for ME's detection and classification was implemented for applications requiring near real-time computations. A new and improved architecture using a Multimodal Network was implemented. In addition to the motion magnification technique for emotion classification and extraction, the Multimodal algorithm takes the audio-visual cues as inputs and reads the MEs on the real face of the participant. This feature of the above architecture can be deployed while administering interviews, or supervising ICU patients in hospitals, in the auto industry, and many others. The real-time emotion classifier based on state-of-the-art Image-Avatar Animation model was tested on simulated subjects. The salient features of the real-face are mapped on avatars that are build with a 3D scene generation platform. In pursuit of the goal of emotion classification, the Image Animation model outperforms all baselines and prior works. Extensive tests and results obtained demonstrate the validity of the approach.

Image reconstruction is the process of converting a sampled image into a continuous one prior to transformation and resampling. This reconstruction can be more accurate if two things are known: the process by which the sampled image was obtained and the general characteristics of the original image. We present a new reconstruction algorithm known as Constraint-Based Interpolation, which estimates the sampling functions found in cameras and analyzes properties of real world images in order to produce quality real-world image magnifications. To accomplish this, Constraint-Based Interpolation uses a sensor model that pushes the pixels in an interpolation to more closely match the data in the sampled image. Real-world image properties are ensured with a level-set smoothing model that smooths "jaggies" and a sharpening model that alleviates blurring. This thesis describes the three models, their methods and constraints. The effects of the various models and constraints are also shown, as well as a human observer test. A variation of a previous interpolation technique, Quad-based Interpolation, and a new metric, gradient weighted contour curvature, is presented and analyzed.