Análise de Movimento Não Rígido em Visão por Computador

Neste artigo são apresentadas várias metodologias actualmente existentes, no domínio da Visão por Computador, para a análise de movimento não rígido e são indicados diversos exemplos de aplicações. Assim o movimento não rígido é classificado e, para cada classe resultante, são indicadas as restrições e as condições inerentes e verificados alguns trabalhos realizados no seu âmbito. Como as questões de análise de movimento e modelização da forma se tornam inseparáveis quando se considera o movimento do tipo não rígido, a modelização sugere uma classificação possível da forma não rígida e do movimento. Assim são também apresentados modelos de forma para objectos deformáveis e indicados vários exemplos de aplicações. Com este estudo, de certo modo aprofundado, das várias metodologias, e suas aplicações, existentes no domínio da análise de movimento não rígido, espera-se contribuir para o seu desenvolvimento, dada a actual carência de boas revisões do estado da arte neste domínio.In this article several methodologies actually existent, in the Computer Vision domain, for non-rigid movement analysis are presented and several examples of applications are indicated. Thus the non-rigid movement is classified and, for each resulting class, the restrictions and the inherent conditions are presented and some works accomplished in its ambit are verified. As the questions of movement and shape analysis becomes non-separable when its considered the movement of the non-rigid type, the shape models also suggests a possible classification of the non-rigid shape and of the movement. Thus shape models for deformable objects will be presented and some examples of applications indicated. With this study, in certain way deep, of several methodologies, and its applications, existent in the domain of the non-rigid movement analysis, the authors hope to contribute for its development, given the actual lack of good state of the art revisions in this domain

Análise de Movimento Não Rígido em Visão por Computador

Neste artigo são apresentadas várias metodologias actualmente existentes, no domínio da Visão por Computador, para a análise de movimento não rígido e são indicados diversos exemplos de aplicações. Assim o movimento não rígido é classificado e, para cada classe resultante, são indicadas as restrições e as condições inerentes e verificados alguns trabalhos realizados no seu âmbito. Como as questões de análise de movimento e modelização da forma se tornam inseparáveis quando se considera o movimento do tipo não rígido, a modelização sugere uma classificação possível da forma não rígida e do movimento. Assim são também apresentados modelos de forma para objectos deformáveis e indicados vários exemplos de aplicações. Com este estudo, de certo modo aprofundado, das várias metodologias, e suas aplicações, existentes no domínio da análise de movimento não rígido, espera-se contribuir para o seu desenvolvimento, dada a actual carência de boas revisões do estado da arte neste domínio

Longitudinal video Investigation of dyadic bodily dynamics around the time of word acquisition

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2010.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student submitted PDF version of thesis.Includes bibliographical references (p. 105-110).Human movement encodes information about internal states and goals. When these goals involve dyadic interactions, such as in language acquisition, the nature of the movement and proximity become representative, allowing parts of our internal states to manifest. We propose an approach called Visually Grounded Virtual Accelerometers (VGVA), to aid with ecologically-valid video analysis investigations, involving humans during dyadic interactions. Utilizing the Human Speechome (HSP) [1] video corpus database, we examine a dyadic interaction paradigm taken from the caregiver-child ecology, during language acquisition. We proceed to characterize human interaction in a video cross-modally; by visually detecting and assessing the child's bodily dynamics in a video, grounded on the caregiver's bodily dynamics of the same video and the related HSP speech transcriptions [2]. Potential applications include analyzing a child's language acquisition, establishing longitudinal diagnostic means for child developmental disorders and generally establishing a metric of effective human communication on dyadic interactions under a video surveillance system. In this thesis, we examine word-learning transcribed video episodes before and after the age of the word's acquisition (AOA). As auditory stimulus is uttered from the caregiver, points along the VGVA tracked sequences corresponding to the onset and post-onset of the child-caregiver bodily responses, are used to longitudinally mark and characterize episodes of word learning. We report a systematic shift in terms of caregiver-child synchrony in motion and turning behavior, tied to exposures of the target word around the time the child begins to understand and thus respond to instances of the spoken word. The systematic shift, diminishes gradually after the age of word acquisition (AOA).by Kleovoulos (Leo) Tsourides.S.M

Adjusting Shape Parameters using Model-Based Optical Flow Residuals

We present a method for estimating the shape of a deformable model using the least-squares residuals from a model-based optical flow computation. This method is built on top of an estimation framework using optical flow and image features, where optical flow affects only the motion parameters of the model. Using the results of this computation, our new method adjusts all of the parameters so that the residuals from the flow computation are minimized. We present face tracking experiments that demonstrate that this method obtains a better estimate of shape compared to related frameworks. Index terms: non-rigid shape and motion estimation, model-based optical flow, deformable models

Automatische Registrierung adaptiver Modelle zur Typerkennung technischer Objekte [online]

Anwendungen der Bildanalyse werden in zunehmendem Maße unter Verwendung dreidimensionaler Modelle realisiert und fusionieren auf diese Weise Methoden der Computergrafik und der Bildauswertung. Mit dem Ziel der automatischen Erfassung dynamischer Szenenaktivitäten ist in den letzten Jahren ein vermehrter Einsatz adaptiver Modelle zu beobachten. In der vorliegenden Arbeit wird ein neu entwickeltes Verfahren zur automatischen Konstruktion adaptiver Modelle für technische Objekte vorgestellt. Ferner werden Module zur automatischen Anpassung dieser adaptiven Modelle an Grauwertbilder beschrieben, die durch Synthese-Analyse-Iterationen die Brücke zur Bildanalyse schlagen. Die zentrale Stärke der vorgestellten Komponenten liegt darin, dass sie aus Einzelbildern dreidimensionale Rekonstruktionen für unbekannte Objektvarianten liefern. Wie experimentell gezeigt wird, sind diese Rekonstruktionen geometrisch genauer als handelsübliche Modelle. Die Leistungsfähigkeit der entwickelten Verfahren wird am Beispiel der Flugzeugtypisierung gezeigt. Darüber hinaus wird die Anwendbarkeit der Module zur Lageschätzung demonstriert

Toward Computational Understanding Of Sign Language

In this paper, we describe some of the current issues in computational sign language processing. Despite the seeming similarities between computational spoken language and sign language processing, signed languages have intrinsic properties that pose some very difficult problems. These include a high level of simultaneous actions, the intersection between signs and gestures, and the complexity of modeling grammatical processes. Additional problems are posed by the difficulties that computers face in extracting reliable information on the hands and the face from video images. So far, no single research group or company has managed to tackle all the hard problems and produced a real working system for analysis and recognition. We present a summary of our research into sign language recognition and how it interacts with sign language linguistics. We propose solutions to some of the aforementioned problems, and also discuss what problems are still unsolved. 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