Thesis (Ph. D.)--University of Hong Kong, 2006. / Title proper from title frame. Also available in printed format.

published_or_final_version / abstract / Computer Science / Doctoral / Doctor of Philosophy

published_or_final_version / Computer Science / Doctoral / Doctor of Philosophy

Recovering a volumetric model of a person, car, or other object of interest from a single snapshot would be useful for many computer graphics applications. 3D model estimation in general is hard, and currently requires active sensors, multiple views, or integration over time. For a known object class, however, 3D shape can be successfully inferred from a single snapshot. We present a method for generating a ``virtual visual hull''-- an estimate of the 3D shape of an object from a known class, given a single silhouette observed from an unknown viewpoint. For a given class, a large database of multi-view silhouette examples from calibrated, though possibly varied, camera rigs are collected. To infer a novel single view input silhouette's virtual visual hull, we search for 3D shapes in the database which are most consistent with the observed contour. The input is matched to component single views of the multi-view training examples. A set of viewpoint-aligned virtual views are generated from the visual hulls corresponding to these examples. The 3D shape estimate for the input is then found by interpolating between the contours of these aligned views. When the underlying shape is ambiguous given a single view silhouette, we produce multiple visual hull hypotheses; if a sequence of input images is available, a dynamic programming approach is applied to find the maximum likelihood path through the feasible hypotheses over time. We show results of our algorithm on real and synthetic images of people.

Thesis (Ph. D.)--University of Hong Kong, 2008. / Also available in print.

Recovering a volumetric model of a person, car, or other objectof interest from a single snapshot would be useful for many computergraphics applications. 3D model estimation in general is hard, andcurrently requires active sensors, multiple views, or integration overtime. For a known object class, however, 3D shape can be successfullyinferred from a single snapshot. We present a method for generating a``virtual visual hull''-- an estimate of the 3D shape of an objectfrom a known class, given a single silhouette observed from an unknownviewpoint. For a given class, a large database of multi-viewsilhouette examples from calibrated, though possibly varied, camerarigs are collected. To infer a novel single view input silhouette'svirtual visual hull, we search for 3D shapes in the database which aremost consistent with the observed contour. The input is matched tocomponent single views of the multi-view training examples. A set ofviewpoint-aligned virtual views are generated from the visual hullscorresponding to these examples. The 3D shape estimate for the inputis then found by interpolating between the contours of these alignedviews. When the underlying shape is ambiguous given a single viewsilhouette, we produce multiple visual hull hypotheses; if a sequenceof input images is available, a dynamic programming approach isapplied to find the maximum likelihood path through the feasiblehypotheses over time. We show results of our algorithm on real andsynthetic images of people.

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La consommation est considérée comme étant l'une des formes simples de la vie quotidienne. L'évolution de la société moderne a entraîné un environnement fortement chargé d'objets, de signes et d'interactions fondées sur des transactions commerciales. À ce phénomène s'ajoutent l'accélération du renouvellement de l'offre disponible et le pouvoir d'achat qui devient une préoccupation grandissante pour la majorité des consommateurs et oú l'inflation des prix est un sujet récurrent. Compte tenu de cette complexité et de ces enjeux économiques aussi consé- quents, la nécessité de modéliser le comportement d'achat des consommateurs dans les diffé- rents secteurs d'activité présente une phase primordiale pour les grands acteurs économiques ou analystes. En 2008, la société Cliris s'est lancée dans le projet de suivi multi-caméras de trajectoires des clients. En effet, le projet repose sur la mise au point d'un système d'analyse automatique multi-flux basé sur le suivi multi-caméras de clients. Ce système permet d'analy- ser la fréquentation et les parcours des clients dans les surfaces de grandes distributions. Dans le cadre de cette thèse CIFRE, nous avons abordé l'ensemble du processus de suivi multi-caméras de personnes tout en mettant l'accent sur le côté applicatif du problème en apportant notre contribution à la réponse aux questions suivantes :1. Comment suivre un individu à partir d'un flux vidéo mono-caméra en assurant la gestion des occultations ?2. Comment effectuer un comptage de personnes dans les surfaces denses ?3. Comment reconnaître un individu en différents points du magasin à partir des flux vidéo multi-caméras et suivre ainsi son parcours ? / ...

This thesis is written as an experiment in instrumentation and the factors of technical limitations of the typical Class C high school band. The criteria used in determining the instrumentation and the difficulty of the composition are certain findings with regard to grading of high school band music as found in John Phillip Dalby's Doctoral Dissertation, A STUDY OF INSTRUMENTATION, MUSICAL ACTIVITIES AND TECHNICAL COMPETENCE AS FACTORS IN ARRANGING FOR HIGH SCHOOL BAND.

Kara Walker, winner of the MacArthur “Genius” award and the Smithsonian Lucelia award, is one of the most critically acclaimed contemporary African American artists. Her work, especially her cut-paper silhouettes depicting grotesque antebellum scenes, has inspired as much outrage from an older generation of Black artists as acclaim from the mainstream media. This thesis gives an overview of the artist’s life, analysis of some of her works, and an examination of the controversy her work has caused. In the conclusion, I introduce the next generation of Black American artists, self-proclaimed “Art Stars,” including Atlanta artist Fahamu Pecou.