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Titlebook: Computer Vision - ECCV 2004; 8th European Confere Tomáš Pajdla,Jiří Matas Conference proceedings 2004 Springer-Verlag Berlin Heidelberg 200

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楼主: INFER
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Shape Reconstruction from 3D and 2D Data Using PDE-Based Deformable Surfacesshape reconstruction from volumetric data, unorganized 3D point clouds and multiple view images. The versatility and robustness of our model allow its application to the challenging problem of multiple view reconstruction. Our approach is unique in its combination of simultaneous use of a high numbe
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0302-9743 mittee members know how authors reacted to their reviews and how their reviews were or were not re?ected in the ?nal decision. Finally, we reduced the length of reviewed papers from 15 to 12 pa978-3-540-21982-8978-3-540-24672-5Series ISSN 0302-9743 Series E-ISSN 1611-3349
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A Constrained Semi-supervised Learning Approach to Data Associations, matching image features to object recognition models and matching image features to semantic concepts. In this paper, we show how a wide class of data association tasks arising in computer vision can be interpreted as a constrained semi-supervised learning problem. This interpretation opens up ro
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Decision Theoretic Modeling of Human Facial Displaysision process, or POMDP. A POMDP is a stochastic planner used by an agent to relate its actions and utility function to its observations and to other context. Video observations are integrated into the POMDP using a dynamic Bayesian network that creates spatial and temporal abstractions of the input
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Kernel Feature Selection with Side Data Using a Spectral Approachable) solutions. In particular, this topic includes on one hand the introduction of hand-crafted kernels which emphasize certain desirable aspects of the data and, on the other hand, the suppression of one of the solutions given “side” data, i.e., when one is given information about undesired aspect
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Tracking Articulated Motion Using a Mixture of Autoregressive Modelsstic motion patterns that exist in typical human activities. Our method is based on automatically clustering the body pose space into connected regions exhibiting similar dynamical characteristics, modelling the dynamics in each region as a Gaussian autoregressive process. Activities that would requ
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3D Human Body Tracking Using Deterministic Temporal Motion Modelstic in nature and seek to avoid becoming trapped into local minima by considering multiple hypotheses, which typically requires exponentially large amounts of computation as the number of degrees of freedom increases..By contrast, in this paper, we use temporal motion models based on Principal Compo
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