Titlebook: Dynamical Vision; ICCV 2005 and ECCV 2 René Vidal,Anders Heyden,Yi Ma Conference proceedings 2007 Springer-Verlag Berlin Heidelberg 2007 3D

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You have to ensure there are paradigmsthe image space. Although the intrinsic body configuration manifolds might be very low in dimensionality, the resulting appearance manifold is challenging to model given various aspects that affects the appearance such as the view point, the person shape and appearance, etc. In this paper we learn d

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Matias del Campo,Sandra Manningertored only implicitly as a set of silhouettes seen from multiple viewpoints; no explicit 3D poses or body models are used, and individual body parts are not identified. Actions and their constituent atomic poses are extracted from a set of multiview multiperson video sequences by an automatic keyfra

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Matias del Campo,Sandra Manningerhis approach has three steps: (i) Assume that a few frames are already registered. (ii) Using the registered frames, the next frame is predicted. (iii) A new video frame is registered to the predicted frame..Frame prediction overcomes the bias introduced by dynamics in the scene, even when dynamic o

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You have to ensure there are paradigmsels have been successfully applied to object recognition and tracking. However, the high dimensionality of such models present an obstacle to traditional particle filtering approaches. We can efficiently use parts-based models in a particle filter by applying Rao-Blackwellization to integrate out co

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Erratum to: Metallische Werkstoffe,ollow a Markovian process and interact with the hidden state either via its evolution model or via the observation process, or both. We consider here a general model that encompasses all these situations, and show how Bayesian filtering can be rigorously conducted with it. The resulting approach fac

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