We present a novel approach to inferring 3D volumetric shape of both moving objects and static background from video sequences shot by a moving camera, with the assumption that th...
We present a common variational framework for dense depth recovery and dense three-dimensional motion field estimation from multiple video sequences, which is robust to camera spe...
Jean-Philippe Pons, Renaud Keriven, Olivier D. Fau...
We combine detection and tracking techniques to achieve robust 3?D motion recovery of people seen from arbitrary viewpoints by a single and potentially moving camera. We rely on d...
Andrea Fossati, Miodrag Dimitrijevic, Vincent Lepe...
This paper addresses the reconstruction of 3 0 human body models fram Z D video sequences. Considering that the input frames are already segmented, the proposed technique consists...
We propose the use of 3D (2D+time) Shape Context to recognize the spatial and temporal details inherent in human actions. We represent an action in a video sequence by a 3D point ...
Franziska Meier, Irfan A. Essa, Matthias Grundmann