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This paper presents a robust framework for online full-body gesture spotting from visual hull data. Using view-invariant pose features as observations, hidden Markov models (HMMs) are trained for gesture spotting from continuous movement data streams. Two major contributions of this paper are 1) view-invariant pose feature extraction from visual hulls, and 2) a systematic approach to automatically...
This paper presents a gesture recognition framework using voxel data obtained through visual hull reconstruction from multiple cameras. View-invariant pose descriptors are extracted by projecting voxel data onto a low dimensional pose coefficient space using multilinear analysis. Gestures are then treated as sequences of pose descriptors and represented by hidden Markov models for gesture recognition...
In this paper, we propose a video-based full-body gesture recognition system independent of the view angle of the cameras. We performed multilinear analysis on the silhouette images of the static poses making up the gestures by tensor decomposition and projection. Each pair of silhouette images is projected to a view-invariant low dimensional pose coefficient vector space. These pose vectors are then...
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