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Simplex-Based 3D Spatio-temporal Feature Description for Action Recognition
2014
2014 IEEE Conference on Computer Vision and Pattern Recognition
We present a novel feature description algorithm to describe 3D local spatio-temporal features for human action recognition. Our descriptor avoids the singularity and limited discrimination power issues of traditional 3D descriptors by quantizing and describing visual features in the simplex topological vector space. Specifically, given a feature's support region containing a set of 3D visual cues, we decompose the cues' orientation into three angles, transform the decomposed angles into the
doi:10.1109/cvpr.2014.265
dblp:conf/cvpr/ZhangZRP14
fatcat:7wcjevidpjetnnubwl3d6vxrkq