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Topology Dictionary for 3D Video Understanding
2012
IEEE Transactions on Pattern Analysis and Machine Intelligence
This paper presents a novel approach that achieves 3D video understanding. 3D video consists of a stream of 3D models of subjects in motion. The acquisition of long sequences requires large storage space (2 GB for 1 min). Moreover, it is tedious to browse data sets and extract meaningful information. We propose the topology dictionary to encode and describe 3D video content. The model consists of a topology-based shape descriptor dictionary which can be generated from either extracted patterns
doi:10.1109/tpami.2011.258
pmid:22745004
fatcat:hn4vet5x7jcjxgijszcuxgxisu