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Multi-gait recognition using hypergraph partition.
- Source :
-
Machine Vision & Applications . Feb2017, Vol. 28 Issue 1/2, p117-127. 11p. - Publication Year :
- 2017
-
Abstract
- Gait recognition is a challenging problem in computer vision, especially when multi-persons walk together, called as multi-gait recognition. Multi-gait recognition includes two aspects: participant segmentation and participant recognition. In this paper, we propose to segment each participant by hypergraph partition and recognize each participant by multi-linear canonical correlation analysis algorithm (UMCCA). Firstly, raw pixel areas are obtained by grid, and each pixel area is taken as a hypergraph vertex. Then HOG-based detection and tracking technology is used to calculate the weight of each hyperedge. After segmentation, UMCCA is used to extract gait features. Finally, identity of multi-gait is recognized. The experimental results demonstrate that our proposed method achieves good performance on multi-gait dataset. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 09328092
- Volume :
- 28
- Issue :
- 1/2
- Database :
- Academic Search Index
- Journal :
- Machine Vision & Applications
- Publication Type :
- Academic Journal
- Accession number :
- 121198167
- Full Text :
- https://doi.org/10.1007/s00138-016-0810-6