Proceedings Paper
Zernike moments features for shape-based gait recognition| Format | Member Price | Non-Member Price |
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Paper Abstract
The paper proposes a new spatio-temporal gait representation, called cycles gait Zernike moments (CGZM), to
characterize human walking properties for individual recognition. Firstly, Zernike moments as shape descriptors are used
to characterize gait silhouette shape. Secondly, we generate CGZM from Zernike moments of silhouette sequences.
Finally, the phase and magnitude coefficientsof CGZM are utilized to perform classification by the modified Hausdorff
distance (MHD) classifier. Experimental results show that the proposed approach have an encouraging recognition
performance.
Paper Details
Date Published: 15 November 2011
PDF: 6 pages
Proc. SPIE 8321, Seventh International Symposium on Precision Engineering Measurements and Instrumentation, 832132 (15 November 2011); doi: 10.1117/12.905211
Published in SPIE Proceedings Vol. 8321:
Seventh International Symposium on Precision Engineering Measurements and Instrumentation
Kuang-Chao Fan; Man Song; Rong-Sheng Lu, Editor(s)
PDF: 6 pages
Proc. SPIE 8321, Seventh International Symposium on Precision Engineering Measurements and Instrumentation, 832132 (15 November 2011); doi: 10.1117/12.905211
Show Author Affiliations
Jun Liu, Chongqing Univ. (China)
Jiang Chao, Chongqing Univ. (China)
Jiang Chao, Chongqing Univ. (China)
Published in SPIE Proceedings Vol. 8321:
Seventh International Symposium on Precision Engineering Measurements and Instrumentation
Kuang-Chao Fan; Man Song; Rong-Sheng Lu, Editor(s)
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