TY - GEN
T1 - Fusion of multiple gait cycles for human identification
AU - Hong, Sungjun
AU - Lee, Heesung
AU - Kim, Euntai
PY - 2009
Y1 - 2009
N2 - In this paper, a gait recognition system fusing multiple gait cycles is presented for human identification. First, the cycle length is estimated by calculating the autocorrelation of the foreground sum signal. After gait cycle partitioning, we extract two kinds of gait feature, gait energy image (GEI) and motion silhouette image (MSI). To identify individual, the outputs of the nearest neighbor classifiers are fused at the abstract level based on majority voting. Our proposed system is tested on the CASIA gait dataset A and the SOTON gait database. Compared to previous works, our empirical results show extraordinary performance in terms of correct classification rate.
AB - In this paper, a gait recognition system fusing multiple gait cycles is presented for human identification. First, the cycle length is estimated by calculating the autocorrelation of the foreground sum signal. After gait cycle partitioning, we extract two kinds of gait feature, gait energy image (GEI) and motion silhouette image (MSI). To identify individual, the outputs of the nearest neighbor classifiers are fused at the abstract level based on majority voting. Our proposed system is tested on the CASIA gait dataset A and the SOTON gait database. Compared to previous works, our empirical results show extraordinary performance in terms of correct classification rate.
UR - http://www.scopus.com/inward/record.url?scp=77951103600&partnerID=8YFLogxK
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M3 - Conference contribution
AN - SCOPUS:77951103600
SN - 9784907764333
T3 - ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
SP - 3171
EP - 3175
BT - ICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
T2 - ICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009
Y2 - 18 August 2009 through 21 August 2009
ER -