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http://dx.doi.org/10.5391/JKIIS.2011.21.1.6

Gait-based Human Identification System using Eigenfeature Regularization and Extraction  

Lee, Byung-Yun (연세대학교 전기전자공학부)
Hong, Sung-Jun (연세대학교 전기전자공학부)
Lee, Hee-Sung (연세대학교 전기전자공학부)
Kim, Eun-Tai (연세대학교 전기전자공학부)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.21, no.1, 2011 , pp. 6-11 More about this Journal
Abstract
In this paper, we propose a gait-based human identification system using eigenfeature regularization and extraction (ERE). First, a gait feature for human identification which is called gait energy image (GEI) is generated from walking sequences acquired from a camera sensor. In training phase, regularized transformation matrix is obtained by applying ERE to the gallery GEI dataset, and the gallery GEI dataset is projected onto the eigenspace to obtain galley features. In testing phase, the probe GEI dataset is projected onto the eigenspace created in training phase and determine the identity by using a nearest neighbor classifier. Experiments are carried out on the CASIA gait dataset A to evaluate the performance of the proposed system. Experimental results show that the proposed system is better than previous works in terms of correct classification rate.
Keywords
Biometrics; gait recognition; gait energy image; eigenfeature regularization and extraction;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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