Frontal gait recognition based on spatio-temporal interest points |
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Authors: | Chin-Chun Huang Chu-Chun Hsu Hsi-Yun Liao Sheng-Hsuan Yang Ling-Ling Wang |
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Affiliation: | 1. Department of Computer Science and Engineering, Yuan Ze University, Taoyuan, Taiwan, ROC;2. Department of Information Communication, Asia University, Taichung, Taiwan, ROC |
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Abstract: | This paper proposes a spatio-temporal interest point (STIP)-based human gait recognition method for frontal gait videos. The proposed method extracts histograms of oriented gradient (HOG) for STIPs directly from gait videos without involving a gait cycle segment, which is required by silhouette analysis as used by most gait recognition methods. Moreover, silhouette extraction may be affected by noise and carried objects leading to consequent recognition error. Matches of STIPs between two gait videos are then found in terms of HOG to measure the similarity of two videos so as to achieve the goal of gait recognition. The experimental results offer evidence that our method outperforms the existing methods on the Carnegie-Mellon University Motion of Body database and the Chinese Academy of Sciences Institute of Automation data-set B. |
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Keywords: | Frontal gait recognition spatio-temporal interest points histogram of oriented gradient individual identification |
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