Chrono-gait image: a novel temporal template for gait recognition

Authors:
Chen Wang;Junping Zhang;Jian Pu;Xiaoru Yuan;Liang Wang
Affiliations:
Shanghai Key Lab of Intelligent Information Processing, School of Computer Science, Fudan University, China;Shanghai Key Lab of Intelligent Information Processing, School of Computer Science, Fudan University, China;Shanghai Key Lab of Intelligent Information Processing, School of Computer Science, Fudan University, China;Key Laboratory of Machine Perception, Ministry of Education, School of Electronics Engineering and Computer Science, Peking University, Beijing, China;Department of Computer Science, University of Bath, United Kingdom and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, China
Venue:
ECCV'10 Proceedings of the 11th European conference on Computer vision: Part I
Year:
2010

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Abstract

In this paper, we propose a novel temporal template, called Chrono-Gait Image (CGI), to describe the spatio-temporal walking pattern for human identification by gait. The CGI temporal template encodes the temporal information among gait frames via color mapping to improve the recognition performance. Our method starts with the extraction of the contour in each gait image, followed by utilizing a color mapping function to encode each of gait contour images in the same gait sequence and compositing them to a single CGI. We also obtain the CGI-based real templates by generating CGI for each period of one gait sequence and utilize contour distortion to generate the CGI-based synthetic templates. In addition to independent recognition using either of individual templates, we combine the real and synthetic temporal templates for refining the performance of human recognition. Extensive experiments on the USF HumanID database indicate that compared with the recently published gait recognition approaches, our CGI-based approach attains better performance in gait recognition with considerable robustness to gait period detection.