Gait recognition using active shape models

Authors:
Woon Cho;Taekyung Kim;Joonki Paik
Affiliations:
Image Processing and Intelligent Systems Laboratory, Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University, Seoul, South Korea;Image Processing and Intelligent Systems Laboratory, Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University, Seoul, South Korea;Image Processing and Intelligent Systems Laboratory, Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University, Seoul, South Korea
Venue:
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Year:
2007

Citing 5
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Abstract

The gait recognition is presented for human identification from a sequence of noisy silhouettes segmented from video. The proposed gait recognition algorithm gives better performance than the baseline algorithm because of segmentation of the object by using active shape model (ASM) algorithm. For the experiment, we used the HumanID Gait Challenge data set, which is the largest gait benchmarking data set with 122 objects, For realistic simulation we use various values for the following parameters; i) viewpoint, ii) shoe, iii) surface, iv) carrying condition, and v) time.