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Gait Recognition Using Multiple Feature detection  

Cho, Woon (Dept. Image Engineering, Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University)
Kim, Dong-Hyeon (Dept. Image Engineering, Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University)
Paik, Joon-Ki (Dept. Image Engineering, Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea SP / v.44, no.6, 2007 , pp. 84-92 More about this Journal
Abstract
The gait recognition is presented for human identification from a sequence of noisy silhouettes segmented from video by capturing at a distance. The proposed gait recognition algorithm gives better performance than the baseline algorithm because of segmentation of the object by using multiple modules; i) motion detection, ii) object region detection, iii) head detection, and iv) active shape models, which solve the baseline algorithm#s problems to make background, to remove shadow, and to be better recognition rates. 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.
Keywords
Gait recognition; Multiple feature detection; Active shape models; Silhouette extraction;
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