SSM-HPC: Front View Gait Recognition Using Spherical Space Model with Human Point Clouds

Jegoon RYU  Sei-ichiro KAMATA  Alireza AHRARY  

IEICE TRANSACTIONS on Information and Systems   Vol.E95-D   No.7   pp.1969-1978
Publication Date: 2012/07/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E95.D.1969
Print ISSN: 0916-8532
Type of Manuscript: PAPER
Category: Image Recognition, Computer Vision
gait recognition,  human point clouds (HPC),  silhouette image,  stereo camera,  principal component analysis (PCA),  linear discriminate analysis (LDA),  

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In this paper, we propose a novel gait recognition framework - Spherical Space Model with Human Point Clouds (SSM-HPC) to recognize front view of human gait. A new gait representation - Marching in Place (MIP) gait is also introduced which preserves the spatiotemporal characteristics of individual gait manner. In comparison with the previous studies on gait recognition which usually use human silhouette images from image sequences, this research applies three dimensional (3D) point clouds data of human body obtained from stereo camera. The proposed framework exhibits gait recognition rates superior to those of other gait recognition methods.