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Uniprojective Features for Gait Recognition
Daoliang Tan; Kaiqi Huang; Shiqi Yu; Tieniu Tan
2007
会议名称the 2nd International Conference on Biometrics
会议录名称International Conference on Advances in Biometrics, 2007
页码673-682
会议日期2007
会议地点Seoul, Korea
摘要Recent studies have shown that shape cues should dominate gait recognition. This motivates us to perform gait recognition through shape features in 2D human silhouettes. In this paper, we propose six simple projective features to describe human gait and compare eight kinds of projective features to figure out which projective directions are important to walker recognition. First, we normalize each original human silhouette into a square form. Inspired by the pure horizontal and vertical projections used in the frieze gait patterns, we explore the positive and negative diagonal projections with or without normalizing silhouette projections and obtain six new uniprojective features to characterize walking gait. Then this paper applies principal component analysis (PCA) to reduce the dimension of raw gait features. Finally, we recognize unknown gait sequences using the Mahalanobis-distance-based nearest neighbor rule. Experimental results show that the horizontal and diagonal projections have more discriminative clues for the side-view gait recognition and that the projective normalization generally can improve the robustness of projective features against the noise in human silhouettes.
关键词Gait Recognition   projective Features   pca
语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/12721
专题智能感知与计算研究中心
通讯作者Kaiqi Huang
作者单位中国科学院自动化研究所
推荐引用方式
GB/T 7714
Daoliang Tan,Kaiqi Huang,Shiqi Yu,et al. Uniprojective Features for Gait Recognition[C],2007:673-682.
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