Uniprojective Features for Gait   Recognition

CASIA OpenIR > 智能感知与计算研究中心

	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
第一作者单位	中国科学院自动化研究所
通讯作者单位	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.