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Orthogonal Diagonal Projections for Gait Recognition
Daoliang Tan; Kaiqi Huang; Shiqi Yu; Tieniu Tan
2007
Conference NameIEEE International Conference on Image Processing, 2007
Source PublicationIEEE International Conference on Image Processing, 2007
Pages337-340
Conference Date2007-09-01
Conference Place San Antonio, Texas, USA
AbstractGait has received much attention from researchers in the vision field due to its utility in walker identification. One of the key issues in gait recognition is how to extract discriminative shape features from 2D human silhouette images. This paper deals with the problem of gait-based walker recognition using statistical shape features. First, we normalize walkers' silhouettes (to facilitate gait feature comparison) into a square form and use the orthogonal projections in the positive and negative diagonal directions to draw personal signatures contained in gait patterns. Then principal component analysis (PCA) and linear discriminant analysis (LDA) are applied to reduce the dimensionality of original gait features and to improve the topological structure in the feature space. Finally, this paper accomplishes the recognition of unknown gait features based on the nearest neighbor rule, with the discussion of the effect of distance metrics and scales on discriminating performance. Experimental results justify the potential of our method.
KeywordComputer Vision   feature Extraction   gait Analysis
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12719
Collection智能感知与计算研究中心
Corresponding AuthorKaiqi Huang
Affiliation中国科学院自动化研究所
Recommended Citation
GB/T 7714
Daoliang Tan,Kaiqi Huang,Shiqi Yu,et al. Orthogonal Diagonal Projections for Gait Recognition[C],2007:337-340.
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