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Abnormal activity recognition in office based on T-transform", International Conference on Image Processing
Ying Wang; Kaiqi Huang; Tieniu Tan
2007
Conference NameIEEE International Conference on Image Processing, 2007
Source PublicationIEEE International Conference on Image Processing, 2007
Pages341-344
Conference Date2007-09-01
Conference Place San Antonio, Texas, USA
AbstractThis paper introduces an abnormal activity recognition method based on a new feature descriptor for human silhouette. For a binary human silhouette, an extended radon transform, R transform, is employed to represent low-level features. The information that the initial silhouette carries is transformed in a compact way preserving important spatial information of the activities. Then a set of HMMs based on the features extracted by our method are trained to recognize abnormal activities. Experiments have proved the accuracy and efficiency of the proposed method, and the comparison with Fourier descriptor illustrates its robustness to disjoint shapes and shapes with holes.
KeywordEdge Detection   feature Extraction   hidden Markov Models
Language英语
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/12718
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
Ying Wang,Kaiqi Huang,Tieniu Tan. Abnormal activity recognition in office based on T-transform", International Conference on Image Processing[C],2007:341-344.
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