Abnormal Event Detection Using HOSF
學年 102
學期 1
發表日期 2013-12-16
作品名稱 Abnormal Event Detection Using HOSF
作品名稱（其他語言）
著者 Yen, Shwu-Huey; Wang, Chun-Hui
作品所屬單位 淡江大學資訊工程學系
出版者
會議名稱 The International Conference on IT Convergence and Security (ICITCS 2013)
會議地點 Macau
摘要 In this paper a simple and effective crowd behavior normality method is proposed. We use the histogram of oriented social force (HOSF) as the feature vector to encode the observed events of a surveillance video. A dictionary of codewords is trained to include typical HOSFs. To detect whether an event is normal is accomplished by comparing how similar to the closest codeword via z-value. The proposed method includes the following characteristic: (1) the training is automatic without human labeling; (2) instead of object tracking, the method integrates particles and social force as feature descriptors; (3) z-score is used in measuring the normality of events. The method is testified by the UMN dataset with promising results.
關鍵字 normality;crowd;social force (SF);histogram of oriented social force (HOSF);z-value
語言 en
收錄於
會議性質 國際
校內研討會地點
研討會時間 20131216~20131218
通訊作者
國別 MAC
公開徵稿 Y
出版型式 電子版
出處 Proceedings of the International Conference on IT Convergence and Security (ICITCS 2013), 4p.
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/97001 )

機構典藏連結