标题：Crowd Foreground Detection and Density Estimation Based on Moment
作者：Li, Wei; Wu, Xiaojuan; Matsumo, Koichi; Zhao, Hua-An
作者机构：[Li, Wei; Wu, Xiaojuan] Shandong Univ, Sch Informat Sci & Engn, Jinan 250100, Shandong, Peoples R China.; [Matsumo, Koichi; Zhao, Hua-An] Kumamoto U 更多
会议名称：2010 International Conference on Wavelet Analysis and Pattern Recognition
会议日期：JUL 11-14, 2010
来源：PROCEEDINGS OF THE 2010 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION
关键词：Segmentation; feature extraction; motion analysis
摘要：This paper focuses on crowd motion analysis and consists two parts. Firstly, we propose a new foreground detection approach called optical flow and background model (OFBM) based on Lucas-Kanade optical flow and Gaussian background model methods. This approach overcomes the shortages of optical flow and background subtract, such as sensitiveness of light changing and producing accumulate errors. Secondly, according to moment analysis, we propose a new feature based on the zeroth-order Tehebichef discrete orthogonal moment (TOM), which is employed for crowd density estimation. Some experimental results show that this approach is useful and efficient in crowd density estimation.