Crowd density estimation in wide areas is a challenging problem for visual surveillance. Because of the high risk of degeneration, the safety of public events involving large crowds has always been a major concern. In...Crowd density estimation in wide areas is a challenging problem for visual surveillance. Because of the high risk of degeneration, the safety of public events involving large crowds has always been a major concern. In this paper, we propose a video-based crowd density analysis and prediction system for wide-area surveillance applications. In monocular image sequences, the Accumulated Mosaic Image Difference (AMID) method is applied to extract crowd areas having irregular motion. The specific number of persons and velocity of a crowd can be adequately estimated by our system from the density of crowded areas. Using a multi-camera network, we can obtain predictions of a crowd's density several minutes in advance. The system has been used in real applications, and numerous experiments conducted in real scenes (station, park, plaza) demonstrate the effectiveness and robustness of the proposed method.展开更多
The goal of this paper is to improve human visual perceptual quality as well as coding efficiency of H. 264 video at low bit rate conditions by adaptively adjusting the number of skipped frames. The encoding frames ar...The goal of this paper is to improve human visual perceptual quality as well as coding efficiency of H. 264 video at low bit rate conditions by adaptively adjusting the number of skipped frames. The encoding frames are selected according to the motion activity of each frame and the motion accumulation of successive frames. The motion activity analysis is based on the statistics of motion vectors and with consider- ation of the characteristics of H. 264 coding standard. A prediction model of motion accumulation is pro- posed to reduce complex computation of motion estimation. The dynamic encoding frame rate control algorithm is applied to both the frame level and the GOB （Group of Macroblocks ） level. Simulation is done to compare the performance of JM76 with the proposed frame level scheme and GOB level scheme.展开更多
基金supported by the National Natural Science Foundation of China under Grant No. 61175007the National Key Technologies R&D Program under Grant No. 2012BAH07B01the National Key Basic Research Program of China (973 Program) under Grant No. 2012CB316302
文摘Crowd density estimation in wide areas is a challenging problem for visual surveillance. Because of the high risk of degeneration, the safety of public events involving large crowds has always been a major concern. In this paper, we propose a video-based crowd density analysis and prediction system for wide-area surveillance applications. In monocular image sequences, the Accumulated Mosaic Image Difference (AMID) method is applied to extract crowd areas having irregular motion. The specific number of persons and velocity of a crowd can be adequately estimated by our system from the density of crowded areas. Using a multi-camera network, we can obtain predictions of a crowd's density several minutes in advance. The system has been used in real applications, and numerous experiments conducted in real scenes (station, park, plaza) demonstrate the effectiveness and robustness of the proposed method.
基金Supported by the High Technology. Research and Development Program of China （No. 2005AA103310） and the National Natural Science Foundation of China （No. 60202006）.
文摘The goal of this paper is to improve human visual perceptual quality as well as coding efficiency of H. 264 video at low bit rate conditions by adaptively adjusting the number of skipped frames. The encoding frames are selected according to the motion activity of each frame and the motion accumulation of successive frames. The motion activity analysis is based on the statistics of motion vectors and with consider- ation of the characteristics of H. 264 coding standard. A prediction model of motion accumulation is pro- posed to reduce complex computation of motion estimation. The dynamic encoding frame rate control algorithm is applied to both the frame level and the GOB （Group of Macroblocks ） level. Simulation is done to compare the performance of JM76 with the proposed frame level scheme and GOB level scheme.
