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Real-time traffic information extraction based on compressed video with interframe motion vector
作者姓名:黄庆明  王聪
作者单位:Joint R&D Lab,Graduate School,Chinese Academy of Sciences,Beijing 100080,China,School of Astronautics,Harbin Institute of Technology,Harbin 150001,China
摘    要:Extraction of traffic information from image or video sequence is a hot research topic in intelligent transportation system and computer vision. A real-time traffic information extraction method based on compressed video with interframe motion vectors for speed, density and flow detection, has been proposed for extraction of traffic information under fixed camera setting and well-defined environment. The motion vectors are first separated from the compressed video streams, and then filtered to eliminate incorrect and noisy vectors using the well-defined environmental knowledge. By applying the projective transform and using the filtered motion vectors, speed can be calculated from motion vector statistics, density can be estimated using the motion vector occupancy, and flow can be detected using the combination of speed and density. The embodiment of a prototype system for sky camera traffic monitoring using the MPEG video has been implemented, and experimental results proved the effectiveness of the me


Real-time traffic information extraction based on compressed video with interframe motion vector
HUANG Qing-ming,WANG Cong.Real-time traffic information extraction based on compressed video with interframe motion vector[J].Journal of Harbin Institute of Technology,2003,10(3).
Authors:HUANG Qing-ming  WANG Cong
Affiliation:1. Joint R&D Lab, Graduate School, Chinese Academy of Sciences, Beijing 100080, China
2. School of Astronautics, Harbin Institute of Technology, Harbin 150001, China
Abstract:Extraction of traffic information from image or video sequence is a hot research topic in intelligent transportation system and computer vision. A real-time traffic information extraction method based on compressed video with interframe motion vectors for speed, density and flow detection, has been proposed for extraction of traffic information under fixed camera setting and well-defined environment. The motion vectors are first separated from the compressed video streams, and then filtered to eliminate incorrect and noisy vectors using the well-defined environmental knowledge. By applying the projective transform and using the filtered motion vectors, speed can be calculated from motion vector statistics, density can be estimated using the motion vector occupancy, and flow can be detected using the combination of speed and density. The embodiment of a prototype system for sky camera traffic monitoring using the MPEG video has been implemented, and experimental results proved the effectiveness of the method proposed.
Keywords:extraction of traffic information  Interframe motion vector  compressed video stream
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