摘要
A novel method was proposed, which extracted video object＇ s track and analyzed video object＇ s be- havior. Firstly, this method tracked the video object based on motion history image, and obtained the co- ordinate-based track sequence and orientation-based track sequence of the video object. Then the pro- posed hidden markov model （HMM） based algorithm was used to analyze the behavior of video object with the track sequence as input. Experimental results on traffic object show that this method can achieve the statistics of a mass of traffic objects＇ behavior efficiently, can acquire the reasonable velocity behavior curve of traffic object, and can recognize traffic object＇ s various behaviors accurately. It provides a base for further research on video object behavior.
A novel method was proposed,which extracted video object' s track and analyzed video object's be-havior.Firstly,this method tracked the video object based on motion history image,and obtained the co-ordinate-based track sequence and orientation-based track sequence of the video object.Then the pro-posed hidden markov model(HMM)based algorithm was used to analyze the behavior of video object withthe track sequence as input.Experimental results on traffic object show that this method can achieve thestatistics of a mass of traffic objects'behavior efficiently,can acquire the reasonable velocity behaviorcurve of traffic object,and can recognize traffic object's various behaviors accurately.It provides a basefor further research on video obiect behavior.
基金
supported by the High Technology Research and Development Programme of China(No.2004AA742209)
作者简介
To whom correspondence should be addressed. E-mail： mengfanfeng@ sohu. com Meng Fanfeng, born in 1976. He is a Ph. D can- didate in Depatment of Control Science and Engineering of Harbin Institute of Technology. He received his B.S. and M.S. degrees from Harbin Institute of Technology in 1999 and 2004 respectively. His research interests in- clude image process and vision control.
