[1]LIU Peizhong,RUAN Xiaohu,TIAN Zhen,et al.A video tracking method based on object multi-feature fusion[J].CAAI Transactions on Intelligent Systems,2014,9(3):319-324.[doi:10.3969/j.issn.1673-4785.201309085]
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A video tracking method based on object multi-feature fusion

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 9 Number of periods: 2014 3 Page number: 319-324 Column: 学术论文—智能系统 Public date: 2014-06-25
Title:
A video tracking method based on object multi-feature fusion
Author(s):
LIU Peizhong1;  RUAN Xiaohu2;  TIAN Zhen2;  LI Weijun2;  QIN Hong2
1. College of Engineering, Huaqiao University, Quanzhou 362000, China;
2. High Speed Circuit and Neural Network Laboratory, Institute of Semiconductors, Chinese Academy of Sciences, Beijing 100083, China
Keywords:
video tracking; background modeling; foreground detection; feature extraction; multi-feature fusion
CLC:
TP391
DOI:
10.3969/j.issn.1673-4785.201309085
Abstract:
Video tracking is a vital technique for the application of intelligent video surveillance. In terms of pre-warning systems and event recording, traditional video tracking methods cannot solve the problems of object reappearance and shadows very well. To tackle these problems, a video tracking method based on object multi-feature fusion is proposed. Firstly, the foreground of a moving target was detected using the method of background modeling, and the image of the moving target was separated from the video frame. Then the target that had been detected currently was set to match the target that appeared previously through the location information of the sequential frames of the object. Furthermore, considering the failure of the location matching, the SIFT(scale invariant feature transform ) and color histogram feature of the target image were extracted to match the different targets. The experimental results showed excellent performance of the real-time video tracking of multi-objects moving slowly in the general surveillance system.
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