[1]柳培忠,阮晓虎,田震,等.一种基于多特征融合的视频目标跟踪方法[J].智能系统学报,2014,9(03):319-324.[doi:10.3969/j.issn.1673-4785.201309085]
 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(03):319-324.[doi:10.3969/j.issn.1673-4785.201309085]
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一种基于多特征融合的视频目标跟踪方法(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第9卷
期数:
2014年03期
页码:
319-324
栏目:
出版日期:
2014-06-25

文章信息/Info

Title:
A video tracking method based on object multi-feature fusion
作者:
柳培忠1 阮晓虎2 田震2 李卫军2 覃鸿2
1. 华侨大学 工学院, 福建 泉州 362000;
2. 中国科学院半导体研究所 高速电路与神经网络实验室, 北京 100083
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
关键词:
视频跟踪背景建模前景检测特征提取特征融合
Keywords:
video trackingbackground modelingforeground detectionfeature extractionmulti-feature fusion
分类号:
TP391
DOI:
10.3969/j.issn.1673-4785.201309085
摘要:
在预警系统和目标记录方面, 传统的视频跟踪方法无法很好地解决目标重现和遮挡等问题, 针对此类问题提出了一种融合多特征的视频目标跟踪方法, 首先用背景建模的方法检测运动前景, 分离目标图像, 通过目标连续帧间的位移信息实现跟踪, 对多目标帧间位移相近的情况, 融合目标SIFT和彩色直方图特征进行目标匹配, 并记录目标各帧的运动状态, 最终实现目标运动的跟踪。实验结果表明, 该方法对多目标缓慢变化的监控视频有较好的跟踪效果。
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.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2013-09-30。
基金项目:国家自然科学基金重大研究计划资助项目(90920013)
作者简介:柳培忠,男,1976年生,讲师,博士,美国杜克大学高级访问学者,主要研究方向为仿生图像处理技术、仿生模式识别理论与方法、网络视觉媒体检索技术、微波成像分析等;阮晓虎,男,1986年生,硕士研究生,主要研究方向为视频、图像处理、模式识别、深度学习相关算法。参与国家自然科学基金重大研究计划项目1项。
通讯作者:田震,男,1988年生,硕士研究生,主要研究方向为图像处理、智能监控系统、模式识别等,E-mail:tianzhen@semi.ac.cn。
更新日期/Last Update: 1900-01-01