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基于梯度方向直方图特征的多核跟踪
引用本文:贾慧星,章毓晋.基于梯度方向直方图特征的多核跟踪[J].自动化学报,2009,35(10):1283-1289.
作者姓名:贾慧星  章毓晋
作者单位:1.清华大学信息科学与技术国家实验室 北京 100084
摘    要:提出了基于梯度方向直方图特征的多核跟踪算法, 对跟踪过程中的光线变化和部分遮挡具有较强的鲁棒性. 该算法将目标分块, 分别提取出每块的核函数加权的梯度方向直方图特征. 目标模型和候选目标模型的相似度用所有块直方图间的Bhattacharyya系数之和进行度量, 目标的跟踪通过Mean shift算法最大化两者的相似度实现. 对车辆、人体等多个目标的跟踪验证了本文提出算法的有效性.

关 键 词:Mean  shift    核跟踪    Bhattacharyya系数    梯度方向直方图
收稿时间:2008-8-13
修稿时间:2009-1-6

Multiple Kernels Based Object Tracking Using Histograms of Oriented Gradients
JIA Hui-Xing,ZHANG Yu-Jin.Multiple Kernels Based Object Tracking Using Histograms of Oriented Gradients[J].Acta Automatica Sinica,2009,35(10):1283-1289.
Authors:JIA Hui-Xing  ZHANG Yu-Jin
Affiliation:1.Tsinghua National Laboratory for Information Science and Technology, Tsinghua University Beijing 100084;2.Department of Electronic Engineering, Tsinghua University, Beijing 100084
Abstract:A novel multiple kernels based object tracking algorithm using histograms of oriented gradients is proposed in this paper, which is robust to illumination change and partial occlusion. The algorithm divides the object into blocks and extracts kernel weighted histograms of oriented gradients for each block. The similarity between target model and candidate model is measured by the sum of Bhattacharyya coefficients of all the corresponding histograms. The object is tracked by maximizing the similarity measure using the mean shift algorithm. Experiments on the tracking of vehicle and human demonstrate the effectiveness of the proposed algorithm.
Keywords:Mean shift  kernel based tracking (KBT)  Bhattacharyya coefficient  histograms of oriented gradients
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