基于极线约束SIFT特征和粒子滤波的目标跟踪算法  

A Tracking Algorithm Based on SIFT Feature and Particle Filter with Epipolar Constraint

作　　者：刘士荣[1,2] 吴楚[1,3] 张波涛[1,2] 章海兵[1,2] 

机构地区：[1]杭州电子科技大学电气自动化研究所,杭州310018 [2]检测仪表与自动化系统集成技术教育部工程研究中心,杭州310018 [3]华为技术有限公司杭州研究所,杭州310007

出　　处：《上海交通大学学报》2014年第7期1026-1032,1038,共8页Journal of Shanghai Jiaotong University

基　　金：国家自然科学基金资助项目(61175093)

摘　　要：针对采用颜色或边缘等特征的目标跟踪算法所存在的跟踪效果不稳定的问题,提出了一种基于极线约束尺度不变特征变换(SIFT)和粒子滤波的目标跟踪方法.该方法采用SIFT特征向量构建目标模型,引入极线约束改善目标匹配精度,采用粒子滤波算法获得SIFT特征向量的候选目标模型,利用似然函数计算目标模型与候选目标模型间的相似性.实验结果表明,该方法可解决目标与背景颜色相似时的跟踪失败问题,且对目标外形与位姿发生变化具有较好的适应能力.To deal with the instability in the target tracking method based on color or edge features, a tracking algorithm based on SIFT features and particle filter with epipolar constraint was proposed in this paper. In this method, the target template was established using the vectors of the SIFT feature points, and the epiploar constraint was used to improve the target matching accuracy. A particle filter method was employed to establish the candidate template of SIFT feature vectors, and a likelihood function was used to calculate the similarity between the candidate template and the target template. Experimental results show that the proposed algorithm can track the target when the color of target is similar to one of the back- ground, and it still works well when the posture or shape of the target changes.

关 键 词：目标跟踪 极线约束 尺度不变特征变换 粒子滤波 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]