Object tracking approach based on mean shift algorithm

被引：1

作者：

Zhang, Xiaojing ^{[1
]}

Yue, Yajie ^{[2
]}

Sha, Chenming ^{[2
]}

机构：

[1] Department of Software Engineering, School of Software, Harbin University of Science and Technology, Harbin

[2] School of Software, Harbin University of Science and Technology, Harbin

来源：

Journal of Multimedia | 2013年 / 8卷 / 03期

基金：

美国国家科学基金会;

关键词：

Computer vision; Mean shift; No parameters estimation; Object tracking;

D O I：

10.4304/jmm.8.3.220-225

中图分类号：

学科分类号：

摘要：

Object tracking has always been a hotspot in the field of computer vision, which has a range of applications in real world. The object tracking is a critical task in many vision applications. The main steps in video analysis are: detection of interesting moving objects and tracking of such objects from frame to frame. Most of tracking algorithms use pre-defined methods to process. In this paper, we introduce the Mean shift tracking algorithm, which is a kind of important no parameters estimation method, then we evaluate the tracking performance of Mean shift algorithm on different video sequences. Experimental results show that the Mean shift tracker is effective and robust tracking method. © 2013 ACADEMY PUBLISHER.

引用

页码：220 / 225

页数：5

共 26 条

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