A Target Tracking Algorithm Based on Mean Shift and Fast Template Matching

This paper proposes a target tracking algorithm based on mean shift and template matching. The algorithm is divided into three stages:prediction, template matching, target positioning, and template updating. In the prediction stage, combined with the target position obtained from the previous frame...

Full description

Bibliographic Details
Format: Article
Language:zho
Published: The Northwestern Polytechnical University 2018-08-01
Series:Xibei Gongye Daxue Xuebao
Subjects:
Online Access:https://www.jnwpu.org/articles/jnwpu/pdf/2018/04/jnwpu2018364p792.pdf
id doaj-5f6d95d41913435a8e77363a7fd18ceb
record_format Article
spelling doaj-5f6d95d41913435a8e77363a7fd18ceb2021-05-02T17:36:57ZzhoThe Northwestern Polytechnical UniversityXibei Gongye Daxue Xuebao1000-27582609-71252018-08-0136479279910.1051/jnwpu/20183640792jnwpu2018364p792A Target Tracking Algorithm Based on Mean Shift and Fast Template Matching0123PLA 63870 UnitPLA 63870 UnitPLA 63870 UnitPLA 63870 UnitThis paper proposes a target tracking algorithm based on mean shift and template matching. The algorithm is divided into three stages:prediction, template matching, target positioning, and template updating. In the prediction stage, combined with the target position obtained from the previous frame tracking, the target position is predicted using the mean shift method, and the template matching search gate is defined with the predicted position as the center and the corresponding size as the coverage area. At the template matching stage, using fast template matching algorithm, the target template and search gate are quickly matched from coarse to fine, and the matching degree between matching result and target template is calculated. If the matching degree is greater than the given threshold, the fast template matching will be performed and the result will be used as the tracking result of the current frame image. Otherwise, the target position predicted by the mean shift algorithm is used as the tracking results of the current frame image. Finally, the template updating process is controlled by the tracking results of the current frame to update the target template, and the stable tracking of the target is finally completed. At the same time, the algorithm improves the robust of tracking by combining the advantages of color and edge features to the insensitivity of rotation and deformation. The method has fast calculation speed and high accuracy, it can meet real-time requirements.https://www.jnwpu.org/articles/jnwpu/pdf/2018/04/jnwpu2018364p792.pdfalgorithmframe imageimage processingtarget positiontarget trackingmean shifttemplate matchingtarget template
collection DOAJ
language zho
format Article
sources DOAJ
title A Target Tracking Algorithm Based on Mean Shift and Fast Template Matching
spellingShingle A Target Tracking Algorithm Based on Mean Shift and Fast Template Matching
Xibei Gongye Daxue Xuebao
algorithm
frame image
image processing
target position
target tracking
mean shift
template matching
target template
title_short A Target Tracking Algorithm Based on Mean Shift and Fast Template Matching
title_full A Target Tracking Algorithm Based on Mean Shift and Fast Template Matching
title_fullStr A Target Tracking Algorithm Based on Mean Shift and Fast Template Matching
title_full_unstemmed A Target Tracking Algorithm Based on Mean Shift and Fast Template Matching
title_sort target tracking algorithm based on mean shift and fast template matching
publisher The Northwestern Polytechnical University
series Xibei Gongye Daxue Xuebao
issn 1000-2758
2609-7125
publishDate 2018-08-01
description This paper proposes a target tracking algorithm based on mean shift and template matching. The algorithm is divided into three stages:prediction, template matching, target positioning, and template updating. In the prediction stage, combined with the target position obtained from the previous frame tracking, the target position is predicted using the mean shift method, and the template matching search gate is defined with the predicted position as the center and the corresponding size as the coverage area. At the template matching stage, using fast template matching algorithm, the target template and search gate are quickly matched from coarse to fine, and the matching degree between matching result and target template is calculated. If the matching degree is greater than the given threshold, the fast template matching will be performed and the result will be used as the tracking result of the current frame image. Otherwise, the target position predicted by the mean shift algorithm is used as the tracking results of the current frame image. Finally, the template updating process is controlled by the tracking results of the current frame to update the target template, and the stable tracking of the target is finally completed. At the same time, the algorithm improves the robust of tracking by combining the advantages of color and edge features to the insensitivity of rotation and deformation. The method has fast calculation speed and high accuracy, it can meet real-time requirements.
topic algorithm
frame image
image processing
target position
target tracking
mean shift
template matching
target template
url https://www.jnwpu.org/articles/jnwpu/pdf/2018/04/jnwpu2018364p792.pdf
_version_ 1721489378153332736