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...
| Format: | Article |
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| Language: | zho |
| Published: |
EDP Sciences
2018-08-01
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| Series: | Xibei Gongye Daxue Xuebao |
| Subjects: | |
| Online Access: | https://www.jnwpu.org/articles/jnwpu/pdf/2018/04/jnwpu2018364p792.pdf |
| _version_ | 1797669085817864192 |
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| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-11T20:39:17Z |
| format | Article |
| id | doaj.art-5f6d95d41913435a8e77363a7fd18ceb |
| institution | Directory Open Access Journal |
| issn | 1000-2758 2609-7125 |
| language | zho |
| last_indexed | 2024-03-11T20:39:17Z |
| publishDate | 2018-08-01 |
| publisher | EDP Sciences |
| record_format | Article |
| series | Xibei Gongye Daxue Xuebao |
| spelling | doaj.art-5f6d95d41913435a8e77363a7fd18ceb2023-10-02T04:08:50ZzhoEDP SciencesXibei 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 |
| 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 | 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_short | 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 |
| 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 |