Target Tracking Algorithm in Football Match Video Based on Deep Learning
After the introduction of online learning mechanism, the traditional target tracking algorithm in football game video based on TLD has good tracking ability, but it will lose the target when the target is seriously obscured. Therefore, a soccer game video target tracking algorithm based on deep lear...
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2022-01-01
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| Series: | Discrete Dynamics in Nature and Society |
| Online Access: | http://dx.doi.org/10.1155/2022/2769606 |
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| _version_ | 1832565763863478272 |
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| author | Wei Zhao |
| author_facet | Wei Zhao |
| author_sort | Wei Zhao |
| collection | DOAJ |
| description | After the introduction of online learning mechanism, the traditional target tracking algorithm in football game video based on TLD has good tracking ability, but it will lose the target when the target is seriously obscured. Therefore, a soccer game video target tracking algorithm based on deep learning is proposed. The target detection algorithm of GoogLeNet-LSTM is used for faltung to obtain the feature mapping array. After processing, a high reliability candidate box for training and matching is obtained, and the feature maps of the detection results are collected to obtain the depth features required for tracking. Scale space discriminant tracking algorithm and Markov Monte Carlo algorithm are used to track single target or multi-target, respectively. Experimental results show that the average frame rate of the algorithm is maintained above 35 Hz, and the tracking time is about 12.5 s. The average center position deviation index is 39, the average coverage index is 40, and the resource utilization is low. The algorithm can track the target in the football game video well. |
| format | Article |
| id | doaj-art-1490dbd040ff4cf1ad4079789eb1b54c |
| institution | Kabale University |
| issn | 1607-887X |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Discrete Dynamics in Nature and Society |
| spelling | doaj-art-1490dbd040ff4cf1ad4079789eb1b54c2025-02-03T01:06:36ZengWileyDiscrete Dynamics in Nature and Society1607-887X2022-01-01202210.1155/2022/2769606Target Tracking Algorithm in Football Match Video Based on Deep LearningWei Zhao0School of Physical EducationAfter the introduction of online learning mechanism, the traditional target tracking algorithm in football game video based on TLD has good tracking ability, but it will lose the target when the target is seriously obscured. Therefore, a soccer game video target tracking algorithm based on deep learning is proposed. The target detection algorithm of GoogLeNet-LSTM is used for faltung to obtain the feature mapping array. After processing, a high reliability candidate box for training and matching is obtained, and the feature maps of the detection results are collected to obtain the depth features required for tracking. Scale space discriminant tracking algorithm and Markov Monte Carlo algorithm are used to track single target or multi-target, respectively. Experimental results show that the average frame rate of the algorithm is maintained above 35 Hz, and the tracking time is about 12.5 s. The average center position deviation index is 39, the average coverage index is 40, and the resource utilization is low. The algorithm can track the target in the football game video well.http://dx.doi.org/10.1155/2022/2769606 |
| spellingShingle | Wei Zhao Target Tracking Algorithm in Football Match Video Based on Deep Learning Discrete Dynamics in Nature and Society |
| title | Target Tracking Algorithm in Football Match Video Based on Deep Learning |
| title_full | Target Tracking Algorithm in Football Match Video Based on Deep Learning |
| title_fullStr | Target Tracking Algorithm in Football Match Video Based on Deep Learning |
| title_full_unstemmed | Target Tracking Algorithm in Football Match Video Based on Deep Learning |
| title_short | Target Tracking Algorithm in Football Match Video Based on Deep Learning |
| title_sort | target tracking algorithm in football match video based on deep learning |
| url | http://dx.doi.org/10.1155/2022/2769606 |
| work_keys_str_mv | AT weizhao targettrackingalgorithminfootballmatchvideobasedondeeplearning |