The Research on Multi-angle Face Tracking Based on Multi-feature Fusion and KCF
Authors: 
Mengnan Hu, Yijie WangAuthors Info & Claims
Mengnan Hu, Yijie WangAuthors Info & ClaimsAbstract
A method for multi-angle face tracking based on multi-feature fusion and KCF algorithm is proposed in this paper. Firstly, Haar-like, MB-LBP and HOG features are combined to detect the face region, which is regarded as the initial tracking search window. Secondly, training, updating and adjusting search window size. Finally, if the tracking target is lost, face region is relocated through the multi-angle detection algorithm which can realize real-time and automatic tracking. To verify the effect, our method is compared with the traditional KCF algorithm. The results of simulation experiments show that, the method proposed can track multi-angle face of video sequences from video database in real time, the center distance error is 8.49, the overlap rate is 58.78%, and the tracking time is 55.41ms.
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October 2019
522 pages
ISBN:9781450376570
DOI:10.1145/3373509
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- Hebei University of Technology
- Beijing University of Technology
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Association for Computing Machinery
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Published: 25 March 2020
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ICCPR '19
ICCPR '19: 2019 8th International Conference on Computing and Pattern Recognition
October 23 - 25, 2019
Beijing, China
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