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A Novel Changing Athlete Body Real-Time Visual Tracking Algorithm Based on Distractor-Aware SiamRPN and HOG-SVM

Science and Technology on Underwater Vehicle Laboratory, Harbin Engineering University, Harbin 150001, China
Department of Computer Science, The University of Hong Kong, Hong Kong 999077, China
Author to whom correspondence should be addressed.
Electronics 2020, 9(2), 378;
Received: 22 January 2020 / Revised: 20 February 2020 / Accepted: 21 February 2020 / Published: 24 February 2020
Athlete detection in sports videos is a challenging task due to the dynamic and cluttered background. Distractor-aware SiamRPN (DaSiamRPN) has a simple network structure and can be utilized to perform long-term tracking of large data sets. However, similarly to the Siamese network, the tracking results heavily rely on the given position in the initial frame. Hence, there is a lack of solutions for some complex tracking scenarios, such as running and changing of bodies of athletes, especially in the stage from squatting to standing to running. The Haar feature-based cascade classifier is involved to catch the key frame, representing the video frame of the most dramatic changes of the athletes. DaSiamRPN is implemented as the tracking method. In each frame after the key frame, a detection window is given based on the bounding box generated by the DaSiamRPN tracker. In the new detection window, a fusion method (HOG-SVM) combining features of Histograms of Oriented Gradients (HOG) and a linear Support-Vector Machine (SVM) is proposed for detecting the athlete, and the tracking results are updated in real-time by fusing the tracking results of DaSiamRPN and HOG-SVM. Our proposed method has reached a stable and accurate tracking effect in testing on men’s 100 m video sequences and has realized real-time operation. View Full-Text
Keywords: visual tracking; real-time; Siamese tracker; HOG-SVM visual tracking; real-time; Siamese tracker; HOG-SVM
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Sheng, M.; Wang, W.; Qin, H.; Wan, L.; Li, J.; Wan, W. A Novel Changing Athlete Body Real-Time Visual Tracking Algorithm Based on Distractor-Aware SiamRPN and HOG-SVM. Electronics 2020, 9, 378.

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