Tracking of moving athlete from video sequences using fower pollination algorithm

• Main Authors: Ong, Pauline, Chong, Tang Keat, Ong, Kok Meng, Low, Ee Soong
• Format: Article
• Language: English
• Published: Springer Link 2022
• Subjects: QA273-280 Probabilities. Mathematical statistics
• Online Access: http://eprints.uthm.edu.my/6919/1/J14030_e716ed0e1b012924f55a5b254d93fb34.pdf; http://eprints.uthm.edu.my/6919/; https://doi.org/10.1007/s00371-021-02060-2
• Institution: Universiti Tun Hussein Onn Malaysia

Performance analysis, as related to sport, is a process underpinned by a systematic analysis of information, to accelerate the performance of athletes through crafted focused practice session based on the obtained analysis. Quantifcation of athlete performance profle using sports video has thus been put forward, where the athlete tracking in such video-based analysis is one of the critical elements for the success of an object tracking system. In this study, for the frst time the fower pollination algorithm (FPA) is utilised to track the motion of the moving athlete from the sports video. Initially, a search window with the attributes of centroid coordinates of the moving athlete, width and length of the search window is used to represent the current position of the athlete. Subsequently, the hue, saturation and value (HSV) histogram of the region within the search window is evaluated. In the consecutive frame, several potential positions of the athlete are identifed, and the Bhattacharyya distance between the HSV histogram of the athlete in the previous frame and the potential position in the current frame is calculated. Since the FPA attempts to maximise the similarity of both histograms, intuitively, the current position of the moving athlete should be only slightly diferent than his previous position. The comparative analysis shows that the FPA is comparable with other competing algorithms in terms of detection rate, tracking accuracy and processing time.