Tracking Socer Player Based on Deepsort Algorithm with YOLOV8 FrameWork

Abstract—Tracking is a set procedure that entails assigninganidentificationtoacertainobjectandsubsequentlycon-sistently recognizing that object without altering the assignedidentification over a sequence of frame images and associatingitaccordingly.Whenperformingresearchonobjecttracking,especially in sports where the object of interest is a human, aresilient technology is necessary to facilitate the tracking process.When the state-of-the-art object detection approach, YOLOV8,is combined with the DeepSORT algorithm, it is anticipated toproduce highly accurate and exact outcomes in the trackingand detection of objects. Challenges in multi-object trackinginclude robustness, oculusion, and identity shifts. In our research,we take advantage of a fusion of YOLOV8 and DeepSORTalgorithmstoachieveahighlyreliableandprecisetrackingsolution. The implementation of the Kalman filter-based motionprediction in DeepSORT allows for the achievement of smoothtrajectories, whereas the YOLOV8 deep neural network usedassists in precisely recognizing the appearance of objects on thefield. The result of our experiment shown the tracking we get is38% HOTA, 47% DetA, 31% AssA, 68% DetPre, 35% AssRE,61% AssPr amd 79% LOcA.Index Terms—Tracking, DeepSORT, YOLO, MOT, Socce