# Multi-Player Tracking for Multi-View Sports Videos with Improved K-Shortest Path Algorithm  
[PERSON]  
1 College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; [EMAIL_ADDRESS]  
[PERSON]  
1 College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; [EMAIL_ADDRESS]  
[PERSON]  
3 Faculty of Engineering and IT, University of Technology Sydney, Sydney NSW 2007, Australia; [EMAIL_ADDRESS] (Y.Y. ); [EMAIL_ADDRESS] (R.Z. ); [EMAIL_ADDRESS] (Y.P)  
Tong Xing Technology, Guangzhou 510000, China  
Correspondence: [EMAIL_ADDRESS] (W.W.); [EMAIL_ADDRESS] (M.X.) Most existing approaches in multiple-player tracking are based on the tracking-by-detection framework [4; 5; 6; 7]. With this paradigm, players are first detected and then linked into trajectories. In contrast, another common tracking framework that is free of object detector is called detection-free-tracking [8]. Although the detection-free-tracking methods are convenient for real-time tracking, the tracking-by-detection approaches can gain more accurate results, since a batch of frames are jointly considered based on the detection results. The latter approach can get a global optimum, while we have to accept a delay in the output as a trade-off for better accuracy. However, the tracking-by-detection methods usually accrue very few detections. Among the tracking approaches based on tracking-by-detection paradigm, k-shortest path (KSP) optimization is one of the most widely used approaches, proposed by [PERSON] et al. [9]. With this method, the data association step is formulated as a constrained flow optimization and results in a convex problem, which can then be solved using the KSP algorithm. This approach relies on very few parameters and its convexity ensures that a global optimum can be found. What is more, its feasibility of application to sports tracking has been verified [10]. While effective and fast enough, the neglect of the appearance model in the original KSP tracking process easily leads to identity switches when two or more players are intertwined with each other, as shown in Figure 1. To avoid identity switches, the authors have also explored the appearance features in the tracking process [11]. The method formulates the tracking problem as a multi-commodity network flow problem which can be illustrated as a duplication of the graph for each appearance-group. It uses the tracklets as graph nodes instead of individual locations. However, the improved method needs to run the KSP algorithm twice and has a little difficulty implementing it. Being inspired by KSP-based tracking, we further address the problem of identity switches by computing the similarity of players in consecutive frames. We use the similarity to represent the linking weight between two players. To calculate the similarity, appropriate features need to be carefully selected to distinguish the players. Generally, robust tracking algorithms rely on more than one feature to obtain accurate tracking results [12]. In this paper, both the jersey color and jersey number of each player from a multi-view camera are explored for tracking. Generally speaking, working together, these two features are enough to accurately determine a player's identity. However, due to occlusions, the two features mentioned above can only be precisely extracted in limited frames, especially for the jersey number. In this regard, our proposed method is also designed to allow more features to be considered. Overall, our major contribution are as follows. We improve the existing KSP multiple player tracking method by taking the appearance features and similarity measurement into consideration. Although in this paper, only two features are applied for similarity computing, our method can take multiple features into account while assigning different weights on them. Moreover, we carried out extensive experiments to quantify the requirements of appearance features in our proposed approach. Figure 1: An example of the identity switch problem.