# Multi-Player Tracking for Multi-View Sports Videos with Improved K-Shortest Path Algorithm
## 4 Experiments
### Results
#### 4.3.5 Discussion  
In order to test the performance of our proposed method, we did three groups of experiments. The first two experiments were working toward the public 1500-frames APIDIS dataset while the third one was implemented on our own STU dataset (10 periods of long sequences). Based on these experiments, we can have the following discussions:  
1. Compared with the original KSP tracking which ignores appearance features, the identity switches problem in multiple-player tracking can be obviously improved by considering appearance cues (see Figures 9 and 10). It also can be seen that the combination of two features is better for KSP-AF tracking than the case when only color feature is included. Although the MOTA and GMOTA scores can not be largely improved or even drop at the beginning when very few features are available, they can surpass the original KSP method when more than 60% jersey color and 40% jersey number are extracted. Ideally, both of the MOTA and GMOTA scores of our KSP-AF can reach 1 if we can extract jersey color and jersey number for each player in all frames, as shown in Figure 10 (100%Color+100%Num).
2. It also can be seen from Table 2 that KSP-based methods are better adaptable to the APIDIS dataset than other related methods (e.g., MOT-CE [59] (MOTA = 0.799) and MOT-SA [58] (MOTA = 0.855)). Among them, KSP-AF (70%Color+50%Num) can gain an obviously large improvement compared to original KSP. When it reaches to 90%Color+50%Num, it can even defeat the state-of-the-art method (T-MCNF [11]).
3. Finally, we use longer sequences (STU dataset collected by our own) to further verify the effectiveness of our proposed KSP-AF. The STU dataset contains 10 periods of sequences  
Figure 12: Identity switches can be successfully avoided based on our KSP-AF tracking method in APIDIS and STU datasets. (**a–d**) Part of the tracking effects in APIDIS dataset. Two players annotated with thicker line (yellow player with number 4 and blue one with number 7) come close to each other from frame 350 to 379 and then separate apart at frame 380. After that, they can still remain their own identities at frame 393, which is impossible when the original KSP approach is applied; (**e–h**) the same effectiveness of our KSP-AF method when it is applied in STU dataset.  
varying from 600 to 4400 frames, and more occlusions, but higher image resolution compared with the public APIDIS dataset. The original KSP method and our KSP-AF with 70% color and 50% number are respectively applied in these sequence. Experimental results show that our method (70% color + 50% number) can maintain the player identity more steadily than the original KSP method.  
To sum up, our proposed KSP-AF method can avoid more identity switches if given more features. And the basic requirements of extracting 70% color and 50% number information are not very challenging considering that many advanced feature extraction methods are emerging [50; 51; 52]. In addition, our method is also flexible for taking more features into consideration. More features would make our method more robust to occlusions and miss-detections.