## 4 Experiments
### Performance Analysis
#### 4.4.2 Performance for Dog Tracking  
Dog tracking is an experiment with a single dog after detection. The DeepSORT, DeepSORT_retrained, and DeepDogTrack models (Models 1, 2, and 3, respectively) were used in the dog-tracking experiment. The experimental results for the IMG_0043_5 data-set \begin{table}
\begin{tabular}{c c c c c c} \hline Datasets & Image Number & Dog Number & Detection Rate & Precision & Recall & mIOU \\ \hline TestSet 1 & 8351 & 8371 & 97.62\% & 93.49\% & 83.72\% & 80.27\% \\ TestSet 2 & 20580 & 22126 & 98.39\% & 88.87\% & 85.67\% & 80.48\% \\ \hline \end{tabular}
\end{table} 
Table 11: Results of dog detection experiments. Figure 14: Reasons for detection errors in TestSet2 data-set experiment. (**a**) Obscured facial features; (**b**) Special breed of dog; (**c**) Obscured or cropped body; (**d**) Incomplete dog region. Figure 13: Reason for detection errors in TestSet1 data-set experiment. (**a**) Obscured facial features; (**b**) Special breed of dog; (**c**) Obscured or cropped body. are presented in Table 12. The MOTA values of Model 1 and of Models 2 and 3 were 81.1% (false negatives [FNs]: 33, false positives [FPs]: 9) and 83.88% (FNs: 33, FPs: 1), respectively. The MOTA values of Models 2 and 3 were higher than that of Model 1 because the prediction regions of these two models use YOLOv3 detection. Two reasons for tracking failure were identified: the obstruction of the dog's body in many regions (Figure 15) and the dog's back being turned to the camera (Figure 16). The YOLOv3 model was not trained using images of dogs' backs, which differ considerably from those taken from front or side views; consequently, the tracked region in such images is incorrect. If the Kalman prediction region is used as the dog region, the IOU between the ground truth and predicted region is less than 50%. This is illustrated in Figure 17, in which blue and red boxes are the predicted and ground truth regions, respectively; the IOUs in images 47 and 48 are 0.46 and 0.43, respectively. The IMG_0014 data-set used in the dog-tracking experiment contained sub-images of four different dogs (ID 1-4). The experimental results for the data-set are presented in Table 14. In the experiments involving ID 1, each of the three models achieved a MOTA value of 98.32%; the tracked regions were all correct. In those involving ID 2, Models 2 and 3 achieved a MOTA value of 69.26%, which was higher than that achieved using Model 1, but considerably lower than that achieved in the experiments involving other dogs. This is partially because several dogs were tracked as the same dog. In the experiments involving ID 3, Models 2 and 3 achieved a MOTA value of 87.50%, which was far higher than that achieved using Model 1 and second only to that obtained in the experiments involving ID 1. In the experiment involving ID 4, Models 1 and 3 achieved a MOTA value of 82.50%, and the tracked regions in both models were all correct; however, Model 2 achieved a lower MOTA value (81.25%) because several dogs were tracked as the same dog. The numbers of FNs obtained for IDs 2 and 4 were higher than those obtained for IDs 1 and 3. Examples of images resulting in FNs for IDs 2 and 4 are presented in Figures 19 and 20, respectively. ID 2 corresponds to a black dog far from the camera. In images 266 to 274, the dog is obscured, leading to tracking failure. ID 4 corresponds to a white dog that entered the frame during recording. In images 302 and 303, the dog has not yet completely entered the frame, resulting in tracking failure. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Methods** & **Number of Dogs** & **Total Image Number** & **Number of Dogs Tracked** & **FN** & **FF** & **IDSW** & **MOTA** \\ \hline Model 1 & & & 119 & 8 & 2 & 0 & 92.24\% \\ Model 2 & 1 & 180 & 120 & 8 & 1 & 0 & 93.02\% \\ Model 3 & & 120 & 8 & 1 & 0 & 93.02\% \\ \hline \end{tabular}
\end{table} 
Table 13: Results of dog-tracking experiments conducted using IMG_0041_1 data-set. Figure 18: Dogs not tracked in images 164 and 165.