# An Improved Kernelized Correlation Filter Algorithm for Underwater Target Tracking
## 4 Experimental Results and Analysis
Figure 6.0 Tracking results for the target with varying scales: (**a**) The tracking results at the 1087 th frame; (**b**) the tracking results at the 1093 rd frame; (**c**) the tracking results at the 1112 th frame; (**d**) the tracking results at the 1132 nd frame. Figure 6.1 Center position error curves (1082 nd frame to 1152 nd frame). From Figure 8, it can be concluded that each algorithm in the first 1112 frames can track the position of the underwater target relatively correctly, while at the 1112 nd frame, the mean-shift begins to deviate during the tracking process, and then at the 1132 nd frame, the mean-shift and MOSSE algorithms all show tracking errors. In order to describe the underwater target tracking results more clearly, as can be further seen in Figure 9, the mean-shift and MOSSE algorithms have serious tracking errors in the tracking process. The KCF and CSK were compared with the proposed IKCF. The results showed that the proposed IKCF has a high tracking accuracy and can effectively track underwater tracking accuracy. Figure 6.2 Overlap precision curves (1082 nd frame to 1152 nd frame). Figure 6.3 Location error precision curves (1082 nd frame to 1152 nd frame). targets. Figure 10 shows that even if the maximum center error is 30 pixels, the ratios of the image frame number to the total frame number are only 48% and 65% in the tracking result of the mean-shift and MOSSE, respectively, for the same central position error value. The ratio of the image frame to the total frame of the proposed IKCF is higher than that of the KCF and CSK, and the central position error value of all the image frame numbers is within 12 pixels, while the KCF and CSK are within 19 pixels and 18 pixels, respectively. Therefore, the tracking accuracy of the proposed IKCF is higher when the target scale is changed in the image sequences. It is further seen from Figure 11 that the proposed IKCF is much better than the KCF, CSK, MOSSE, and mean-shift. Therefore, when the target scale changes, the proposed IKCF has stronger adaptability than other algorithms and can maintain a high tracking accuracy. Figure 12 shows the tracking results when the target disappears and appears again when frame is 359 th, 365 th, 393 rd, and 403 rd, respectively. Center position error curves (354 th frame to 434 th frame) of the occluded target are shown in Figure 6.4 Location error precision curves (354 th frame to 434 th frame) of the occluded target are shown in Figure 6.5 Overlap precision curves (354 th frame to 434 th frame) of the target that disappears and appears again are shown in Figure 6.6  
From the tracking results in Figure 12, when the target disappears and appears again at the 365 th frame, all the other algorithms could track the position of the underwater target correctly except CSK, and after the 365 th frame, the tracking deviation of KCF, MOSSE, and mean-shift gradually increased. Until the 393 rd frame, the MOSSE has a tracking error, at the 403 rd frame, the KCF and mean-shift also have tracking errors; only the proposed IKCF still maintains the correct tracking trajectory and has a high tracking accuracy. As can be further seen in Figure 13, the central position error of the KCF,  
Figure 6.7 Tracking results for the target that disappears and appears again: (**a**) The tracking results at the 359 th frame; (**b**) the tracking results at the 365 th frame; (**c**) the tracking results at the 393 th frame; (**d**) the tracking results at the 403 rd frame. CSK, MOSSE, and mean-shift increases as the target disappears, whereas the proposed IKCF still has a high tracking accuracy and stability, and has strong robustness. From Figures 14 and 15, regardless of the location error and the overlap threshold, the ratio of the image frame number to the total frame number cannot reach 100% of the KCF, CSK, MOSSE, and mean-shift algorithms. The proposed IKCF has a higher tracking accuracy compared with other algorithms and has a certain adaptability and effectiveness.