## 4 Experiments
### Qualitative Comparisons  
In this subsection, the proposed CFSA tracker is qualitatively compared with 9 state-of-the-art trackers and tracking results of 7 representative image sequences with all 11 attributes are shown in Figure 8. In the following, we compare the tracking results of these trackers when the target object undergoes rotation, deformation, scale variation and occlusion. (1) Rotation: Rotation is a type of challenging appearance changes that occurs frequently, mainly divided into in-plane rotation and out-of-plane rotation. Figure 8a,b show the tracking results on two challenging sequences to evaluate whether CFSA tracker is able to deal with rotation. In the _Deer_ sequence, SCM and ASLA start drifting at frame 10 due to the in-plane rotation of the target. At frame 26, 30 and 33, all trackers except CFSA, CSK, SAMF and Struck drift to the background. Due to the fast motion and continuous rotation of the target, all trackers apart from CFSA are failed to track the target in the _Skiing_ sequence (e.g., #0021, #0051 and #0058). Moreover, as shown in Figure 8e, the target liquor bottle is fast moving with out-of-plane rotation at frame 1414, only CFSA could accurately track the target. (2) Deformation: Figure 8c,d are used to qualitatively assess each tracker in the aspect of handling deformation. The tracking results as presented in the _Basketball_ sequence show that CFSA, CSK and SAMF could track the target object on most of the entire sequence, while other trackers fail to track the target or drift away from the target object at frame 96, 287 and 701. The sequence of _Tiger2_ contains challenging factors such as fast motion, partially occlusion, in-plane rotation, out-of-plane rotation and deformation. For example, the tiger opens his mouth at frame 125 and is partially occluded at frame 267, resulting in most of the trackers cannot accurately locate the target and estimate its target scale, while the KCF and CFSA trackers could stick to the target in the whole sequence. (3) Scale variation: In order to prove the effectiveness of the CFSA tracker in the case of significant scale variation, Figure 8e shows the tracking results of _CarScale_ sequence. The car is far away and its scale changes little at frame 42, all trackers could stick to the car. As the car approaches, its scale changes rapidly, most trackers can successfully track the car, but the bounding box does not change with the scale of the car at frame 148 and 220. TLD, DSST, and CFSA perform better than other trackers at frame 220 and 238. Compared with CFSA tracker, the DSST tracker is faster. This is mainly due to too much time (about 26 ms per frame on average) is spent on the generation of high-quality proposals and the detection of the target car's position, while these two parts are critical for estimating the position and scale of the target object. After getting the accurate position of the target car, its scale can be estimated in 6 ms. However, CFSA and all other state-of-the-art trackers cannot accurately estimate the scale of the target object when the scale changes quickly, which should be noted in future studies. Furthermore, in Figure 8f, the target bottle is rotated and its scale changed at frame 1414. Only CFSA could accurately track the target bottle and estimate its size. Benefit from the water flow driven MBD algorithm and scale estimation method, the CFSA tracker is able to track the target and estimate its scale more accurate. (4) Occlusion: The target object may be partially or heavily occluded as shown in Figure 8f,g. For the _Liquor_ sequence, all trackers can successfully track the target bottle at frame 10, and then all trackers except KCF and CFSA have already lost the target when the target bottle is occluded by another green bottle at frame 732 and reappears at frame 782. In the sequence of _Jogging_-2, the running woman is occluded by a traffic signal pole at frame 48 and 61 and reappears at frame 72.