# RAMC: A Rotation Adaptive Tracker with Motion Constraint for Satellite Video Single-Object Tracking
## 5 Discussion  
The experimental results demonstrate the effectiveness of the proposed approach in tracking rotating and non-rotating objects in SVs. Compared to those trackers that consider the rotation issue, the proposed method can perceive small angle deviations and provide more accurate orientation and size information. For example, the method of [37] can also detect the orientation of objects by computing the slope of object centroids. However, the slope defined in [37] may be difficult to represent the orientations of objects with obvious angle changes. The method of [40] uses the fixed-angle pool to solve object rotation and outputs the axis-aligned bounding boxes, which ignores accurate semantic information (e.g., real size, orientation of the object). Compared to [37; 40], the proposed approach may be suitable to represent the orientations of objects with tiny and obvious angle changes and yield-rotating bounding boxes due to precise angle estimation effects of the rotation branch. In contrast to those trackers that handle the tracking drift issue, it guarantees precise localization assisted by the hybridization of angle and motion information. The methods of [38; 39] also use optical flow for tracking. However, in [38; 39], the Lucas-Kanade sparse optical flow [45] is regarded as a feature for representation, which may make it difficult to represent pixel-level motion information. In addition, [38; 39] focus  
Figure 11: Tracking examples of the top four trackers. The symbol \(\times\) means tracking failure. The bounding boxes are thinned for better visualization of the tracking effect differences, best viewed by zooming in.  
on considering the magnitudes of the optical flow and ignore the directional information. The proposed approach explores the effects of dense optical flow, which is capable of representing the pixel-level motion information. Furthermore, magnitudes coupled with directions of the optical flow are incorporated to prevent tracking drift and enhance the tracking performance.  
The advantages of the proposed method are attributed to its branches (i.e., rotation and translation branches) in estimating the rotation angle and preventing tracking drift. In the estimation of rotation angle (i.e., rotation branch), this study attempts to reveal the relationship between the rotation and the translation. The rotation phenomenon is decomposed into the translation solution to achieve adaptive rotation estimation. In this way, the angle difference between adjacent frames can be obtained precisely by solving the translation problem. Figure 12 shows the effect of rotation angle estimation with a sample of the original (Figure 12a) and rotated patches (Figure 12b). In Figure 12b, the original ones are rotated to the initial orientation of the first frame by the estimated angle. It can ensure the spatial consistency of the adjacent patches as much as possible, allowing stable response results. Furthermore, the appearance and motion information contained in adjacent frames are synergized to enhance the object representations and deal with the tracking drift issue in the translation branch with motion constraint. To achieve the per-pixel motion constraint, the motion state of the object in the previous frame can be remapped to the current frame using the dense optical flow feature. Moreover, the proposed method can orient the bounding box to a more realistic object state with precise angle, size, and location information, and the results would serve a variety of scenarios (e.g., 2-D pose estimation of moving objects in a video, precise representations of dense objects in remote-sensing images, etc.).  
This paper verifies the significance of angle estimation and motion constraints for SOT in SVs. This work will help exploit the potential of satellite videos for applications such as traffic analysis, disaster response, and military target surveillance.