Visual object tracking is one of the most active research topic in the field of computer vision, and it plays a significant role in applications such as unmanned aerial vehicle surveillance, robotics and driver assistance. Accurate online visual tracking faces great challenges due to the uncertainty of the motion between the camera and the target, the previously unknown parameters in the camera model, and the clutters in the circumstances for video capturing. During the capturing, the field-of-view (FOV) of the camera may be changed frequently to obtain different resolutions of the target. In these situations, the scale change of the target occurs a lot in the captured image sequences, along with the appearance change and the abrupt motion of the target. By now, researchers have not yet systematically studied the online visual tracking in situations where the FOV of the camera changes, resulting in unsatisfactory accuracy, robustness and efficiency of the tracking algorithms when dealing with these situations in real applications. In this dissertation, we lucubrate object tracking algorithms in dealing with two situations of FOV change of the camera. The main contributions are listed as follows: (1) A scale adaptive tracking method using Mean Shift and efficient feature matching is proposed to deal with the tracking problem in the situation where the FOV of the camera gradually changes. In this situation, the scale and the location of the target gradually change between consecutive frames. The scale estimation module calculates the affine model by matching local features extracted in the target between consecutive frames to obtain the scaling factors. This module is modified and integrated with the Mean Shift tracker to give accurate results for the target scale in tracking. The proposed method utilizes FAST corners and LHOG description for the good efficiency in feature matching. Experimental results show that the tracker locates the target accurately and efficiently, and gives satisfying results for the scale of the target. (2) A scale adaptive Mean Shift tracker based on invariant foreground occupation ratio is proposed to deal with the tracking problem when the FOV of the camera gradually changes. The thesis of foreground occupation ratio (FOR) of the image is proposed, and its four simple properties are summarized. With its invariance between two frames, the coarse scaling factor of the foreground is obtained, and it is modified and adjusted prope...
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