|M.Sc Student||Boudoukh Guy|
|Subject||Bitmap Tracking under Very General Conditions|
|Department||Department of Electrical Engineering||Supervisor||Professor Ehud Rivlin|
|Full Thesis text|
In this research we propose a new method that addresses the problem of visually tracking the bitmap (silhouette) of an object in a video under very general conditions. We assume a general target, possibly non rigid, with no prior information except initialization. The target, as well as the background, may change its appearance over time and the camera may move arbitrarily. The proposed algorithm fuses different visual cues by means of a conditional random field probabilistic model. The target's bitmap is estimated every frame by incorporating temporal color similarity, spatial color continuity and spatial motion continuity into an energy function that is minimized via min-cut. The spatial motion continuity is incorporated in the energy function in multiple image resolutions by a novel multi-scale energy term. Compared to other methods that calculate optical flow for the whole image, the algorithm complexity is reduced when the optical flow calculation is done only at specific feature points. Experimental results show that our method outperforms other algorithms that address the problem of tracking under general conditions. Experiments on a variety of video clips demonstrate the robustness and effectiveness of our method to track an object under very general conditions.