Title :
A predictive contour inertia snake model for general video tracking
Author :
Jiang, Hao ; Drew, Mark S.
Author_Institution :
Sch. of Comput. Sci., Simon Fraser Univ., Vancouver, BC, Canada
Abstract :
We present a modified snake model for the problem of general video object tracking. We introduce a new external force into the snake equation based on the predictive contour such that the active contour is attracted to a shape similar to the one in the previous video frame. New methods of contour prediction and contour smoothing are presented. The proposed methods can deal with the problem of an object´s stopping movement temporarily and can also avoid the problem of the snake tracking into the object interior. Global affine motion estimation is applied to eliminate the effect of camera motion and hence the method can be applied in a general video environment. Experimental results show that the proposed method exhibits increased robustness over a traditional snake algorithm and works well for general video object tracking.
Keywords :
motion estimation; optical tracking; prediction theory; smoothing methods; video signal processing; affine motion estimation; camera motion; contour inertia; contour smoothing; object tracking; predictive contour; snake model; video tracking; Active contours; Cameras; Deformable models; Equations; Kalman filters; Motion estimation; Predictive models; Robustness; Shape; Tracking;
Conference_Titel :
Image Processing. 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7622-6
DOI :
10.1109/ICIP.2002.1038993