Title :
Object contour tracking using graph cuts based active contours
Author :
Xu, Ning ; Ahuja, Narendra
Author_Institution :
Beckman Inst. for Adv. Sci. & Technol., Illinois Univ., Urbana, IL, USA
Abstract :
In this paper, we present an object contour tracking approach using graph cuts based active contours (GCBAC). Our proposed algorithm does not need any a priori global shape model, which makes it useful for tracking objects with deformable shapes and appearances. GCBAC are not sensitive to initial conditions and always converge to the optimal contour within the dilated neighborhood of itself. Given an initial boundary near the object in the first frame, GCBAC can iteratively converge to an optimal object boundary. In each frame thereafter, the resulting contour in the previous frame is taken as initialization and the algorithm consists of two steps. In the first step, GCBAC are applied to the difference between this frame and its previous one. The resulting contour is taken as initialization of the second step, which applies GCBAC to current frame directly. To evaluate the tracking performance, we apply the algorithm to several real world video sequences. Experimental results are provided.
Keywords :
graph theory; image segmentation; image sequences; iterative methods; tracking; video signal processing; deformable shapes; dilated neighborhood; graph cuts based active contours; iterative object segmentation; object contour tracking; optimal object boundary; s-t minimum cut algorithm; video sequences; Active contours; Cameras; Deformable models; Iterative algorithms; Object segmentation; Robustness; Shape; Video sequences; Video surveillance; Videoconference;
Conference_Titel :
Image Processing. 2002. Proceedings. 2002 International Conference on
Print_ISBN :
0-7803-7622-6
DOI :
10.1109/ICIP.2002.1038959