Object tracking and matting for a class of dynamic image-based representations

Abstract

Image-based rendering (IBR) is an emerging technology for photo-realistic rendering of scenes from a collection of densely sampled images and videos. Recently, an object-based approach for a class of dynamic image-based representations called plenoptic videos was proposed. This paper proposes an automatic object tracking approach using the level-set method. Our tracking method, which utilizes both local and global features of the image sequences instead of global features exploited in previous approach, can achieve better tracking results for objects, especially with non-uniform energy distribution. Due to possible segmentation errors around object boundaries, natural matting with Bayesian approach is also incorporated into our system. Furthermore, a MPEG-4 like object-based algorithm is developed for compressing the plenoptic videos, which consist of the alpha maps, depth maps and textures of the segmented image-based objects from different video plenoptic streams. Experimental results show that satisfactory renderings can be obtained by the proposed approaches.