Video Object Segmentation and Tracking for Content-Based Video Coding

In this paper, a novel technique for the segmentation and tracking of moving objects is proposed. The proposed scheme extracts moving objects based on both motion and spatial information. Initially, an intra-frame segmentation is performed using a morphological segmentation algorithm. After this, the video object areas are merged according to their motions based on a new criterion. When different moving objects are extracted, their affine motion parameters are estimated. In the tracking stage, different objects are projected to the next frame according to their affine motion parameters. The projected regions may be overlapped and/or uncovered, creating uncertain areas. By using a two-scan Zig-Zag algorithm, the pixels in the uncertain areas can be absorbed into one of the neighboring objects. Experimental results have demonstrated successful object segmentation and tracking in both moving and stationary background cases.