Video object cosegmentation

Ding-Jie Chen, Hwann-Tzong Chen, Long-Wen Chang

Abstract: We introduce and address the problem of video object cosegmentation, which concerns the task of segmenting the common object in a pair of video sequences. We present a new algorithm that works on super-voxels in videos to solve this task. The algorithm computes i the intra-video relative motion derived from dense optical flow and ii) the inter-video co-features based on Gaussian mixture models. The experimental results show that, by integrating the intra-video and inter-video information, our algorithm is able to obtain better results of segmenting video objects.