Part propagation for local part segmentation

Segment propagation transfers object priors among images, which is an important prior generation manner in image segmentation. The existing propagation methods focus on object foreground propagation, while the detailed part propagation is deficiency, which is caused by the challenges that not only the multiple part regions, but also their relationships need to be transferred. In this paper, a part propagation method is proposed. Two level propagations such as object level propagation, and part level propagation are successively used for the part propagation. The object level propagation is to transfer global shape information among images, which is formulated as graph matching based edge fragments matching problem, with dynamic programming solution. The part level propagation is to transfer the more detailed part labels, which is formulated as pixel level structure matching problem, and is efficiently solved by traditional dense pixel matching methods. The proposed method is verified on 15 challenging classes selected from PASCAL 2010 dataset, Bird dataset and Cat-Dog dataset. The experimental results demonstrate the effectiveness of the proposed method.