Simultaneous pose motion recovery and video object cutout

In this paper, we present a novel system for simultaneously performing segmentation and 2D pose motion recovery for the articulated object in a video sequence. The system first preprocesses pixels into superpixels to reduce the number of nodes which largely affects the computational complexity of later optimizations. By starting from true pose estimation obtained with user assistants on each key frame, a parallel pose tracking procedure, whose energy function considers boundary, appearance and pose prior information as well, is conducted forward and backward on in-between frames. With different searching strategies, multiple pose candidates are inferred to help recover missed true poses. Finally, by solving the cost function of the pose motion recovery, which exploits the temporal coherence of object movement, the pose motion and the video object are produced at the mean time. As a parameterized tree-based articulated model drawn by the user is applied to denote the pose, our method is generic and can be used for any articulated object.