Background Removal of Object Movies by Learning Shape Priors

The object movie technique has been successfully used to capture and display 3D objects for manifold applications. Before integrating the object movies into the chosen scene source (e.g., a panorama), the challenge is how to efficiently and effectively separate the background from the interesting object. The problem will be referred to as object movie segmentation. This paper proposes a new object movie segmentation method that incorporates the shape prior into the segmentation algorithm. The shape prior introduced into every image of the object movie is learned from the 3D model reconstructed by the volumetric graph cuts algorithm. Here, the constraint derived from the discrete medial axis is used to improve the reconstruction algorithm. Our segmentation method requires only a small amount of user intervention, which is to select a subset of acceptable segmentations of the object movie after the initial segmentation process. Compared to other techniques, our method provides not only the better segmentation result but also the better 3D reconstruction result. Impressive improvement in object movie segmentation is demonstrated.