A semiautomatic multiview depth estimation method In this paper, we propose a semiautomatic depth estimation algorithm whereby the user defines object depth boundaries and disparity initialization. Automatic depth estimation methods generally have difficulty to obtain good depth results around object edges and in areas with low texture. The goal of our method is to improve the depth in these areas and reduce view synthesis artifacts in Depth Image Based Rendering. Good view synthesis quality is very important in applications such as 3DTV and Freeviewpoint Television (FTV). In our proposed method, initial disparity values for smooth areas can be input through a socalled manual disparity map, and depth boundaries are defined by a manually created edge map which can be supplied for one or multiple frames. For evaluation we used MPEG multiview videos and we demonstrate our algorithm can significantly improve the depth maps and reduce view synthesis artifacts.

An Improved Depth Map Estimation Algorithm For View Synthesis and Multiview Video Coding In this paper, an improved algorithm to generate a smooth and accurate depth map for view synthesis and multiview video coding is developed. For each block in the target view, the algorithm first uses epipolar geometry to find its matched block in the reference view, from which an initial depth is obtained using the triangulation method and depth projection. 3D warping is then applied to refine the depth. In addition, a structural similarity and maximum likelihoodbased approach is developed to fuse the depth estimations from multiple references. Finally, the depth map is smoothed via segmentation and plane fitting. Compared to existing 3D warpingbased depth estimation, the proposed algorithm can achieve up to 4 dB improvement in view synthesis, while requires much fewer bits to encode the depth map. Experimental results in multiview video coding show that the proposed method can outperform the H.264 JMVC software by more than 1 dB.