Reconstruction of intermediate views from stereoscopic images using disparity vectors estimated by the geometrical constraint

In this letter, we propose a reconstruction method of intermediate views from stereoscopic images captured by parallel cameras for three-dimensional (3-D) display applications. Conventional methods to reconstruct intermediate views for 3-D videoconference systems ignore the background region and assume a single object in a scene; however, in 3-D display devices such as 3-D television (TV), geometrical relationships between an object and background regions and between one object and another must be importantly considered. The proposed algorithm makes use of the geometric constraint of objects in reconstructing intermediate views. First of all, using quadtree-based variable-size block matching, we estimate disparity vectors (DVs) in visible areas in both stereoscopic images. Next, to synthesize intermediate views, we propose a novel algorithm that assigns DVs in occlusion regions, based on the geometrical constraint that describes structures of objects. Finally, we present four different intermediate views between two stereoscopic images. Experimental results show that the proposed algorithm assigns more precise DVs to occlusion regions and obtains more accurate intermediate views than conventional algorithms.