Efficient Stitching Algorithm for Stereoscopic VR Images

In this paper, we propose a novel approach for stitching stereoscopic panoramas. When stitching stereoscopic panoramas, the amount of depth retrieved is the most important factor to pay attention to. Also, it is very crucial to deliver the two left and right panoramas with the right depth information to deliver good 3D perception. However, when stitching the two panoramas independently using the state-of-the-art algorithms and methods, we do still have some inconsistencies with the disparity map retrieved from the panoramas. In order to overcome this problem, we propose a method that modifies the latest conventional algorithm by making the two panoramas dependent on one another. This brings two panoramas with a much more consistent disparity map that lets users fully immerse into a comfortable stereoscopic vision.