Casual Stereoscopic Panorama Stitching

Fan Zhang and Feng Liu

Department of Computer Science, Portland State University

Abstract

This paper presents a method for stitching stereoscopic panoramas from stereo images casually taken using a stereo camera. This method addresses three challenges of stereoscopic image stitching: how to handle parallax, how to stitch the left- and right-view panorama consistently, and how to take care of disparity during stitching. This method addresses these challenges using a three-step approach. First, we employ a state-of-the-art stitching algorithm that handles parallax well to stitch the left views of input stereo images and create the left view of the final stereoscopic panorama. Second, we stitch the input disparity maps to obtain the target disparity map for the stereoscopic panorama by solving a Poisson's equation. This target disparity map is optimized such that there are no vertical disparities and the original perceived depth distribution is preserved. Finally, we warp the right views of the input stereo images and stitch them into the right view of the final stereoscopic panorama according to the target disparity map. The stitching of the right views is formulated as a labeling problem that is constrained by the stitching of the left views to make the left- and right-view panorama consistent to avoid retinal rivalry. Our experiments show that our method can effectively stitch casually taken stereo images and produce high-quality stereoscopic panoramas that deliver a pleasant stereoscopic 3D viewing experience.

Paper

Fan Zhang and  Feng Liu. Casual Stereoscopic Panorama Stitching.  IEEE CVPR 2015, Boston, MA, June 2015.

Related project

Fan Zhang and  Feng Liu. Parallax-tolerant Image Stitching.  IEEE CVPR 2014, Columbus, OH, June 2014. (oral, acceptance rate 5.75%) Project website Feng Liu, Yu-hen Hu and Michael Gleicher. Discovering Panoramas in Web Videos.  ACM Multimedia 2008, Vancouver, Canada, October 2008. pp. 329-338. Project website

Dataset

We experimented with our casual stereoscopic panorama stitching technique on our own stitching dataset. You can download the stereo stitching dataset here.

360° Panorama