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Stereoscopic image stitching with rectangular boundaries

Zhang, Yun, Lai, Yukun ORCID: https://orcid.org/0000-0002-2094-5680 and Zhang, Fang-Lue 2019. Stereoscopic image stitching with rectangular boundaries. Visual Computer 35 (6-8) , pp. 823-835. 10.1007/s00371-019-01694-7

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Abstract

This paper proposes a novel algorithm for stereoscopic image stitching, which aims to produce stereoscopic panoramas with rectangular boundaries. As a result, it provides wider field of view and better viewing experience for users. To achieve this, we formulate stereoscopic image stitching and boundary rectangling in a global optimization framework that simultaneously handles feature alignment, disparity consistency and boundary regularity. Given two (or more) stereoscopic images with overlapping content, each containing two views (for left and right eyes), we represent each view using a mesh and our algorithm contains three main steps: We first perform a global optimization to stitch all the left views and right views simultaneously, which ensures feature alignment and disparity consistency. Then, with the optimized vertices in each view, we extract the irregular boundary in the stereoscopic panorama, by performing polygon Boolean operations in left and right views, and construct the rectangular boundary constraints. Finally, through a global energy optimization, we warp left and right views according to feature alignment, disparity consistency and rectangular boundary constraints. To show the effectiveness of our method, we further extend our method to disparity adjustment and stereoscopic stitching with large horizon. Experimental results show that our method can produce visually pleasing stereoscopic panoramas without noticeable distortion or visual fatigue, thus resulting in satisfactory 3D viewing experience.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Computer Science & Informatics
Publisher: Springer Verlag
ISSN: 0178-2789
Funders: Royal Society
Date of First Compliant Deposit: 5 May 2019
Date of Acceptance: 21 March 2019
Last Modified: 06 Nov 2023 17:42
URI: https://orca.cardiff.ac.uk/id/eprint/122166

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