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Stereoscopic Image Stitching via Disparity-Constrained Warping and Blending

As a significant branch of virtual reality, stereoscopic image stitching aims to generating wide perspectives and natural-looking scenes. Existing 2D image stitching methods cannot be successfully applied to the stereoscopic… Click to show full abstract

As a significant branch of virtual reality, stereoscopic image stitching aims to generating wide perspectives and natural-looking scenes. Existing 2D image stitching methods cannot be successfully applied to the stereoscopic images without considering the disparity consistency of stereoscopic images. To address this issue, this paper presents a stereoscopic image stitching method based on disparity-constrained warping and blending, which could avoid visual distortion and preserve disparity consistency. First, a point-line-driven homography based disparity minimization method is designed to pre-align the left and right images and reduce vertical disparity. Afterwards, a multi-constraint warping is proposed to further align the left and right images, where the initial disparity map is introduced to control the consistency of disparities. Finally, a disparity consistency seam-cutting and blending method is presented to determine the optimal seam and conduct stereoscopic image stitching. Experimental results demonstrate that the proposed method achieves competitive performance compared with other state-of-the-art methods.

Keywords: image stitching; stereoscopic image; constrained warping; disparity constrained; disparity

Journal Title: IEEE Transactions on Multimedia
Year Published: 2020

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