@inproceedings{29018939f4754309a26b787cfbb604f3,
title = "Region-based parallax-tolerant image stitching",
abstract = "Image Stitching with large parallax has always been a challenging task, and accurate image alignment is critical for stitching results. In this paper, an image stitching method based on superpixel segmentation regions is proposed. To solve the problem of insufficient matching feature points under large parallax, an improved multi-plane RANSAC method is used to improve the robustness of matching feature selection algorithm. In terms of image alignment, a mesh optimization method with the global similarity prior is adopted, and a superpixel-based segmentation method is used to obtain reasonable matching points and global similarity transformation parameters. A standard seam-cutting algorithm is finally used to compose images together. Experiments show that the proposed method can effectively improve the performance of image stitching in complex scenes with large parallax.",
keywords = "Global similarity transformation, Image alignment, Image stitching, Large parallax, Seam-cutting, Superpixel",
author = "Chenxu Zhao and Hai Zhang and Jieling Chen and Wenxing Fu",
note = "Publisher Copyright: {\textcopyright} COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.; 10th International Conference on Graphics and Image Processing, ICGIP 2018 ; Conference date: 12-12-2018 Through 14-12-2018",
year = "2019",
doi = "10.1117/12.2524275",
language = "英语",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Chunming Li and Hui Yu and Zhigeng Pan and Yifei Pu",
booktitle = "Tenth International Conference on Graphics and Image Processing, ICGIP 2018",
}