Content area

Abstract

Conventional cameras and fisheye cameras are often used together to capture clear target images and large scene background images in many applications, such as mobile robotic telepresence systems and large scene monitoring systems. In this paper, we propose to stitch images from these cameras for offering remote operators a large field of view to perceive a local environment. To provide a clear view of targets for face-to-face communication and a complete view of a robot’s surroundings for safe teleoperation of the robot, we stitch these images by keeping the original conventional image. The image stitching is formulated as a nonrigid motion estimation problem and images are stitched based on nonrigid warping, e.g., the thin-plate spline. To improve the algorithmic efficiency of image stitching, we exploit a region-based point correspondence selection method to reduce the number of point correspondences that are used for thin-plate spline interpolation. The experiments conducted on collected images and images captured from a telepresence system show the effectiveness of the proposed method.

Details

Title
Stitching images from a conventional camera and a fisheye camera based on nonrigid warping
Author
Dong Yanmei 1 ; Pei Mingtao 2   VIAFID ORCID Logo  ; Wu, Yuwei 2 ; Jia Yunde 2 

 Guangxi University of Science and Technology, Tus College of Digit, Liuzhou, People’s Republic of China (GRID:grid.440719.f) (ISNI:0000 0004 1800 187X); Beijing Institute of Technology, Beijing Laboratory of Intelligent Information Technology, School of Computer Science, Beijing, People’s Republic of China (GRID:grid.43555.32) (ISNI:0000 0000 8841 6246) 
 Beijing Institute of Technology, Beijing Laboratory of Intelligent Information Technology, School of Computer Science, Beijing, People’s Republic of China (GRID:grid.43555.32) (ISNI:0000 0000 8841 6246) 
Pages
18417-18435
Publication year
2022
Publication date
May 2022
Publisher
Springer Nature B.V.
ISSN
13807501
e-ISSN
15737721
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2660203494
Copyright
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.