@inproceedings{f08c2c8a008e48d28f725a81b23a34ca,
title = "Robust Image Matching for Camera Pose Estimation Using Oriented Fast and Rotated Brief",
abstract = "This paper presents a novel image matching method for camera pose estimation based on point cloud segmentation. The Oriented Fast and Rotated Brief (ORB) is employed to extract the key points, which are then extracted based on matched point cloud planes. The point cloud planes are segmented based on the depth image, and then matched by the distance of the centroid between planes. The putative corresponding key points on the planes are generated based on the distance of their 3-D coordinates and the descriptors of the key points are further matched based on the putative corresponding key points. As an additional constraint, the spatial relative position in 3-D spaces solves the problem that the descriptors of each key point in some scenarios are too similar which may lead to a mismatch. According to the experimental results, the superiority of the proposed approach is illustrated by comparing with the existing matching methods.",
keywords = "Image Matching, Image Segmentation, Oriented Fast and Rotated Brief, Point Cloud",
author = "Junqi Bao and Xiaochen Yuan and Lam, \{Chan Tong\}",
note = "Publisher Copyright: {\textcopyright} 2022 ACM.; 5th International Conference on Algorithms, Computing and Artificial Intelligence, ACAI 2022 ; Conference date: 23-12-2022 Through 25-12-2022",
year = "2022",
month = dec,
day = "23",
doi = "10.1145/3579654.3579720",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
booktitle = "ACAI 2022 - Conference Proceedings",
}