@inproceedings{ed7c8d6e98114902ab86f28871d0bc1d,
title = "Image matching for space objects based on grid-based motion statistics",
abstract = "Image matching for space objects has attracted wide attention for its importance in applications. Major challenges for this task include the textureless appearance and symmetrical structure of space objects. In this paper, we propose a novel image matching method, aiming to improve the image matching quality for space objects. Our approach consists of three main components, which are grid-based motion statistic (GMS), a contrario-random sample consensus (AC-RANSAC), and constraint of three-view. First of all, GMS is utilized to generate a collection of corresponding points. Subsequently, we adopt AC-RANSAC to eliminate false matches and estimate fundamental matrix. In the end, accurate matches are obtained under the constraint of three-view. Experimental results on simulated images of space objects have quantitatively and qualitatively demonstrated the effectiveness of our approach.",
keywords = "AC-RANSAC, Grid-based motion statistics, Image matching, Space objects",
author = "Shanlan Nie and Zhiguo Jiang and Haopeng Zhang and Quanmao Wei",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd., 2018.; 13th Conference on Image and Graphics Technologies and Applications, IGTA 2018 ; Conference date: 08-04-2018 Through 10-04-2018",
year = "2018",
doi = "10.1007/978-981-13-1702-6\_31",
language = "英语",
isbn = "9789811317019",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "310--318",
editor = "Yongtian Wang and Yuxin Peng and Zhiguo Jiang",
booktitle = "Image and Graphics Technologies and Applications - 13th Conference on Image and Graphics Technologies and Applications, IGTA 2018, Revised Selected Papers",
address = "德国",
}