@inproceedings{bd01b6c0a01d4414835376713e111aa5,
title = "Accurate joint template matching based on tree propagating",
abstract = "Given a single template image, it is a big challenge to match all the target images accurately only by pairwise template matching. To handle this case, this paper introduces an accurate template matching method based on tree structure building to jointly match a set of target images. Our method aims to select well matched results for template updating and rescue badly matched images via the tree matching propagating. First, a novel similarity measure is given to evaluate the pairwise matching results. Then the joint matching is under an iterative framework which contains two main steps: (1) tree structure growing; and (2) matching propagating. When all the target images are included in the tree structure, the matching process is finished. Finally, experimental results demonstrate the improvement of the proposed method.",
keywords = "Joint, Template matching, Template updating, Tree propagating",
author = "Qian Kou and Yang Yang and Shaoyi Du and Zhuo Chen and Weile Chen and Dexing Zhong",
note = "Publisher Copyright: {\textcopyright} Springer Nature Singapore Pte Ltd. 2017.; 2nd Chinese Conference on Computer Vision, CCCV 2017 ; Conference date: 11-10-2017 Through 14-10-2017",
year = "2017",
doi = "10.1007/978-981-10-7299-4\_25",
language = "英语",
isbn = "9789811072987",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "307--319",
editor = "Xiang Bai and Qinghua Hu and Liang Wang and Qingshan Liu and Jinfeng Yang and Ming-Ming Cheng and Deyu Meng",
booktitle = "Computer Vision - 2nd CCF Chinese Conference, CCCV 2017, Proceedings",
}