Finding point correspondence using local similarity and global constraint

dc.citation.epage	261	en_US
dc.citation.spage	258	en_US
dc.contributor.author	Chuang, Jen-Hui	en_US
dc.contributor.author	Kao, Jau-Hong	en_US
dc.contributor.author	Lin, Chien-Chou	en_US
dc.contributor.department	資訊工程學系	zh_TW
dc.contributor.department	Department of Computer Science	en_US
dc.date.accessioned	2014-12-08T15:24:58Z
dc.date.available	2014-12-08T15:24:58Z
dc.date.issued	2006	en_US
dc.description.abstract	Establishing feature point correspondences from a pair of stereo images or a long sequence of images is a very important research topic in computer vision. In this paper, an algorithm using local similarity and global constraint to obtain point correspondence is proposed. The point correspondences are obtained by comparing the color codes, computed by image gradients obtained as by-products from the corner detector, and spatial relationships among neighboring feature points.	en_US
dc.identifier.isbn	0-7695-2616-0	en_US
dc.identifier.journal	ICICIC 2006: First International Conference on Innovative Computing, Information and Control, Vol 2, Proceedings	en_US
dc.identifier.uri	https://ir.lib.nycu.edu.tw/handle/11536/17348
dc.identifier.wosnumber	WOS:000240868000063
dc.language.iso	en_US	en_US
dc.title	Finding point correspondence using local similarity and global constraint	en_US
dc.type	Proceedings Paper	en_US

Files

Now showing 1 - 1 of 1