Dense image correspondence under large appearance variations

• Main Authors: LIU, Linlin, LOW, Kok-Lim, LIN, Wen-yan
• 格式: text
• 語言: English
• 出版: Institutional Knowledge at Singapore Management University 2013
• 主題: belief propagation; image matching; image motion analysis; image registration; SIFT Flow; Graphics and Human Computer Interfaces; Software Engineering
• 在線閱讀: https://ink.library.smu.edu.sg/sis_research/4811; https://ink.library.smu.edu.sg/context/sis_research/article/5814/viewcontent/image_match_icip2013.pdf
• 機構: Singapore Management University

This paper addresses the difficult problem of finding dense correspondence across images with large appearance variations. Our method uses multiple feature samples at each pixel to deal with the appearance variations based on our observation that pre-defined single feature sample provides poor resul...