Partial correspondence based on subgraph matching

作     者：Yang, Xu Qiao, Hong Liu, Zhi-Yong 

作者机构：Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China 

出 版 物：《NEUROCOMPUTING》 (神经计算)

年 卷 期：2013年第122卷

页      面：193-197页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National natural Science Foundation of China(NSFC) [61033011, 61210009, 61101221] National Key Technology RD Program [2012BAI34B02] 

主　　题：Feature correspondence Structural model Subgraph matching GNCGCP 

摘      要：Exploiting both appearance similarity and geometric consistency is popular in addressing the feature correspondence problem. However, when there exist outliers the performance generally deteriorates greatly. In this paper, we propose a novel partial correspondence method to tackle the problem with outliers. Specifically, a novel pairwise term together with a neighborhood system is proposed, which, together with the other two pairwise terms and a unary term, formulates the correspondence to be solved as a subgraph matching problem. The problem is then approximated by the recently proposed Graduated Non-Convexity and Graduated Concavity Procedure (GNCGCP). The proposed algorithm obtains a state-of-the-art accuracy in the existence of outliers while keeping O(N-3) computational complexity and O(N-2) storage complexity. Simulations on both the synthetic and real-world images witness the effectiveness of the proposed method. (C) 2013 Elsevier B.V. All rights reserved.