Title :
An evaluation of recent graph matching algorithms
Author :
Tian, Yu ; Liu, Yuncai
Author_Institution :
Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
Graph matching is a fundamental problem in computer vision and image processing and is widely used in object detection. Recently, many methods formulate it as integer quadratic programming problem to find inexact solutions by relaxing it in continuous domain. In this paper we classify these methods in 3 categories based on the relaxed constraints, hypothesis, solving methods, and convergence properties separately. For evaluation purpose we modify these methods and add some toy modifications to compare the detail configuration of these algorithms under different situations. Finally we try to give some explanation based on experimental results.
Keywords :
computer vision; convergence; image matching; linear programming; object detection; quadratic programming; computer vision; convergence properties; graph matching algorithms; hypothesis; image processing; integer quadratic programming problem; object detection; relaxed constraints; solving methods; graph matching; inexact matching; integer quadratic programming;
Conference_Titel :
Computer Science and Information Processing (CSIP), 2012 International Conference on
Conference_Location :
Xi´an, Shaanxi
Print_ISBN :
978-1-4673-1410-7
DOI :
10.1109/CSIP.2012.6308801