DocumentCode
3413606
Title
An evaluation of recent graph matching algorithms
Author
Tian, Yu ; Liu, Yuncai
Author_Institution
Dept. of Autom., Shanghai Jiao Tong Univ., Shanghai, China
fYear
2012
fDate
24-26 Aug. 2012
Firstpage
85
Lastpage
88
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Information Processing (CSIP), 2012 International Conference on
Conference_Location
Xi´an, Shaanxi
Print_ISBN
978-1-4673-1410-7
Type
conf
DOI
10.1109/CSIP.2012.6308801
Filename
6308801
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