DocumentCode :
3728272
Title :
Local Topology Preserved Tensor Models for Graph Matching
Author :
Jiufeng Zhou;Hong Yan;Yuan Zhu
Author_Institution :
Dept. of Electron. &
fYear :
2015
Firstpage :
2153
Lastpage :
2157
Abstract :
This paper proposes local topology preserved features in graph matching problem based on tensor technique. Many tensor based works paid much attention on catching many invariant feature tuples while local information for every single point to improve matching performance is also important. Here our proposed Local Topology Preserved Tensor (LTPT) models not only take into account of the neighbor structure but also employ the three-order tensor technique to keep the geometric consistency. Extensive experiments on the synthetic and real datasets show that LTPT performs better than the state-of-the-art graph matching methods.
Keywords :
"Tensile stress","Topology","Feature extraction","Data mining","Time complexity","Biological system modeling","Matrix decomposition"
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2015 IEEE International Conference on
Type :
conf
DOI :
10.1109/SMC.2015.376
Filename :
7379508
Link To Document :
بازگشت