DocumentCode :
1742980
Title :
Image analysis by accumulative Hopfield matching
Author :
Li, Wen-Jing ; Lee, Tong ; Tsui, Hung-Tat
Author_Institution :
Dept. of Electron. Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong
Volume :
2
fYear :
2000
fDate :
2000
Firstpage :
442
Abstract :
In this paper, a novel image analysis system based on attributed relational graph matching is proposed, which is called accumulative Hopfield matching. We first divide the scene graph into many sub-graphs, and a modified Hopfield network is then constructed to obtain the sub-graph isomorphism between each sub-scene graph and model graph. The final result is deduced by accumulating the solutions of all small subnetworks. The proposed system was applied to automatic object recognition and modeling of articulated objects with good results
Keywords :
Hopfield neural nets; graph theory; image matching; learning (artificial intelligence); object recognition; Hopfield neural network; attributed relational graph matching; image analysis; image matching; model learning; object recognition; pose estimation; scene graph; Computer industry; Computer vision; Image analysis; Industrial relations; Layout; Neural networks; Object recognition; Shape; Tree graphs; Very large scale integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
ISSN :
1051-4651
Print_ISBN :
0-7695-0750-6
Type :
conf
DOI :
10.1109/ICPR.2000.906107
Filename :
906107
Link To Document :
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