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
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;
Conference_Titel :
Pattern Recognition, 2000. Proceedings. 15th International Conference on
Conference_Location :
Barcelona
Print_ISBN :
0-7695-0750-6
DOI :
10.1109/ICPR.2000.906107