Competitive Hopfield neural network for stereo vision correspondence

被引：0

作者：

Mayoral, R ^{[1
]}

Pérez-Ilzarbe, MJ ^{[1
]}

机构：

[1] Univ Publ Navarra, Dept Automat & Computac, E-31006 Pamplona, Spain

来源：

IJCNN 2000: PROCEEDINGS OF THE IEEE-INNS-ENNS INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOL V | 2000年

关键词：

D O I：

10.1109/IJCNN.2000.861513

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

For the correspondence problem in stereo vision, we developed an Hopfield algorithm that favors unicity of the matches for all interest points both on the left and right images. Although the convergence of the network used cannot be theoretically proven, we have experimentally shown that for the cases we are interested in the method converges either to a stable state or to an acceptable limit cycle. The method is computationally fast.

引用

页码：464 / 469

页数：6

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