Competitive learning algorithms for vector quantization
Neural Networks
A review of recent range image registration methods with accuracy evaluation
Image and Vision Computing
Range image registration using particle filter and competitive associative nets
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
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This paper describes range image registration to fuse three-dimensional surfaces of range images taken from around an object. By means of using the competitive associative net caUed CAN2 for plane extraction, we constructed two methods: one is for the case where the planes of the floor and the waU are available, and the other is for the case where the available planes are on the floor and the object. With experimental results using the real images obtained by the laser range finder (LRF), we examine the performance of the methods, and present several problems to be solved in future research studies.