A review of recent range image registration methods with accuracy evaluation
Image and Vision Computing
Range image registration using plane extraction by the CAN2
CIRA'09 Proceedings of the 8th IEEE international conference on Computational intelligence in robotics and automation
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This paper presents a method using a particle filter (PF) and competitive associative nets (CAN2s) for range image registration to fuse 3D surfaces on range images taken from around an object by the laser range finder (LRF). The method uses the CAN2 for learning to provide a piecewise linear approximation of the LRF data involving various noise, and obtaining a coarse but fast pairwise registration. The PF is used for reducing the cumulative error of the consecutive pair-wise registration. The effectiveness is shown by using the real LRF data of a rectangular box.