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Robust adaptive segmentation of range images

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3 Author(s)
Kil-Moo Lee ; Dept. of Electron. Eng., Sogang Univ., Seoul, South Korea ; P. Meer ; Rae-Hong Park

We propose a novel image segmentation technique using the robust, adaptive least kth order squares (ALKS) estimator which minimizes the kth order statistics of the squares of residuals. The optimal value of k is determined from the data, and the procedure detects the homogeneous surface patch representing the relative majority of the pixels. The ALKS shows a better tolerance to structured outliers than other recently proposed similar techniques. The performance of the new, fully autonomous, range image segmentation algorithm is compared to several other methods

Published in:

IEEE Transactions on Pattern Analysis and Machine Intelligence  (Volume:20 ,  Issue: 2 )