A new robust operator for computer vision: application to range data

The basic MINPRAN (MINimize the Probability of RANdomness) technique, introduced by C.V. Stewart (1994), is extended to handle range data taken from complex scenes. Such data often includes: (1) a large numbers of outliers, (2) points from multiple surfaces interspersed over large image regions, and (3) extended regions containing only bad data. The initial version of MINPRAN handles cases (1) and (3). For (2), given an image region containing data from more than one surface, the basic technique tends to favor a single fit that "bridges" two surfaces. We analyze the extent of this problem and introduce two modifications to solve it. The new version of the algorithm, called MINPRAN2, produces extremely good results on difficult range data.<<ETX>>

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