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

Author

Stewart, Charles V.

Author_Institution

Dept. of Comput. Sci., Rensselaer Polytech. Inst., Troy, NY, USA

fYear

1994

fDate

21-23 Jun 1994

Firstpage

167

Lastpage

173

Abstract

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

Keywords

computer vision; minimisation; probability; MINPRAN technique; MINPRAN2; bad data; complex scenes; computer vision; image regions; multiple surfaces; outliers; randomness probability minimization; range data; robust operator; single fit; Machine vision; Minimization methods; Probability; Surfaces;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Vision and Pattern Recognition, 1994. Proceedings CVPR '94., 1994 IEEE Computer Society Conference on

Conference_Location

Seattle, WA

ISSN

1063-6919

Print_ISBN

0-8186-5825-8

Type

conf

DOI

10.1109/CVPR.1994.323825

Filename

323825