Authors
Ramin Zabih, John Woodfill
Publication date
1994
Conference
Computer Vision—ECCV'94: Third European Conference on Computer Vision Stockholm, Sweden, May 2–6 1994 Proceedings, Volume II 3
Pages
151-158
Publisher
Springer Berlin Heidelberg
Description
We propose a new approach to the correspondence problem that makes use of non-parametric local transforms as the basis for correlation. Non-parametric local transforms rely on the relative ordering of local intensity values, and not on the intensity values themselves. Correlation using such transforms can tolerate a significant number of outliers. This can result in improved performance near object boundaries when compared with conventional methods such as normalized correlation. We introduce two non-parametric local transforms: the rank transform, which measures local intensity, and the census transform, which summarizes local image structure. We describe some properties of these transforms, and demonstrate their utility on both synthetic and real data.
Total citations
Scholar articles
R Zabih, J Woodfill - Computer Vision—ECCV'94: Third European …, 1994
R Zabih, J Woodfill - IEEE transactions on pattern analysis and machine …, 1996