Summary: Sixth International Conference on Computer Vision; Bombay, India; Jan 1998; pp. 739--746
Grouping based on Projective Geometry Constraints and
Uncertainty
Sven Utcke
Technische Informatik I
University of Technology in Hamburg­Harburg
21071 Hamburg, Germany
Abstract
The process of grouping and subsequently recog­
nising objects in cluttered images is one laden with
di#culties; however, results can be greatly enhanced
if the inherent uncertainty of image­features is taken
into account. This paper shows that starting with the
individual edgel's uncertainty it is possible to calcu­
late covariance­information for all derived quantities.
This information can be used to choose between com­
peting algorithms, selecting the one that produces the
more reliable results, but also as an aid during the
recognition process. The consequent application of
error­propagation leads to a new formulation for the

Source: Albert-Ludwigs-Universität Freiburg, Institut für Informatik,, Lehrstuhls für Mustererkennung und Bildverarbeitung

Collections: Computer Technologies and Information Sciences