Stochastic Analysis of Scale-Space Smoothing

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceeding

Abstract

In the high-level operations of computer vision it is taken for granted that image features have been reliably detected. This paper addresses the problem of feature extraction by scale-space methods. This paper is based on two key ideas: to investigate the stochastic properties of scale-space representations, and to investigate the interplay between discrete and continuous images. These investigations are then used to predict the stochastic properties of sub-pixel feature detectors

Details

Authors
Organisations
Research areas and keywords

Subject classification (UKÄ) – MANDATORY

  • Mathematics

Keywords

  • computer vision, correlation methods, feature extraction, interpolation, smoothing methods, stochastic processes
Original languageEnglish
Title of host publication13th International Conference on Pattern Recognition
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Pages305-309
Volume2
ISBN (Print)0 8186 7282 X
Publication statusPublished - 1996
Publication categoryResearch
Peer-reviewedNo
Event13th International Conference on Pattern Recognition, (ICPR 1996) - Vienna, Austria
Duration: 1996 Aug 251996 Aug 29

Publication series

Name
Volume2

Conference

Conference13th International Conference on Pattern Recognition, (ICPR 1996)
CountryAustria
CityVienna
Period1996/08/251996/08/29