Algorithm Evaluation by Probabilistic Fitness/Cost Analysis and Application to Image Segmentation

MR Everingham, H Muller, BT Thomas

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

Abstract

In many areas of computer vision the research producing new algorithms greatly exceeds work on their evaluation. Evaluation of vision algorithms is often difficult because of the multiple objectives that an algorithm should meet, for example accuracy and computational efficiency, and because algorithms typically have several parameters which must be specified by the user. In this paper we propose a framework for evaluation of algorithms with multiple objectives, which allows probabilistic analysis of the behavior of a set of algorithms in a joint fitness/cost space. We take the image segmentation problem as an example application domain and use our approach to compare seven state-of-the-art image segmentation algorithms.
Translated title of the contributionAlgorithm Evaluation by Probabilistic Fitness/Cost Analysis and Application to Image Segmentation
Original languageEnglish
Title of host publicationUnknown
EditorsD. Suter, A. Bab-Hadiashar
PublisherAsian Federation of Computer Vision Societies (AFCV)
Pages580 - 586
Number of pages6
ISBN (Print)0958025606
Publication statusPublished - Jan 2002

Bibliographical note

Conference Proceedings/Title of Journal: Proceedings of the 5th Asian Conference on Computer Vision (ACCV2002)

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