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Publication detail
HRADIŠ, M.
Original Title
Framework for Research on Detection Classifiers
Type
article in a collection out of WoS and Scopus
Language
English
Original Abstract
Detection of patterns in images with classifiers is currently one of the most important research topics in computer vision. Many practical applications such as face detection exist and recent work even suggests that any specialized detectors (e.g. corner-point detectors) can be approximated by very fast detection classifiers. In this paper, we analyze the requirements on tools which are needed when experimenting with detection classifiers and we present a general framework which was created to fulfill these requirements. This framework offers high performance for training, high variability, elegant handling of configuration and it is able to meet all the requirements which arise when experimenting with almost all possible kinds of detection classifiers. The framework offers good testing support, full supporting infrastructure and some useful training algorithms and features. We offer this framework for research and educational purposes and we hope it will allow lower initial investments when experimenting with detection classifiers.
Keywords
Detection, Face Detection, Classification, Image Processing, Computer Vision, AdaBoost, WaldBoost, Cascade of Classifiers, Corner Points, Classifier Evaluation
Authors
RIV year
2008
Released
22. 4. 2008
Publisher
Comenius University in Bratislava
Location
Budmerice
ISBN
978-80-89186-30-3
Book
Proceedings of Spring Conference on Computer Graphics
Pages from
171
Pages to
177
Pages count
7
URL
http://www.fit.vutbr.cz/research/groups/graph/publi/2008/2008-Hradis-SCCG-Framework.pdf
BibTex
@inproceedings{BUT27709, author="Michal {Hradiš}", title="Framework for Research on Detection Classifiers", booktitle="Proceedings of Spring Conference on Computer Graphics", year="2008", pages="171--177", publisher="Comenius University in Bratislava", address="Budmerice", isbn="978-80-89186-30-3", url="http://www.fit.vutbr.cz/research/groups/graph/publi/2008/2008-Hradis-SCCG-Framework.pdf" }