Classifier and feature based stereo for mobile robot systems

C. H. Messom, A. L. Barczak

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

6 Citations (Scopus)

Abstract

Classifier based approaches to stereo vision reduce the ambiguity associated with low level texture and feature based image registration, however there are challenges associated with providing accurate object positioning for good depth estimation using these high level approaches. This paper investigates the performance of stereo based systems that use Haar-like features for object classification. The availability of good face detectors using this approach makes it suitable for biped and mobile robot systems that operate in environments that include people, however significant challenges exist for identifying general objects that are not as highly structured and aligned as human faces.

Original languageEnglish
Title of host publication2008 IEEE International Instrumentation and Measurement Technology Conference (I2MTC 2008)Proceedings
PublisherIEEE
Pages997-1002
Number of pages6
ISBN (Print)1424415411, 9781424415410
DOIs
Publication statusPublished - 2008
Externally publishedYes
Event2008 IEEE International Instrumentation and Measurement Technology Conference, I2MTC - Victoria, Canada
Duration: 12 May 200815 May 2008

Publication series

NameConference Record - IEEE Instrumentation and Measurement Technology Conference
ISSN (Print)1091-5281

Conference

Conference2008 IEEE International Instrumentation and Measurement Technology Conference, I2MTC
Abbreviated titleI2MTC
Country/TerritoryCanada
CityVictoria
Period12/05/0815/05/08

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