Improved data association and occlusion handling for vision-based people tracking by mobile robots

Grzegorz Cielniak, Tom Duckett, Achim J. Lilienthal

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

19 Scopus citations

Abstract

This paper presents an approach for tracking multiple persons using a combination of colour and thermal vision sensors on a mobile robot. First, an adaptive colour model is incorporated into the measurement model of the tracker. Second, a new approach for detecting occlusions is introduced, using a machine learning classifier for pairwise comparison of persons (classifying which one is in front of the other). Third, explicit occlusion handling is then incorporated into the tracker.

Original languageEnglish
Title of host publicationProceedings of the 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007
Pages3436-3441
Number of pages6
DOIs
StatePublished - 2007
Externally publishedYes
Event2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007 - San Diego, CA, United States
Duration: 29 Oct 20072 Nov 2007

Publication series

NameIEEE International Conference on Intelligent Robots and Systems

Conference

Conference2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2007
Country/TerritoryUnited States
CitySan Diego, CA
Period29/10/072/11/07

Fingerprint

Dive into the research topics of 'Improved data association and occlusion handling for vision-based people tracking by mobile robots'. Together they form a unique fingerprint.

Cite this