Real-time rotationally invariant features for environmental feature detection by mobile robots and sensor networks

Andre Barczak*, Chris Messom, Ravi Chemudugunta

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

We introduce a mobile and/ or remote sensor framework for computationally fast rotationally invariant feature detection. The sensor and computational system is small enough to be carried by a mobile robot platform with a relatively low power requirement allowing the system to be deployed without the need for frequent recharges of the batteries. The rotationally invariant Haar-like features are introduced and evaluated both at feature level and in classifiers. Other invariant approaches such as moment based approaches do not offer the same discriminatory power as the Haar-like rotationally invariant features to detect complex objects such as hands and faces.

Original languageEnglish
Title of host publicationROSE 2007 - International Workshop on Robotic and Sensor Environments, Proceedings
PublisherIEEE
Pages19-24
Number of pages6
ISBN (Print)1424415276, 9781424415274
DOIs
Publication statusPublished - 2007
Externally publishedYes
Event2007 IEEE International Workshop on Robotic and Sensor Environments - Ottawa, ON, Canada
Duration: 12 Oct 200713 Oct 2007

Publication series

NameROSE 2007 - International Workshop on Robotic and Sensor Environments, Proceedings

Conference

Conference2007 IEEE International Workshop on Robotic and Sensor Environments
Abbreviated titleROSE 2007
Country/TerritoryCanada
CityOttawa, ON
Period12/10/0713/10/07

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