Sensor registration and calibration using moving targets

Kodagoda, KRS; Alempijevic, A; Underwood, J; Kumar, S; Dissanayake, G

Sensor registration and calibration using moving targets

Kodagoda, KRS

Alempijevic, A

Underwood, J Kumar, S Dissanayake, G

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Publication Type:: Conference Proceeding
Citation:: 9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06, 2006
Issue Date:: 2006-12-01

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Field	Value	Language
dc.contributor.author	Kodagoda, KRS https://orcid.org/0000-0001-5175-9138	en_US
dc.contributor.author	Alempijevic, A https://orcid.org/0000-0002-1769-8041	en_US
dc.contributor.author	Underwood, J	en_US
dc.contributor.author	Kumar, S	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.date.issued	2006-12-01	en_US
dc.identifier.citation	9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06, 2006	en_US
dc.identifier.isbn	1424403421	en_US
dc.identifier.isbn	9781424403424	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2847
dc.description.abstract	Multimodal sensor registration and calibration are crucially important aspects in distributed sensor fusion. Unknown relationships of sensors and joint probability distribution between sensory signals make the sensor fusion nontrivial. In this paper, we adopt a Mutual Information (MI) based approach for sensor registration and calibration. It is based on unsupervised learning of a nonparametric sensing model by maximizing mutual information between signal streams. Experiments were carried out in an office like environment with two laser sensors capturing arbitrarily moving people. Attributes of the moving targets are used. Problems due to target occlusions are alleviated by the multiple model tracker. The registration and calibration methodology does not require any artificially generated patterns or motions unlike other calibration methodologies. © 2006 IEEE.	en_US
dc.relation.ispartof	9th International Conference on Control, Automation, Robotics and Vision, 2006, ICARCV '06	en_US
dc.relation.isbasedon	10.1109/ICARCV.2006.345361	en_US
dc.title	Sensor registration and calibration using moving targets	en_US
dc.type	Conference Proceeding
utslib.for	0909 Geomatic Engineering	en_US
dc.location.activity	Singapore	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Mechanical and Mechatronic Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US

Abstract:

Multimodal sensor registration and calibration are crucially important aspects in distributed sensor fusion. Unknown relationships of sensors and joint probability distribution between sensory signals make the sensor fusion nontrivial. In this paper, we adopt a Mutual Information (MI) based approach for sensor registration and calibration. It is based on unsupervised learning of a nonparametric sensing model by maximizing mutual information between signal streams. Experiments were carried out in an office like environment with two laser sensors capturing arbitrarily moving people. Attributes of the moving targets are used. Problems due to target occlusions are alleviated by the multiple model tracker. The registration and calibration methodology does not require any artificially generated patterns or motions unlike other calibration methodologies. © 2006 IEEE.

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http://hdl.handle.net/10453/2847