Torso detection and tracking using a 2D laser range finder

Zainudin, Z; Kodagoda, S; Dissanayake, G

Torso detection and tracking using a 2D laser range finder

Zainudin, Z Kodagoda, S

Dissanayake, G

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Publication Type:: Conference Proceeding
Citation:: Proceedings of the 2010 Australasian Conference on Robotics and Automation, ACRA 2010, 2010
Issue Date:: 2010-12-01

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Field	Value	Language
dc.contributor.author	Zainudin, Z	en_US
dc.contributor.author	Kodagoda, S https://orcid.org/0000-0001-5175-9138	en_US
dc.contributor.author	Dissanayake, G https://orcid.org/0000-0002-7992-0680	en_US
dc.date.issued	2010-12-01	en_US
dc.identifier.citation	Proceedings of the 2010 Australasian Conference on Robotics and Automation, ACRA 2010, 2010	en_US
dc.identifier.isbn	9780980740417	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16405
dc.description.abstract	Detecting and tracking people in populated environments has various applications including, robotics, healthcare, automotive, security and defence. In this paper, we present an algorithm for people detection and tracking based on a two dimensional laser rage finder (LRF). The LRF was mounted on a mobile robotic platform to scan a torso section of a person. The tracker is designed to discard spurious targets based on the log likelihood ratio and can effectively handle short term occlusions. Long term occlusions are considered as new tracks. Performance of the algorithm is analysed based on experiments, which shows appealing results.	en_US
dc.relation.ispartof	Proceedings of the 2010 Australasian Conference on Robotics and Automation, ACRA 2010	en_US
dc.title	Torso detection and tracking using a 2D laser range finder	en_US
dc.type	Conference Proceeding
utslib.for	090602 Control Systems, Robotics and Automation	en_US
dc.location.activity	Queensland University of Technology, Brisbane, QueenslandE, Australia	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	open_access
pubs.publication-status	Published	en_US

Abstract:

Detecting and tracking people in populated environments has various applications including, robotics, healthcare, automotive, security and defence. In this paper, we present an algorithm for people detection and tracking based on a two dimensional laser rage finder (LRF). The LRF was mounted on a mobile robotic platform to scan a torso section of a person. The tracker is designed to discard spurious targets based on the log likelihood ratio and can effectively handle short term occlusions. Long term occlusions are considered as new tracks. Performance of the algorithm is analysed based on experiments, which shows appealing results.

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http://hdl.handle.net/10453/16405