Towards simultaneous place classification and object detection based on conditional random field with multiple cues

Shi, L; Kodagoda, S; Piccardi, M

Towards simultaneous place classification and object detection based on conditional random field with multiple cues

Shi, L

Kodagoda, S

Piccardi, M

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Publication Type:: Conference Proceeding
Citation:: IEEE International Conference on Intelligent Robots and Systems, 2013, pp. 2806 - 2811
Issue Date:: 2013-12-01

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Field	Value	Language
dc.contributor.author	Shi, L https://orcid.org/0000-0002-5215-025X	en_US
dc.contributor.author	Kodagoda, S https://orcid.org/0000-0001-5175-9138	en_US
dc.contributor.author	Piccardi, M https://orcid.org/0000-0001-9250-6604	en_US
dc.date.issued	2013-12-01	en_US
dc.identifier.citation	IEEE International Conference on Intelligent Robots and Systems, 2013, pp. 2806 - 2811	en_US
dc.identifier.isbn	9781467363587	en_US
dc.identifier.issn	2153-0858	en_US
dc.identifier.uri	http://hdl.handle.net/10453/27026
dc.description.abstract	Simultaneous place classification and object detection (SPCOD) is an algorithm which is able to categorize the environment (place) and detect the objects presented in the environment. Although both place classification and object detection problems have been in discussion in literature, as a concept SPCOD is still in its early stage of research. Focusing mainly on the discrimination ability of SPCOD, in this paper we have proposed a pairwise conditional random field (CRF) framework to integrate mature techniques on laser data based place classification and vision based off-the-shelf object descriptor. Extensive experimental results on a public data set demonstrate the effectiveness of the proposed method. © 2013 IEEE.	en_US
dc.relation.ispartof	IEEE International Conference on Intelligent Robots and Systems	en_US
dc.relation.isbasedon	10.1109/IROS.2013.6696753	en_US
dc.title	Towards simultaneous place classification and object detection based on conditional random field with multiple cues	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Tokyo, Japan	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 Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CAS - Centre for Autonomous Systems
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

Simultaneous place classification and object detection (SPCOD) is an algorithm which is able to categorize the environment (place) and detect the objects presented in the environment. Although both place classification and object detection problems have been in discussion in literature, as a concept SPCOD is still in its early stage of research. Focusing mainly on the discrimination ability of SPCOD, in this paper we have proposed a pairwise conditional random field (CRF) framework to integrate mature techniques on laser data based place classification and vision based off-the-shelf object descriptor. Extensive experimental results on a public data set demonstrate the effectiveness of the proposed method. © 2013 IEEE.

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http://hdl.handle.net/10453/27026