Local Depth Patterns for Fine-Grained Activity Recognition in Depth Videos

Awwad, S; Piccardi, M

Local Depth Patterns for Fine-Grained Activity Recognition in Depth Videos

Awwad, S Piccardi, M

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Publisher:: IEEE
Publication Type:: Conference Proceeding
Citation:: PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON IMAGE AND VISION COMPUTING NEW ZEALAND (IVCNZ), 2016, pp. 214-219
Issue Date:: 2016-01-01

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Field	Value	Language
dc.contributor.author	Awwad, S
dc.contributor.author	Piccardi, M https://orcid.org/0000-0001-9250-6604
dc.contributor.editor	Bailey, D
dc.contributor.editor	SenGupta, G
dc.contributor.editor	Marsland, S
dc.date	2016-11-21
dc.date.accessioned	2021-03-29T06:58:04Z
dc.date.available	2021-03-29T06:58:04Z
dc.date.issued	2016-01-01
dc.identifier.citation	PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON IMAGE AND VISION COMPUTING NEW ZEALAND (IVCNZ), 2016, pp. 214-219
dc.identifier.issn	2151-2191
dc.identifier.uri	http://hdl.handle.net/10453/147618
dc.language	en
dc.publisher	IEEE
dc.relation.ispartof	PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON IMAGE AND VISION COMPUTING NEW ZEALAND (IVCNZ)
dc.relation.ispartof	International Conference on Image and Vision Computing New Zealand (IVCNZ)
dc.relation.ispartofseries	International Conference on Image and Vision Computing New Zealand
dc.rights	© 2016 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.	en_US
dc.rights	info:eu-repo/semantics/restrictedAccess
dc.title	Local Depth Patterns for Fine-Grained Activity Recognition in Depth Videos
dc.type	Conference Proceeding
utslib.location.activity	Massey Univ, Sch Engn & Adv Technol, Palmerston North, NEW ZEALAND
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/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
utslib.copyright.status	in_progress	*
dc.date.updated	2021-03-29T06:58:03Z
pubs.finish-date	2016-11-22
pubs.publication-status	Published
pubs.start-date	2016-11-21

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http://hdl.handle.net/10453/147618