Human action recognition with MPEG-7 descriptors and architectures

Moghaddam, Z; Piccardi, M

Human action recognition with MPEG-7 descriptors and architectures

Moghaddam, Z Piccardi, M

Permalink

Publication Type:: Conference Proceeding
Citation:: ARTEMIS'10 - Proceedings of the 1st ACM Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Streams, Co-located with ACM Multimedia 2010, 2010, pp. 63 - 68
Issue Date:: 2010-12-28

Open Access

Copyright Clearance Process

Recently Added
In Progress
Open Access

This item is open access.

Adobe PDF

Download full textAdobe PDF (259.89 kB)

View on publisher's site

View statistics

Full metadata record

Field	Value	Language
dc.contributor.author	Moghaddam, Z	en_US
dc.contributor.author	Piccardi, M https://orcid.org/0000-0001-9250-6604	en_US
dc.date.issued	2010-12-28	en_US
dc.identifier.citation	ARTEMIS'10 - Proceedings of the 1st ACM Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Streams, Co-located with ACM Multimedia 2010, 2010, pp. 63 - 68	en_US
dc.identifier.isbn	9781450301633	en_US
dc.identifier.uri	http://hdl.handle.net/10453/16282
dc.description.abstract	Modern video surveillance requires addressing high-level concepts such as humans' actions and activities. In addition, surveillance applications need to be portable over a variety of platforms, from servers to mobile devices. In this paper, we explore the potential of the MPEG-7 standard to provide interfaces, descriptors, and architectures for human action recognition from surveillance cameras. Two novel MPEG-7 descriptors, symbolic and feature-based, are presented alongside two different architectures, server-intensive and client-intensive. The descriptors and architectures are evaluated in the paper by way of a scenario analysis.	en_US
dc.relation.ispartof	ARTEMIS'10 - Proceedings of the 1st ACM Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Streams, Co-located with ACM Multimedia 2010	en_US
dc.relation.isbasedon	10.1145/1877868.1877885	en_US
dc.title	Human action recognition with MPEG-7 descriptors and architectures	en_US
dc.type	Conference Proceeding
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
dc.location.activity	Florence, Italy	en_US
dc.location.activity	Nelson, New Zealands
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 - GBDTC - Global Big Data Technologies
utslib.copyright.status	open_access
pubs.publication-status	Published	en_US

Abstract:

Modern video surveillance requires addressing high-level concepts such as humans' actions and activities. In addition, surveillance applications need to be portable over a variety of platforms, from servers to mobile devices. In this paper, we explore the potential of the MPEG-7 standard to provide interfaces, descriptors, and architectures for human action recognition from surveillance cameras. Two novel MPEG-7 descriptors, symbolic and feature-based, are presented alongside two different architectures, server-intensive and client-intensive. The descriptors and architectures are evaluated in the paper by way of a scenario analysis.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/16282