Camera control and multimedia interaction using individual object recognition

Xu, RYD; Jin, JS

Camera control and multimedia interaction using individual object recognition

Xu, RYD Jin, JS

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Publication Type:: Journal Article
Citation:: Journal of Multimedia, 2007, 2 (3), pp. 77 - 85
Issue Date:: 2007-01-01

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Field	Value	Language
dc.contributor.author	Xu, RYD	en_US
dc.contributor.author	Jin, JS	en_US
dc.date.issued	2007-01-01	en_US
dc.identifier.citation	Journal of Multimedia, 2007, 2 (3), pp. 77 - 85	en_US
dc.identifier.issn	1796-2048	en_US
dc.identifier.uri	http://hdl.handle.net/10453/26564
dc.description.abstract	Currently, most of the automated, computervision assisted camera control policies are based on human events, such as the speaker gesture and position changes. In addition to these events, in this paper, we introduce a set of natural camera control and multimedia synchronization schemes based on the individual object interaction. We describe in detail, how our unique method, in which the head-pose estimation are used to compute the region of interest (ROI) for recognizing the hand-held object. We explain, from our results, how our approach has achieved robustness, efficiency and unambiguous object interaction during real-time video shooting. © 2007 ACADEMY PUBLISHER.	en_US
dc.relation.ispartof	Journal of Multimedia	en_US
dc.relation.isbasedon	10.4304/jmm.2.3.77-85	en_US
dc.title	Camera control and multimedia interaction using individual object recognition	en_US
dc.type	Journal Article
utslib.citation.volume	3	en_US
utslib.citation.volume	2	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	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 - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.issue	3	en_US
pubs.publication-status	Published	en_US
pubs.volume	2	en_US

Abstract:

Currently, most of the automated, computervision assisted camera control policies are based on human events, such as the speaker gesture and position changes. In addition to these events, in this paper, we introduce a set of natural camera control and multimedia synchronization schemes based on the individual object interaction. We describe in detail, how our unique method, in which the head-pose estimation are used to compute the region of interest (ROI) for recognizing the hand-held object. We explain, from our results, how our approach has achieved robustness, efficiency and unambiguous object interaction during real-time video shooting. © 2007 ACADEMY PUBLISHER.

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http://hdl.handle.net/10453/26564