Mean shift object tracking for a SIMD computer

Allen, JG; Xu, RYD; Jin, JS

Mean shift object tracking for a SIMD computer

Allen, JG Xu, RYD Jin, JS

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 3rd International Conference on Information Technology and Applications, ICITA 2005, 2005, I pp. 692 - 697
Issue Date:: 2005-12-01

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Field	Value	Language
dc.contributor.author	Allen, JG	en_US
dc.contributor.author	Xu, RYD	en_US
dc.contributor.author	Jin, JS	en_US
dc.date.issued	2005-12-01	en_US
dc.identifier.citation	Proceedings - 3rd International Conference on Information Technology and Applications, ICITA 2005, 2005, I pp. 692 - 697	en_US
dc.identifier.isbn	0769523161	en_US
dc.identifier.isbn	9780769523163	en_US
dc.identifier.uri	http://hdl.handle.net/10453/2437
dc.description.abstract	We use SIMD instructions to implement a popular video object-tracking algorithm in an attempt to achieve the best possible performance on the available hardware. We start with an implementation of the well-known mean shift algorithm with adaptive scale and background-weighted histogram enhancements. Due to its histogramic nature, mean shift is not normally considered worth optimizing with vector instructions. However, when we looked for basic opportunities to exploit SIMD style processing, we in fact discovered several opportunities to exploit SIMD instructions. We compare the tracking efficiency of our implementation with a standard implementation in order to demonstrate the efficiency of the modified technique. In this paper we present the optimizations we have applied as well as the performance results obtained. © 2005 IEEE.	en_US
dc.relation.ispartof	Proceedings - 3rd International Conference on Information Technology and Applications, ICITA 2005	en_US
dc.relation.isbasedon	10.1109/ICITA.2005.177	en_US
dc.title	Mean shift object tracking for a SIMD computer	en_US
dc.type	Conference Proceeding
utslib.citation.volume	I	en_US
utslib.for	080104 Computer Vision	en_US
utslib.for	080305 Multimedia Programming	en_US
dc.location.activity	Sydney, 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 Business
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.publication-status	Published	en_US
pubs.volume	I	en_US

Abstract:

We use SIMD instructions to implement a popular video object-tracking algorithm in an attempt to achieve the best possible performance on the available hardware. We start with an implementation of the well-known mean shift algorithm with adaptive scale and background-weighted histogram enhancements. Due to its histogramic nature, mean shift is not normally considered worth optimizing with vector instructions. However, when we looked for basic opportunities to exploit SIMD style processing, we in fact discovered several opportunities to exploit SIMD instructions. We compare the tracking efficiency of our implementation with a standard implementation in order to demonstrate the efficiency of the modified technique. In this paper we present the optimizations we have applied as well as the performance results obtained. © 2005 IEEE.

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http://hdl.handle.net/10453/2437