Parallel Object Detection on Multicore Platforms

Full metadata record

DC Field	Value	Language
dc.contributor.author	Chen, Shin-Kai	en_US
dc.contributor.author	Lin, Tay-Jyi	en_US
dc.contributor.author	Liu, Chih-Wei	en_US
dc.date.accessioned	2014-12-08T15:24:45Z	-
dc.date.available	2014-12-08T15:24:45Z	-
dc.date.issued	2009	en_US
dc.identifier.isbn	978-1-4244-4334-5	en_US
dc.identifier.issn	1520-6130	en_US
dc.identifier.uri	http://hdl.handle.net/11536/17196	-
dc.description.abstract	Object detection is an important function for intelligent multimedia processing, but its computational complexity prevented its pervasive uses in consumer electronics. Cost-effective & energy-efficient computations are now available with various innovative multicore architectures proposed for embedded systems. However, extensive software optimizations are needed to unravel the inherent parallelisms in object detection for multicore processing. This paper presents interleaved reordering and splitting of parallel tasks in object detection. Overall performance improvements by 10% & 19% have been measured for the proposed methods respectively on a face detection prototype implemented on Sony PlayStation 3.	en_US
dc.language.iso	en_US	en_US
dc.title	Parallel Object Detection on Multicore Platforms	en_US
dc.type	Proceedings Paper	en_US
dc.identifier.journal	SIPS: 2009 IEEE WORKSHOP ON SIGNAL PROCESSING SYSTEMS	en_US
dc.citation.spage	75	en_US
dc.citation.epage	80	en_US
dc.contributor.department	電子工程學系及電子研究所	zh_TW
dc.contributor.department	Department of Electronics Engineering and Institute of Electronics	en_US
dc.identifier.wosnumber	WOS:000274328800014	-
Appears in Collections:	Conferences Paper