Parallel object detection on multicore platforms

Shin Kai Chen*, Tay Jyi Lin, Chih-Wei Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

9 Scopus citations

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.

Original languageEnglish
Title of host publication2009 IEEE Workshop on Signal Processing Systems, SiPS 2009 - Proceedings
Pages75-80
Number of pages6
DOIs
StatePublished - 1 Dec 2009
Event2009 IEEE Workshop on Signal Processing Systems, SiPS 2009 - Tampere, Finland
Duration: 7 Oct 20099 Oct 2009

Publication series

NameIEEE Workshop on Signal Processing Systems, SiPS: Design and Implementation
ISSN (Print)1520-6130

Conference

Conference2009 IEEE Workshop on Signal Processing Systems, SiPS 2009
CountryFinland
CityTampere
Period7/10/099/10/09

Fingerprint Dive into the research topics of 'Parallel object detection on multicore platforms'. Together they form a unique fingerprint.

Cite this