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RESEARCH PRODUCT
Embedded System Study for Real Time Boosting Based Face Detection
Julien DuboisJiri MatasJohel MiteranKhalil Khattabsubject
Boosting (machine learning)business.industryComputer scienceEmbedded systemReal-time computingDetectorFace detectionbusinessFacial recognition systemdescription
This paper describes a study for a real time embedded face detection system. Recently, the boosting based face detection algorithms proposed by [(Viola, P and Jone, M, 2001); (Lienhart, R, et al., 2003)] have gained a lot of attention and are considered as the fastest accurate face detection algorithms today. However, the embedded implementation of such algorithms into hardware is still a challenge, since these algorithms are heavily based on memory access. A sequential implementation model is built showing its lack of regularity in time consuming and speed of detection. We propose a parallel implementation that exploits the parallelism and the pipelining in these algorithms. This implementation proves capable of increasing the speed of the detector as well as bringing regularity in time consuming.
year | journal | country | edition | language |
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2006-11-01 | IECON 2006 - 32nd Annual Conference on IEEE Industrial Electronics |