Efficient Face Detection on Epiphany Multicore Processor
Abstract
The article studies the possibility of usage of energy-efficient Epiphany microprocessor for solving actual applied problem of face detection at still image. The microprocessor is a multicore system with distributed memory, implemented in a single chip. Due to small die area, the micropro-cessor has significant hardware limitations (in particular it has only 32 kilobytes of memory per core) which limit the range of usable algorithms and complicate their software implementation. Common face-detection algorithm based on local binary patterns (LBP) and cascading classifier was adapted for parallel implementation. It is shown that Epiphany microprocessor having 16 cores can outperform single-core CPU of personal computer having the same clock rate by a factor of 2.5, while consuming only 0.5 watts of electric power.
Keywords
face detection,
local binary patterns,
parallel data processing,
specialized processors,
distributed memory
Supporting agencies: The research is done within the frame independent R&D.
About the Authors
Anton A. Sukhinov
UAB “Pixelmator Team”
(Lithuania, Vilnius, J. Kubiliaus g. 6-1, LT-08234)
Lithuania
Lithuania
Sukhinov Anton A., Candidate of Sciences in Physics and Mathematics, Developer UAB “Pixelmator Team” (Lithuania, Vilnius, J. Kubiliaus g. 6-1, LT-08234)
Georgiy B. Ostrobrod
CVisionLab LLC
(Russia, Taganrog, Severnaya Ploshchad 3, office 5, 347900)
Russian Federation
Russian Federation
Ostrobrod Georgiy B., Senior Developer, CVisionLab LLC (Russia, Taganrog, Severnaya Ploshchad 3, office 5, 347900)
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Review
For citations:
Sukhinov A.A., Ostrobrod G.B. Efficient Face Detection on Epiphany Multicore Processor. Computational Mathematics and Information Technologies. 2017;1(1).
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