Review and testing of frontal face detectors

Ilya Andreevich Kalinovskii, Vladimir Grigorievich Spitsyn

Division for Information Technology

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Abstract

This paper presents comparison results for the proposed face detection algorithm based on a compact convolutional neural network cascade and modern frontal face detectors. Test results for 16 frontal view face detectors on two public benchmarks datasets are shown. A comparative assessment of the performance of face detection algorithms is made.

Original language	English
Pages (from-to)	99-111
Number of pages	13
Journal	Computer Optics
Volume	40
Issue number	1
DOIs	https://doi.org/10.18287/2412-6179-2016-40-1-99-111
Publication status	Published - 1 Jan 2016

Keywords

Cascade classifiers
Convolutional neural networks
Deep learning
Face detection

ASJC Scopus subject areas

Atomic and Molecular Physics, and Optics
Computer Science Applications
Electrical and Electronic Engineering

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