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 | |
| Publication status | Published - 1 Jan 2016 |
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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
Cite this
Review and testing of frontal face detectors. / Kalinovskii, Ilya Andreevich; Spitsyn, Vladimir Grigorievich.
In: Computer Optics, Vol. 40, No. 1, 01.01.2016, p. 99-111.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Review and testing of frontal face detectors
AU - Kalinovskii, Ilya Andreevich
AU - Spitsyn, Vladimir Grigorievich
PY - 2016/1/1
Y1 - 2016/1/1
N2 - 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.
AB - 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.
KW - Cascade classifiers
KW - Convolutional neural networks
KW - Deep learning
KW - Face detection
UR - http://www.scopus.com/inward/record.url?scp=84961257779&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84961257779&partnerID=8YFLogxK
U2 - 10.18287/2412-6179-2016-40-1-99-111
DO - 10.18287/2412-6179-2016-40-1-99-111
M3 - Article
AN - SCOPUS:84961257779
VL - 40
SP - 99
EP - 111
JO - Computer Optics
JF - Computer Optics
SN - 0134-2452
IS - 1
ER -