Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)

Fast Deformation Part Model with CNN for Face Detection

Authors
Canzhang Guo, Yinwei Zhan
Corresponding Author
Canzhang Guo
Available Online May 2018.
DOI
10.2991/ncce-18.2018.65How to use a DOI?
Keywords
DPM; filter pyramid; scale invariance; face detection
Abstract

This paper proposes a fast deformation part model (DPM) with neural network (FDPDPM) for face detection. It can make fully use of the advantage of high level feature and classifier with spatial location information. In fact, this paper uses a truncated the variant of VVGNET and a pyramid of multi-scale filter method to maintain the scale invariance. As a result, it not only improves the detection efficiency, but also makes a contribution to better detection effect on the face with small size and partial occlusion

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
Series
Advances in Intelligent Systems Research
Publication Date
May 2018
ISBN
10.2991/ncce-18.2018.65
ISSN
1951-6851
DOI
10.2991/ncce-18.2018.65How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Canzhang Guo
AU  - Yinwei Zhan
PY  - 2018/05
DA  - 2018/05
TI  - Fast Deformation Part Model with CNN for Face Detection
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 408
EP  - 413
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.65
DO  - 10.2991/ncce-18.2018.65
ID  - Guo2018/05
ER  -