An Efficient Method of Face and Keypoint Detection Based on Shared Network

DOI

10.2991/acaai-18.2018.22How to use a DOI?

Keywords

face detection; facial keypoint detection; fused network

Abstract

We propose a method to perform face detection and facial keypoint detection in parallel. On the basis of the traditional object detection framework Faster R-CNN for face detection, we have designed a facial keypoint detection network with the same base network. And the two networks share the weights of the base network by the method of alternate training. Depends on the feature map in Faster R-CNN, after detecting the face box, we can find the feature patch corresponding to the face box directly. In this way, we make the two models can be fused together. Compared with the traditional serial process, our model run faster more than 20%, with the same accuracy.

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/).

Download article (PDF)

TY  - CONF
AU  - Xiaogang Tian
AU  - Xiaoye Fan
AU  - Feixue Tang
AU  - Xixin Cao
PY  - 2018/03
DA  - 2018/03
TI  - An Efficient Method of Face and Keypoint Detection Based on Shared Network
BT  - Proceedings of the 2018 International Conference on Advanced Control, Automation and Artificial Intelligence (ACAAI 2018)
PB  - Atlantis Press
SP  - 90
EP  - 93
SN  - 1951-6851
UR  - https://doi.org/10.2991/acaai-18.2018.22
DO  - 10.2991/acaai-18.2018.22
ID  - Tian2018/03
ER  -