Real-Time Facial Feature Extraction Scheme Using Cascaded Networks

Hyeonwoo Kim; Hyungjoon Kim; Eenjun Hwang

doi:10.1109/BIGCOMP.2019.8679316

Real-Time Facial Feature Extraction Scheme Using Cascaded Networks

Hyeonwoo Kim, Hyungjoon Kim, Eenjun Hwang

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

12 Citations (Scopus)

Abstract

Facial landmarks such as eyes, nose, and mouth are the most prominent feature points on the face. So far, many works have been done for efficiently extracting such landmarks from facial images. Utilizing more feature points for landmark extraction usually requires more processing time, which has been an obstacle to real-time processing or video processing. On the contrary, utilizing a too small number of feature points cannot represent diverse landmark properties such as shape accurately. In this paper, we propose a deep learning based method for extracting popular 68 feature points for facial landmarks quickly and accurately. To do that, we first detect all the faces in the image by using a cascaded structure composed of relatively light Convolution Neural Networks(CNN). Then, we perform facial landmark extraction for each face, which reduces the processing time a lot. We performed several experiments to evaluate the performance of our method. We report some of the results.

Original language	English
Title of host publication	2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538677896
DOIs	https://doi.org/10.1109/BIGCOMP.2019.8679316
Publication status	Published - 2019 Apr 1
Event	2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Kyoto, Japan Duration: 2019 Feb 27 → 2019 Mar 2

Publication series

Name	2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings

Conference

Conference	2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019
Country/Territory	Japan
City	Kyoto
Period	19/2/27 → 19/3/2

Bibliographical note

Funding Information:
ACKNOWLEDGMENT This work was partly supported by Institute for Information & communications Technology Promotion (IITP) grant funded by the Korea government (MSIT) (No. R0190- 16-2012, High Performance Big Data Analytics Platform Performance Acceleration Technologies Development) and Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2016R1D1A1A09919590).

Publisher Copyright:
© 2019 IEEE.

Keywords

Facial landmarks
MTCNN
cascaded structure
face alignment
face detection
real-time extraction

ASJC Scopus subject areas

Information Systems and Management
Artificial Intelligence
Computer Networks and Communications
Information Systems

Access to Document

10.1109/BIGCOMP.2019.8679316

Cite this

Kim, H., Kim, H., & Hwang, E. (2019). Real-Time Facial Feature Extraction Scheme Using Cascaded Networks. In 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings Article 8679316 (2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIGCOMP.2019.8679316

Real-Time Facial Feature Extraction Scheme Using Cascaded Networks. / Kim, Hyeonwoo; Kim, Hyungjoon; Hwang, Eenjun.
2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. 8679316 (2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kim, H, Kim, H & Hwang, E 2019, Real-Time Facial Feature Extraction Scheme Using Cascaded Networks. in 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings., 8679316, 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings, Institute of Electrical and Electronics Engineers Inc., 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019, Kyoto, Japan, 19/2/27. https://doi.org/10.1109/BIGCOMP.2019.8679316

Kim H, Kim H, Hwang E. Real-Time Facial Feature Extraction Scheme Using Cascaded Networks. In 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc. 2019. 8679316. (2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings). doi: 10.1109/BIGCOMP.2019.8679316

Kim, Hyeonwoo ; Kim, Hyungjoon ; Hwang, Eenjun. / Real-Time Facial Feature Extraction Scheme Using Cascaded Networks. 2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 IEEE International Conference on Big Data and Smart Computing, BigComp 2019 - Proceedings).

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Real-Time Facial Feature Extraction Scheme Using Cascaded Networks

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this