Facial Keypoint Detection with Convolutional Neural Networks

Savina Colaco; Dong Seog Han

doi:10.1109/ICAIIC48513.2020.9065279

Facial Keypoint Detection with Convolutional Neural Networks

Savina Colaco, Dong Seog Han

School of Electronics Engineering

Kyungpook National University

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

11 Scopus citations

Abstract

Facial keypoint detection is a challenging problem in the field of computer vision. The keypoint detection is done by predicting the coordinates of certain facial features. In this paper, facial keypoint detection is predicted using convolutional neural networks. The models are trained to predict facial key points using the webcam input data. The facial keypoints includes eyebrow corners, nose tip, eye corners and center, and lip points. The predicted keypoints are mapped onto the webcam input data and compared with different models for better detection of keypoints. The mean square error is used to estimate the loss of each model.

Original language	English
Title of host publication	2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	671-674
Number of pages	4
ISBN (Electronic)	9781728149851
DOIs	https://doi.org/10.1109/ICAIIC48513.2020.9065279
State	Published - Feb 2020
Event	2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 - Fukuoka, Japan Duration: 19 Feb 2020 → 21 Feb 2020

Publication series

Name	2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020

Conference

Conference	2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020
Country/Territory	Japan
City	Fukuoka
Period	19/02/20 → 21/02/20

Keywords

convolutional neural network
facial keypoint detection

Access to Document

10.1109/ICAIIC48513.2020.9065279

Cite this

Colaco, S., & Han, D. S. (2020). Facial Keypoint Detection with Convolutional Neural Networks. In 2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 (pp. 671-674). Article 9065279 (2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICAIIC48513.2020.9065279

Colaco, Savina ; Han, Dong Seog. / Facial Keypoint Detection with Convolutional Neural Networks. 2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. pp. 671-674 (2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020).

@inproceedings{02eb19f7ba8248029ee5362f91edf94c,

title = "Facial Keypoint Detection with Convolutional Neural Networks",

abstract = "Facial keypoint detection is a challenging problem in the field of computer vision. The keypoint detection is done by predicting the coordinates of certain facial features. In this paper, facial keypoint detection is predicted using convolutional neural networks. The models are trained to predict facial key points using the webcam input data. The facial keypoints includes eyebrow corners, nose tip, eye corners and center, and lip points. The predicted keypoints are mapped onto the webcam input data and compared with different models for better detection of keypoints. The mean square error is used to estimate the loss of each model.",

keywords = "convolutional neural network, facial keypoint detection",

author = "Savina Colaco and Han, {Dong Seog}",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020 ; Conference date: 19-02-2020 Through 21-02-2020",

year = "2020",

month = feb,

doi = "10.1109/ICAIIC48513.2020.9065279",

language = "English",

series = "2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "671--674",

booktitle = "2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020",

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}

Colaco, S & Han, DS 2020, Facial Keypoint Detection with Convolutional Neural Networks. in 2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020., 9065279, 2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020, Institute of Electrical and Electronics Engineers Inc., pp. 671-674, 2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020, Fukuoka, Japan, 19/02/20. https://doi.org/10.1109/ICAIIC48513.2020.9065279

Facial Keypoint Detection with Convolutional Neural Networks. / Colaco, Savina; Han, Dong Seog.
2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020. Institute of Electrical and Electronics Engineers Inc., 2020. p. 671-674 9065279 (2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020).

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

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AU - Han, Dong Seog

PY - 2020/2

Y1 - 2020/2

N2 - Facial keypoint detection is a challenging problem in the field of computer vision. The keypoint detection is done by predicting the coordinates of certain facial features. In this paper, facial keypoint detection is predicted using convolutional neural networks. The models are trained to predict facial key points using the webcam input data. The facial keypoints includes eyebrow corners, nose tip, eye corners and center, and lip points. The predicted keypoints are mapped onto the webcam input data and compared with different models for better detection of keypoints. The mean square error is used to estimate the loss of each model.

AB - Facial keypoint detection is a challenging problem in the field of computer vision. The keypoint detection is done by predicting the coordinates of certain facial features. In this paper, facial keypoint detection is predicted using convolutional neural networks. The models are trained to predict facial key points using the webcam input data. The facial keypoints includes eyebrow corners, nose tip, eye corners and center, and lip points. The predicted keypoints are mapped onto the webcam input data and compared with different models for better detection of keypoints. The mean square error is used to estimate the loss of each model.

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U2 - 10.1109/ICAIIC48513.2020.9065279

DO - 10.1109/ICAIIC48513.2020.9065279

M3 - Conference contribution

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T3 - 2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020

SP - 671

EP - 674

BT - 2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020

Y2 - 19 February 2020 through 21 February 2020

ER -

Colaco S, Han DS. Facial Keypoint Detection with Convolutional Neural Networks. In 2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020. Institute of Electrical and Electronics Engineers Inc. 2020. p. 671-674. 9065279. (2020 International Conference on Artificial Intelligence in Information and Communication, ICAIIC 2020). doi: 10.1109/ICAIIC48513.2020.9065279

Facial Keypoint Detection with Convolutional Neural Networks

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