Facial Landmark Detection using Gaussian Guided Regression Network

Yongju Lee, Taeoh Kim, Taejae Jeon, Hanbyeol Bae, Sangyoun Lee

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Facial landmark detection is important prior information for other face alignment problems such as head pose estimation, facial emotion expression, and face modeling. Among the typical facial landmark detection algorithms, the TREE [1] algorithm which uses the cascaded regression method can detect facial landmark faster than the other algorithms using small training data. In this paper, we extract the Gaussian guided landmark map from the TREE and predict residual facial landmarks via landmark regression network. By using the Gaussian landmark feature map as prior information, the regression network effectively guides the direction of the refined landmarks on the 300W test dataset.

Original languageEnglish
Title of host publication34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728132716
DOIs
Publication statusPublished - 2019 Jun
Event34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019 - JeJu, Korea, Republic of
Duration: 2019 Jun 232019 Jun 26

Publication series

Name34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019

Conference

Conference34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019
CountryKorea, Republic of
CityJeJu
Period19/6/2319/6/26

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Electrical and Electronic Engineering
  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture

Cite this

Lee, Y., Kim, T., Jeon, T., Bae, H., & Lee, S. (2019). Facial Landmark Detection using Gaussian Guided Regression Network. In 34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019 [8793317] (34th International Technical Conference on Circuits/Systems, Computers and Communications, ITC-CSCC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITC-CSCC.2019.8793317