Back to articles
Articles
Volume: 30 | Article ID: art00007
Image
Robust Convolutional Neural Network Cascade for Facial Landmark Localization Exploiting Training Data Augmentation
  DOI :  10.2352/ISSN.2470-1173.2018.10.IMAWM-374  Published OnlineJanuary 2018
Abstract

Facial landmark localization plays a critical role in many face analysis tasks. In this paper, we present a coarse-to-fine cascaded convolutional neural network system for robust facial landmark localization of faces in the wild. The system consists of two cascaded convolutional neural network levels. The first level network generates an initial prediction of all facial landmarks. The second level networks are cascaded to implement facial component-wise local refinement of the landmark points. We also present a novel data augmentation method for facial landmark localization networks training. The experiment result shows our method outperforms state-of-the-art methods on 300W [18] common dataset.

Subject Areas :
Views 18
Downloads 0
 articleview.views 18
 articleview.downloads 0
  Cite this article 

Ruiyi Mao, Qian Lin, Jan P. Allebach, "Robust Convolutional Neural Network Cascade for Facial Landmark Localization Exploiting Training Data Augmentationin Proc. IS&T Int’l. Symp. on Electronic Imaging: Imaging and Multimedia Analytics in a Web and Mobile World,  2018,  pp 374-1 - 374-5,  https://doi.org/10.2352/ISSN.2470-1173.2018.10.IMAWM-374

 Copy citation
  Copyright statement 
Copyright © Society for Imaging Science and Technology 2018
72010604
Electronic Imaging
2470-1173
Society for Imaging Science and Technology