NDLI: Survey on the approaches based geometric information for 3D face landmarks detection

Content Provider	IET Digital Library
Author	Manal, El Rhazi Arsalane, Zarghili Aicha, Majda
Abstract	Facial landmarks detection is an important and basic step in many face analysis applications. For this reason, it is considered a challenging task as the final results of the analysis depend on the accuracy of the landmarks detection. Decades of research have investigated approaches for two-dimensional (2D) facial landmarks detection but; however, the good obtained results, they still suffer from some weakness regarding the pose and illumination variations. Recently, the large availability of 3D scans makes the use of 3D face models easier hence, overcome the problems caused using 2D images. Many papers have studied the problem of 3D facial landmarks detection; nevertheless, there is a lack of literature reviews allowing an overview of the studies and researches related to the 3D face landmarks detection. In this study, the authors present a detailed survey of the latest (2010–2018) approaches based geometric information for 3D face landmarks detection, including the limitations and strengths of each work.
Starting Page	1225
Ending Page	1231
Page Count	7
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 8, Jun (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/8
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.6117
Journal	IET Image Processing
Publisher Date	2019-04-10
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	2D Facial Landmark Detection 2D Images 3D Face Landmark Detection 3D Face Models 3D Scans Computer Vision And Image Processing Technique Face Analysis Application Face Recognition Geometric Information Illumination Variations Image Recognition Object Detection Pose Variations Two-dimensional Facial Landmarks Detection
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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