NDLI: Facial landmarks detection using improved active shape model on android platform

Content Provider	Springer Nature Link
Author	Lee, Yong Hwan Kim, Cheong Ghil Kim, Youngseop Whangbo, Taeg Keun
Copyright Year	2013
Abstract	Detection of facial feature is fundamental for applications such as security, biometrics, 3D face modeling and personal authentication. Active Shape Model (ASM) is one of the most popular local texture models for face detection. This paper presents an issue related to face detection based on ASM, and proposes an efficient extraction algorithm for facial landmarks suitable for use on mobile devices. We modifies the original ASM to improve its performance with three changes; (1) Improving the initialization model using the center of the eyes by using a feature map of color information, (2) Constructing modified model definition and fitting more landmarks than the classical ASM, and (3) Extending and building a 2-D profile model for detecting faces in input image. The proposed method is evaluated on dataset containing over 700 images of faces, and experimental results reveal that the proposed algorithm exhibited a significant improvement of over 10.2 % in average success ratio, compared to the classic ASM, clearly outperforming on success rate and computing time.
Starting Page	8821
Ending Page	8830
Page Count	10
File Format	PDF
ISSN	13807501
Journal	Multimedia Tools and Applications
Volume Number	74
Issue Number	20
e-ISSN	15737721
Language	English
Publisher	Springer US
Publisher Date	2013-06-30
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Facial feature points Face analysis Active shape model (ASM) Facial landmarks Multimedia Information Systems Computer Communication Networks Data Structures, Cryptology and Information Theory Special Purpose and Application-Based Systems
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications Hardware and Architecture Software Media Technology

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