The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Archives
  • Proposals

DOI: 10.14569/SpecialIssue.2011.010109
PDF

Component Localization in Face Alignment

Author 1: Yanyun Qu
Author 2: Tianzhu Fang
Author 3: Yanyun Cheng
Author 4: Han Liu

International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Image Processing and Analysis, 2011.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Face alignment is a significant problem in the processing of face image, and Active Shape Model (ASM) is a popular technology for this problem. However, the initiation of the alignment strongly affects the performance of ASM. If the initiation of alignment is bad, the iteration of ASM optimization will be stuck in a local minima, and the alignment will fail. In this paper, we propose a novel approach to improve ASM by building the classifiers of the face components. We design the SVM classifiers for eyes, mouth and nose, and we use Speeded Up Robust Features(SURF) and Local Binary Pattern(LBP) feature to describe the components which are discriminative for the components than Haar-like features. The face components are firstly located by the classifiers and they indicate the initiation of the alignment. Our approach can make the iterations of ASM optimization converge fast and with the less errors. We evaluate our approach on the frontal views of upright faces of IMM dataset. The experimental results have shown that our approach outperforms the original ASM in terms of efficiency and accuracy.

Keywords: face alignment; ASM; component localization; LBP; SURF

Yanyun Qu, Tianzhu Fang, Yanyun Cheng and Han Liu, “Component Localization in Face Alignment” International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Image Processing and Analysis, 2011. http://dx.doi.org/10.14569/SpecialIssue.2011.010109

@article{Qu2011,
title = {Component Localization in Face Alignment},
journal = {International Journal of Advanced Computer Science and Applications(IJACSA), Special Issue on Image Processing and Analysis}
doi = {10.14569/SpecialIssue.2011.010109},
url = {http://dx.doi.org/10.14569/SpecialIssue.2011.010109},
year = {2011},
publisher = {The Science and Information Organization},
volume = {1},
number = {1},
author = {Yanyun Qu and Tianzhu Fang and Yanyun Cheng and Han Liu},
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Upcoming Conferences

Computer Vision Conference (CVC) 2026

16-17 April 2026

  • Berlin, Germany

Healthcare Conference 2026

21-22 May 2025

  • Amsterdam, The Netherlands

Computing Conference 2025

19-20 June 2025

  • London, United Kingdom

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2025

6-7 November 2025

  • Munich, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org