We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 November 2024
Reseach Article

An Approach of Extracting Facial Components for Facial Expression Detection using Fiducial Point Detection

by Ashim Saha, Hillol Das, Nirmalya Kar, M C Pal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 80 - Number 10
Year of Publication: 2013
Authors: Ashim Saha, Hillol Das, Nirmalya Kar, M C Pal
10.5120/13901-1923

Ashim Saha, Hillol Das, Nirmalya Kar, M C Pal . An Approach of Extracting Facial Components for Facial Expression Detection using Fiducial Point Detection. International Journal of Computer Applications. 80, 10 ( October 2013), 49-53. DOI=10.5120/13901-1923

@article{ 10.5120/13901-1923,
author = { Ashim Saha, Hillol Das, Nirmalya Kar, M C Pal },
title = { An Approach of Extracting Facial Components for Facial Expression Detection using Fiducial Point Detection },
journal = { International Journal of Computer Applications },
issue_date = { October 2013 },
volume = { 80 },
number = { 10 },
month = { October },
year = { 2013 },
issn = { 0975-8887 },
pages = { 49-53 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume80/number10/13901-1923/ },
doi = { 10.5120/13901-1923 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:54:14.311616+05:30
%A Ashim Saha
%A Hillol Das
%A Nirmalya Kar
%A M C Pal
%T An Approach of Extracting Facial Components for Facial Expression Detection using Fiducial Point Detection
%J International Journal of Computer Applications
%@ 0975-8887
%V 80
%N 10
%P 49-53
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Facial Expression detection or Emotion Recognition is one of the rising fields of research on intelligent systems. Emotion plays a significant role in non-verbal communication. An efficient face and facial feature detection algorithms are required to detect emotion at that particular moment. The paperpresents a new approach to the problem of extracting the facial components from a still facial image which will be used further for Facial Expression detection. Robust extraction of such facial feature locations is a crucial problem which is used in a wide range of applications. Facial features such as lip corners, eye corners and nose tip are critical points in a human face. Thepaper approach relies on image segmentation based on skin color algorithm and fiducial point detection. First, the face region is extracted from the image by skin-color filter and window growing. Second, eyes and mouth are approximately located by projection of fiducial point. It is been observed for subjects not wearing glasses, the extraction of eyes could be correctly located in 94% of the images and in over 90% of these images they could be accurately extracted, while for subjects wearing glasses, the success rate is somewhat lower. Also, in certain moods or depending on the facial expression, the detection of lips in case of mouth opening and closing varies which can also be extracted by our method.

References
  1. M. Yang,D. J. Kriegman, N. Ahuja, Detecting faces inimages:asurvey, IEEE Transactions on Pattern Analysisand Machine Intelligence. 24(1)(2002)3458.
  2. WuH,ChenQ,YachidaM(1995),Anapplication offuzzy theory:facedetection. In: Proceedings of IWAFGR95 ,pp314319.
  3. Rowley HA, BalujaS, Kanade (1998) Neural network- based face detection. IEEE Trans Pattern Anal MachIntell20(1):2338.
  4. BhatiaN,KumarR,MenonS(2007)FIDA: face recognition usin gdescriptive inputsemantics,December14.
  5. Z. Liu,J. Yang,N. S. Peng, Anefficient face segmentation algorithm based on binary partition tree,Signal Processing: Image Communication20(4)(2005)295314.
  6. A. M. Tekalp, J. Ostermann Face and 2-Dmesh animation in MPEG-4, Signal Processing:Image Communication 15 (2000)387-421.
  7. M. Chuang,R. Chang and Y. Huang Automatic Facial Feature Extractionin Model-based Coding Journal of Information Science and Engineering16,447-458(2000).
  8. P. Ekman, Facial Expression and Emotion,"in America Pshychologist, vol. 48,no. 4,pp. 384-392,1993.
  9. D. Vukadinovic and M. Pantic, Fully automatic facial feature point detection using gabor feature based boosted classiers,In SMC05,pp. 1692-1698,2005
  10. F. Fleuret, D. Geman, Coarse-to-fine face detection, International Journal of Computer Vision41 (12)(2001)85107.
  11. L. Huang, A. Shimizu, Y. Hagihara, H. Kobatake, Gradient feature extraction for classification-based face detection, Pattern Recognition36(11)(2003)25012511.
  12. F. Tsalakanidou, S. Malassiotis ,M. G. Strintzis, Face localization and authentication using color and depth images, IEEE Transactions on Image Processing14(2)(2005)152168.
  13. M. Soriano, B. Martinkauppi, S. Huovinen, M. Laaksonen, Adaptiveskin color model ingusingtheskin locus for selecting training pixels, Pattern Recognition36 (3)(2003)681690.
  14. R. L. Hsu,M . Abdel-Mottaleb, A. K. Jain,Facedetectionin colorimages, IEEE Transactionson Pattern Analysis and MachineIntelligence24(5)(2002)696706.
  15. R. Xiao,M. Li,H. Zhang, Robust multipose face detection in images, IEEE Transactions on Circuits and Systems for Video Technology14(1)(2004)3141.
  16. C. Liu, ABayesian discriminating features method for face detection, IEEE Transactions on Pattern Analysis and Machine Intelligence25(6)(2003)725740.
  17. Y. Li,S. Gong,J. Sherrah ,H. Liddell, Support vector machine based multi-view face detection and recognition, Image and Vision Computing 22(5) (2004)413427.
  18. P. Viola, M. J. Jones, Robustreal-time face detection, International Journal of ComputerVision 57 (2) (2004) 137154.
  19. S. Phimoltares, C. Lursinsap, K. Chamnongthai, Locating essential facialfeatures using neural visua lmodel,in: Proceedings of the First IEEE International Conference on Machine Learning and Cybernetics, 2002, pp. 19141919.
Index Terms

Computer Science
Information Sciences

Keywords

Feature extraction fiducial point facial expression.