CFP last date
20 January 2025
Call for Paper
February Edition
IJCA solicits high quality original research papers for the upcoming February edition of the journal. The last date of research paper submission is 20 January 2025

Submit your paper
Know more
The week's pick
Responsive image
SFLA-Based Line Balancing and Task Optimization in Master-Slave Controlled Hanger Transportation Systems for Garment Production

Duc Hoang Nguyen
Random Articles
Reseach Article

A Fusion based Approach of Face Detection using Viola - Jones and Skin Color Modeling Technique

by Nancy Goyal, Harsh Dev
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 119 - Number 9
Year of Publication: 2015
Authors: Nancy Goyal, Harsh Dev
10.5120/21094-3791

Nancy Goyal, Harsh Dev . A Fusion based Approach of Face Detection using Viola - Jones and Skin Color Modeling Technique. International Journal of Computer Applications. 119, 9 ( June 2015), 9-16. DOI=10.5120/21094-3791

@article{ 10.5120/21094-3791,
author = { Nancy Goyal, Harsh Dev },
title = { A Fusion based Approach of Face Detection using Viola - Jones and Skin Color Modeling Technique },
journal = { International Journal of Computer Applications },
issue_date = { June 2015 },
volume = { 119 },
number = { 9 },
month = { June },
year = { 2015 },
issn = { 0975-8887 },
pages = { 9-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume119/number9/21094-3791/ },
doi = { 10.5120/21094-3791 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:03:35.755635+05:30
%A Nancy Goyal
%A Harsh Dev
%T A Fusion based Approach of Face Detection using Viola - Jones and Skin Color Modeling Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 119
%N 9
%P 9-16
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Human computer interaction is dealing with different branches of learning that involves the interaction of human with machines directly. For an effective interaction between the machines and humans a user friendly and interactive interface needed. Automatic Face Detection and Recognition proves as a solution for that. Face is a physiological characteristic that indicates what we have in the mind by analyzing the facial expressions such as screaming, happiness and so on. The various factors such as identity, gender, expression, age and pose can be efficiently analyzed by observing the information contained a face. It is very easy for humans to recognize faces because human beings are very good in recognizing process, but it seems to be challenging for machines in the field of computer vision. Therefore, many researchers contribute their interest and attention in this emerging field. In this paper our focus on analyzing the existing faces detection techniques and combining some compatible techniques to form a model with improved efficiency and better detection rate.

References
  1. S. A. Sirohey, "Human Face Segmentation and Identification," Technical Report CS-TR-3176, Univ. of Maryland, 1993.
  2. H. P. Graf, T. Chen, E. Petajan, and E. Cosatto, "Locating Faces and Facial Parts," Proc. First Int'l Workshop Automatic Face and Gesture Recognition, pp. 41-46, 1995.
  3. K. C. Yow and R. Cipolla, "Feature-Based Human Face Detection, Image and Vision Computing," vol. 15, no. 9, pp. 713-735, 1997.
  4. M. F. Augusteijn and T. L. Skujca,"Identification of Human Faces through texture-based feature recognition and Neural Network Technology," Proc. IEEE Conf. Neural Networks, pp. 392-398, 1993.
  5. D. Chai and K. N. Ngan, "Locating Facial Region of a Head-and- Shoulders Color Image," Proc. Third Int'l Conf. Automatic Face and Gesture Recognition, pp. 124-129, 1998.
  6. K. Sobottka and I. Pitas, "Face Localization and Feature Extraction Based on Shape and Color Information," Proc. IEEE Int'l Conf Image Processing, pp. 483-486, 1996.
  7. I. Craw, H. Ellis, and J. Lishman, "Automatic Extraction of Face Features," Pattern Recognition Letters, vol. 5, pp. 183-187, 1987.
  8. A. Yuille, P. Hallinan, and D. Cohen, "Feature Extraction from Faces Using Deformable Templates," Int'l J. Computer Vision, vol. 8, no. 2, pp. 99-111, 1992.
  9. M. Kirby and L. Sirovich, "Application of the Karhunen-Loeve Procedure for the Characterization of Human Faces," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 12, no. 1, pp. 103-108, Jan 1990.
  10. M. Turk and A. Pentland, "Eigenfaces for Recognition," J. Cognitive Neuroscience, vol. 3, no. 1, pp. 71-86, 1991.
  11. T. Agui, Y. Kokubo, H. Nagashashi, and T. Nagao, "Extraction of Face Recognition from Monochromatic Photographs Using Neural Networks," Proc. Second Int'l Conf. Automation, Robotics, and Computer Vision, vol. 1, pp. 18. 8. 1-18. 8. 5, 1992.
  12. H. Rowley, S. Baluja, and T. Kanade, "Rotation Invariant Neural Network-Based Face Detection," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 38-44, 1998.
  13. E. Osuna, R. Freund, and F. Girosi, "Training Support Vector Machines: An Application to Face Detection," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp. 130-136, 1997.
  14. H. Schneiderman and T. Kanade, "A Statistical Method for 3D Object Detection Applied to Faces and Cars," Proc. IEEE Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 746-751, 2000.
  15. A. V. Nefian and M. H. H, "Face Detection and Recognition Using Hidden Markov Models," Proc. IEEE Int'l Conf. Image Processing vol. 1, pp. 141-146, 1998.
  16. Wilson, P. I. and Fernandez, "Facial Feature Detection using Haar Classifiers," JCSC 21, April 2006.
  17. Boblck, A. F. and Davis, J. W. , "The Recognition of Human Movement Using Temporal Templates," IEEE Trans. on PAMI vol. 23, pp. 257- 267, 2001.
  18. Essa, I. and Pentland, "Coding Analysis, Interpretation and Recognition of Facial Expressions," IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 7, pp. 757- 763, 1997.
  19. Park H. and Park J. I. , "Analysis and Recognition of Facial Expression Based on Point-wise Motion Energy," Springer Berlin/Heidelberg, vol. 3212, 2004.
  20. Nidhi Srivastava, Dr. Harsh Dev and S. Qamar Abbas, "Framework for Face Detection," International Journal of Computer Applications (0975 – 8887) Vol. 58– No. 17, November 2012.
Index Terms

Computer Science
Information Sciences

Keywords

Face Detection Face Recognition Computer-vision Illumination Feature and Image.

Powered by PhDFocusTM