Open Access   Article Go Back

Implementation of combined Viola-Jones and NPD Based Face Detection Algorithm

Ramakrishna B1 , M Sharmila Kumari2

Section:Research Paper, Product Type: Journal Paper
Volume-6 , Issue-6 , Page no. 1518-1522, Jun-2018

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v6i6.15181522

Online published on Jun 30, 2018

Copyright © Ramakrishna B B, M Sharmila Kumari . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

XML View
PDF Download

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: Ramakrishna B B, M Sharmila Kumari, “Implementation of combined Viola-Jones and NPD Based Face Detection Algorithm,” International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.1518-1522, 2018.

MLA Style Citation: Ramakrishna B B, M Sharmila Kumari "Implementation of combined Viola-Jones and NPD Based Face Detection Algorithm." International Journal of Computer Sciences and Engineering 6.6 (2018): 1518-1522.

APA Style Citation: Ramakrishna B B, M Sharmila Kumari, (2018). Implementation of combined Viola-Jones and NPD Based Face Detection Algorithm. International Journal of Computer Sciences and Engineering, 6(6), 1518-1522.

BibTex Style Citation:
@article{B_2018,
author = {Ramakrishna B B, M Sharmila Kumari},
title = {Implementation of combined Viola-Jones and NPD Based Face Detection Algorithm},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {6 2018},
volume = {6},
Issue = {6},
month = {6},
year = {2018},
issn = {2347-2693},
pages = {1518-1522},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=2377},
doi = {https://doi.org/10.26438/ijcse/v6i6.15181522}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v6i6.15181522}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=2377
TI - Implementation of combined Viola-Jones and NPD Based Face Detection Algorithm
T2 - International Journal of Computer Sciences and Engineering
AU - Ramakrishna B B, M Sharmila Kumari
PY - 2018
DA - 2018/06/30
PB - IJCSE, Indore, INDIA
SP - 1518-1522
IS - 6
VL - 6
SN - 2347-2693
ER -

VIEWS PDF XML
535 360 downloads 268 downloads
  
  
           

Abstract

Now a days video information is growing more and more widespread, their intelligent or automatic examining is becoming exceptionally important. People, i.e. human faces, are one of most common and very specific objects in video, which are tried to trace with help face detection tools. Face detection is a difficult task in image analysis which has each day more and more applications. In this paper we presented comparison of two face detection methods, which are commonly used. The Viola-Jones face detector is first reviewed and different techniques used in this algorithm to extract features are discussed. Secondly color based face detection approach is reviewed. In this paper, we implement Viola-Jons and Normalized pixel difference (NPD) detection methods. These algorithms are explained in brief. These face detection methods that are universally used are elaborated with their capabilities, advantages and disadvantages.

Key-Words / Index Term

Face detection, Viola-Jones face detector, Color Space, NPD, Adaboost, Feature Extraction

References

[1] Paul Viola, Michael J. Jones, Robust Real-Time Face Detection, International Journal of Computer Vision 57(2), 2004.
[2] Sanjay Kr. Singh1, D. S. Chauhan2, Mayank Vatsa3, Richa Singh3 A Robust Skin Color Based Face Detection Algorithm Tamkang Journal of Science and Engineering, Vol. 6, No. 4, pp. 227-234 (2003).
[3] Phung, S. L., Chai, D. K., & Bouzerdoum, A. (2001). Skin colour based face detection. Proceedings of 7th Australian and New Zealand Intelligent Information Systems Conference. (pp. 0). Australia. IEEE.
[4] Ragini Choudhury Verma, Cordelia Schmid, and KrystianMikolajczyk, ―Face Detection and Tracking in a Video by Propagating Detection Probabilities, ieee transactions on pattern analysis and machine intelligence, vol. 25, no. 10, october 2003.
[5] H.A. Rowley, S. Baluja, and T. Kanade, ―Neural Networks Based Face Detection, IEEE Trans. Pattern Analysis an Machine Intelligence, vol. 20, no. 1, pp. 22-38, Jan. 1998.
[6] K.K. Sung and T. Poggio, ―Example-Based Learning for View-Based Human Face Detection, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 1, pp. 39-51, Jan. 1998.
[7] J.-C. Terrillon, M. Shirazi, H. Fukamachi, and S. Akamatsu,―Comparative Performance of Different Skin Chrominance Models and Chrominance Spaces for the Automatic Detection of Human Faces in Color Images, Proc. Int‘l Conf. Automatic Face and Gesture Recognition, pp. 54-61, 2000.
[8] D. Decarlo and D. Metaxas, ―Deformable Model Based Face Shape and Motion Estimation, Proc. Int‘l Conf. Face and Gesture Recognition, 1996.
[9] G. Hager and K. Toyama, ―X Vision: A Portable Substrate for Real- Time Vision Applications,‖ Computer Vision and Image Understanding, vol. 69, no. 1, pp. 23-37, 1998.
[10] J. Yang and A. Waibel, ―Tracking Human Faces in Real Time,Technical Report CMU-CS-95-210, School of Computer Science, Carnegie Mellon Univ., Pittsburgh, Pa., 1995.
[11] J. P. Kapur, “Face Detection in Color Images,” University of Washington Department of Electrical Engineering, 1997. [Online]. Available: http://web.archive.org/web/20090723024922/http:/geocities.com/jaykapur/face.html. [Accessed 10 December 2013].
[12] Cahi, D. and Ngan, K. N., “Face Segmentation Using Skin-Color Map in Videophone Applications,” IEEE Transaction on Circuit and Systems for Video Technology, Vol. 9, pp. 551-564. 1999.
[13] Christopher M. Bishop, Pattern Recognition and Machine Learning, first edition, Springer 2006.
[14] Sanjay Kr. Singh, A Robust Skin Color Based Face Detection Algorithm, Tamkang Journal of Science and Engineering, Vol. 6, No. 4, pp. 227-234 (2003).
[15] Crowley, J. L. and Coutaz, J., “Vision for Man Machine Interaction,” Robotics and Autonomous Systems, Vol. 19, pp. 347-358 (1997).
[16] Hsu, Rein-Lien, Mohamed Abdel-Mottaleb, and Anil K. Jain."Face detection in color images." Pattern Analysis and Machine Intelligence, IEEE Transactions on 24.5 (2002):696-706.
[17] Hsu, Rein-Lien, Mohamed Abdel-Mottaleb, and Anil K. Jain. "Face detection in color images." Pattern Analysis and Machine Intelligence, IEEE Transactions on 24.5 (2002): 696-706.
[18] A.S. Georghiades, P.N. Belhumeur, D.J. Kriegman, From few to many: illumination cone models for face recognition under variable lighting and pose, IEEE Trans. Pattern Anal. Mach. Intell. 23 (6) (2001) 643–660.
[19] Mayank Chauha and Mukesh Sakle―Study & Analysis of Different Face Detection Techniques.‖ International Journal of Computer Science and Information Technologies, Vol. 5 (2), 2014, 1615-1618.
[20] G. Yang and T. S. Huang, ―Human Face Detection in Complex Background,‖ Pattern Recognition, vol. 27, no. 1, pp. 53-63, 1994.
[21] T.K. Leung, M.C. Burl, and P. Perona, ―Finding Faces in Cluttered Scenes Using Random Labeled Graph Matching, Proc. Fifth IEEE Int’l Conf. Computer Vision, pp. 637-644, 1995.
[22] K.C. Yow and R. Cipolla, ―Feature-Based Human Face Detection, Image and Vision Computing, vol. 15, no. 9, pp 713-735, 1997.
[23] J. Yang and A. Waibel, ―A Real-Time Face Tracker, Proc. Third Workshop Applications of Computer Vision, pp. 142-147, 1996.
[24] S. McKenna, S. Gong, and Y. Raja, ―Modelling Facial Colour and Identity with Gaussian Mixtures, Pattern Recognition, vol. 31, no. 12, pp. 1883-1892, 1998
[25] R. Kjeldsen and J. Kender, ―Finding Skin in Color Images, Proc. Second Int’l Conf. Automatic Face and Gesture Recognition, pp. 312- 317, 1996.
[26] I. Craw, D. Tock, and A. Bennett, ―Finding Face Features,Proc. Second European Conf. Computer Vision, pp. 92-96, 1992.
[27] A. Lanitis, C.J. Taylor, and T.F. Cootes, ―An Automatic Face Identification System Using Flexible Appearance Models, Image and Vision Computing, vol. 13, no. 5, pp. 393-401, 1995.
[28] H. Rowley, S. Baluja, and T. Kanade, Neural Network-Based Face Detection, IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 20, no. 1, pp. 23-38, Jan. 1998.
[29] Sharifara, Ali, et al. "A general review of human face detection including a study of neural networks and Haar feature-based cascade classifier in face detection." Biometrics and Security Technologies (ISBAST), 2014 International Symposium on. IEEE, 2014.
[30] Zhengming Li; Lijie Xue; Fei Tan, "Face detection in complex background based on skin color features and improved AdaBoost algorithms," Progress in Informatics and Computing (PIC), 2010 IEEE International Conference on ,vol.2, no., pp.723,727, 10-12 Dec. 2010.
[31] Yang, Ming-Hsuan, David J. Kriegman, and Narendra Ahuja. "Detecting faces in images: A survey." Pattern Analysis and Machine Intelligence, IEEE Transactions on 24.1 (2002): 34-58.
[32] Shengcai Liao, Anil K. Jain, and Stan Z. Li. “A Fast and Accurate Unconstrained Face Detector: IEEE transactions on pattern analysis and machine intelligence, vol. 38, no. pp.723,727, February 2016
[33] V. Jain and E. Learned-Miller, “FDDB: A benchmark for face detection in unconstrained settings,” Univ. Massachusetts, Amherst, MA, USA, Tech. Rep. UM-CS-2010-009, 2010.
[34] R. Lienhart and J. Maydt, “An extended set of Haar-like features for rapid object detection,” in Proc. IEEE Int. Conf. Image Process., 2002, pp. I-900–I-903.
[35] E. H. Weber, “Tastsinn und gemeingef€uhl,” in Handworterbuch der Physiologie, R. Wagner, Ed. Brunswick, Germany: Vieweg, 1846, pp. 481–588.
[36] M. Jones and P. Viola, “Fast multi-view face detection,” Mitsubishi Electric Res. Lab, Kendall Square, Cambridge, Massachusetts, Tech. Rep. TR-2003-96, 2003.
[37] J. Chen, S. Shan, C. He, G. Zhao, M. Pietik€ainen, X. Chen, and W. Gao, “WLD: A robust local image descriptor,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 32, no. 9, pp. 1705–1720, Sep. 2010.
[38] J. Friedman, T. Hastie, and R. Tibshirani, “Additive logistic regression: A statistical view of boosting,” The Ann. Statist., vol. 28, no. 2, pp. 337–374, Apr. 2000.