A review on Face Detection and study of Viola Jones method

International Journal of Computer Trends and Technology (IJCTT)          
© 2015 by IJCTT Journal
Volume-25 Number-1
Year of Publication : 2015
Authors : Monali Chaudhari, Shanta sondur, Gauresh Vanjare
DOI :  10.14445/22312803/IJCTT-V25P110


Monali Chaudhari, Shanta sondur, Gauresh Vanjare "A review on Face Detection and study of Viola Jones method". International Journal of Computer Trends and Technology (IJCTT) V25(1):54-61, July 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
This paper describes the necessity and adopted methods to detect a human face. Since the data is computed by the computer, many algorithms are developed to detect a face. Some of the key challenges for the process of face detection are discussed. Four general face detection methods that are universally used are elaborated with their capabilities, advantages and disadvantages. A rapid approach to detect face developed by viola and jones is explained in brief. The 4 main concepts involved in the viola jones method such as haar features, integral image, Adaboost and classifier cascade are demonstrated.

[1] 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.
[2] 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.
[3] 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.
[4] G. Yang and T. S. Huang, ?Human Face Detection in Complex Background, Pattern Recognition, vol. 27, no. 1, pp. 53-63, 1994.
[5] 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.
[6] K.C. Yow and R. Cipolla, ?Feature-Based Human Face Detection, Image and Vision Computing, vol. 15, no. 9, pp. 713-735, 1997.
[7] J. Yang and A. Waibel, ?A Real-Time Face Tracker, Proc. Third Workshop Applications of Computer Vision, pp. 142- 147, 1996.
[8] 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
[9] R. Kjeldsen and J. Kender, ?Finding Skin in Color Images, Proc. Second Int’l Conf. Automatic Face and Gesture Recognition, pp. 312- 317, 1996.
[10] I. Craw, D. Tock, and A. Bennett, ?Finding Face Features, Proc. Second European Conf. Computer Vision, pp. 92-96, 1992
[11] 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.
[12] 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.
[13] 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.
[14] 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.
[15] Campadelli, Paola, Raffaella Lanzarotti, and Chiara Savazzi. "A feature-based face recognition system." Image Analysis and Processing, 2003. Proceedings. 12th International Conference on. IEEE, 2003.
[16] 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.
[17] Xiaowei Zhao, Xiujuan Chai ,"Context Constrained Facial Landmark Localization Based on Discontinuous Haar-like Feature" International Conference on Computer Vision (ICCV2013),2013.
[18] Paul Viola, Micheal Jones, "Rapid object detection using a Boosted Cascade of Simple features" CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION, 2001
[19] Lienhart and J. Maydt. An Extended Set of Haar-like Features for Rapid Object Detection. IEEE ICIP 2002
[20] Monali Chaudhari, Gauresh Vanjare, Dhairya Thakkar, Malay Shah and Amit Kadam, Intelligent Surveillance and Security System, Vol. 3, Issue 3, March 2015, pp. 2291- 2299.
[21] Cordiner, A.; Ogunbona, P.; Wanqing Li, "Face detection using generalised integral image features," Image Processing (ICIP), 2009 16th IEEE International Conference on , vol., no., pp.1229,1232, 7- 10 Nov. 2009.
[22] Ms.Drashti H. Bhatt , Mr.Kirit R. Rathod , Mr.Shardul J. Agravat. Article: A Study of Local Binary Pattern Method for Facial Expression Detection. International Journal of Computer Trends and Technology (IJCTT) 7(3):151-153, January 2014. Published by Seventh Sense Research Group.

Adaboost, Face detection, challenges, haar cascade.