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A Survey on Face Recognition Technology - Viola Jones Algorithm

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IJCA Proceedings on National Conference on “Recent Trends in Information Technology”
© 2016 by IJCA Journal
NCRTIT 2016 - Number 2
Year of Publication: 2016
Authors:
Ankur Sahitya
Manjunath T N
Veena N

Ankur Sahitya, Manjunath T N and Veena N. Article: A Survey on Face Recognition Technology - Viola Jones Algorithm. IJCA Proceedings on National Conference on Recent Trends in Information Technology NCRTIT 2016(2):33-38, August 2016. Full text available. BibTeX

@article{key:article,
	author = {Ankur Sahitya and Manjunath T N and Veena N},
	title = {Article: A Survey on Face Recognition Technology - Viola Jones Algorithm},
	journal = {IJCA Proceedings on National Conference on Recent Trends in Information Technology},
	year = {2016},
	volume = {NCRTIT 2016},
	number = {2},
	pages = {33-38},
	month = {August},
	note = {Full text available}
}

Abstract

Computer vision is gaining momentum towards variety of applications in recent days, in this context, we have done survey of face recognition technology and algorithms for the current trend applications. Here we describe 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. 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 highlighted, this work will help image accelerators, enhancements, filmy and military purposes.

References

  • Manisha V. Borkar, Bhakti Kurhade, A Research – Face Recognition by Using Near Set Theory, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 5, Issue 4, 2015 ISSN: 2277 128X.
  • Asit Kumar Datta, Madhura Datta, Pradipta Kumar Banerjee, Face Detection and Recognition: Theory and Practice, CRC Press, 28-Oct-2015.
  • White paper by Animetrics, Inc, Facial Recognition & Identity Resolution, 2012.
  • Paul Viola, Michael J. Jones, Robust Real-Time Face Detection, International Journal of Computer Vision 57(2), 2004.
  • Paul Viola, Michael J. Jones, Fast Multi-view Face Detection, Mitsubishi Electric Research Laboratories, TR2003-096, August 2003.
  • Henry A. Rowley, Shumeet Baluja, Takeo Kanade, Neural Network-Based Face Detection, IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume 20, Issue 1, Jan 1998. Digital Object Identifier 10. 1109/34. 655647.
  • Henry Schneiderman, Take o Kanade,A Statistical Method for 3D Object Detection Applied To Faces and Cars, IEEE Conference on ComputerVision and PatternRecognition 2000 proceedings, Volume1. Digital Object Identifier 10. 1109/CVPR. 2000. 855895.
  • Christopher M. Bishop,Pattern Recognition and Machine Learning, first edition, Springer 2006.
  • GaryB. Huang,Manu Ramesh,TamaraBerg,ErikLearned-Miller,LabeledFacesintheWild: A Database for Studying Face Recognition in Unconstrained Environments,University of Massachusetts,Amherst,TechnicalReport07-49,October2007.
  • Brian W. Kernighan, Dennis M. Ritchie, The C Programming Language, second edition, PrenticeHallSoftwareSeries,1988