NDLI: Face detection with a Viola–Jones based hybrid network

Content Provider	IET Digital Library
Author	Murphy, Thomas M. Broussard, Randy Schultz, Robert Rakvic, Ryan Ngo, Hau
Abstract	Face detection is the determination of the positions and sizes of faces, primarily human, within digital images and videos, often as a component of a broader facial recognition system. It is seen as technologically mature, yet its operational performance typically remains sub-optimal, even within the less difficult frontal face detection tests. Empirical evidence shows that the Viola–Jones framework, a standard face detection solution with generally superior performance and other desirable properties, underdetects in some instances. Some true faces survive all but the final stages of the rejection cascade, resulting in missed faces. A hybrid framework consisting of a neural network following a truncated Viola–Jones cascade is constructed in an attempt to recover the undetected faces. Presumably, the neural network could fine tune and augment the face decision. Its inputs are a subset of the thresholding (detection) values of a rejection cascade's intermediate stages. Experiments reveal significantly improved performance, with increased detection rates if no false alarm increases are tolerated, with a greater detection rate increase if some false alarm increases are acceptable, and with a substantial false alarm reduction with no detection reduction. These improved face detection results could address shortcomings in widely-varying applications.
Starting Page	200
Ending Page	210
Page Count	11
ISSN	20474938
Volume Number	6
e-ISSN	20474946
Issue Number	Issue 3, May (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-bmt/6/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-bmt.2016.0037
Journal	IET Biometrics
Publisher Date	2016-12-06
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Computer Vision And Image Processing Technique Face Detection Face Recognition Facial Recognition System Image Recognition Neural Computing Technique Neural Nets Neural Network Viola-Jones Based Hybrid Network
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Vision and Pattern Recognition Software

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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