NDLI: Joint Boosting Feature Selection for Robust Face Recognition

Content Provider	IEEE Xplore Digital Library
Author	Rong Xiao Wujun Li Yuandong Tian Xiaoou Tang
Copyright Year	2006
Description	Author affiliation: Microsoft Research Asia, Beijing, 100080, P. R. China (Rong Xiao)
Abstract	A fundamental challenge in face recognition lies in determining what facial features are important for the identification of faces. In this paper, a novel face recognition framework is proposed to address this problem. In our framework, 3D face models are used to synthesize a huge database of realistic face images which covers wide appearance variations of faces due to various pose, illumination, and expression changes. A novel feature selection algorithm which we call Joint Boosting is developed to extract discriminative face features using this massive database. The major contributions of this paper are: (1) With the help of 3D face models, a massive database of realistic virtual face images is generated to achieve robust feature selection; (2)Because the huge database covers a wide range of face variations, our feature selection procedure only needs to be trained once, and the selected feature set can be generalized to other face database without re-training; (3) We propose a new learning algorithm, Joint Boosting Algorithm, which is effective and efficient in learning directly from a massive database without having to convert face images to intra-personal and extra-personal difference images. This property is important for applying our algorithm to other general pattern recognition problems. Experimental results show that our method significantly improves recognition performance.
Starting Page	1415
Ending Page	1422
File Size	450997
Page Count	8
File Format	PDF
ISBN	0769525970
ISSN	10636919
DOI	10.1109/CVPR.2006.159
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-06-17
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Boosting Robustness Face recognition Image databases Spatial databases Facial features Lighting Feature extraction Image generation Image converters
Content Type	Text
Resource Type	Article
Subject	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

Boosting Coded Dynamic Features for Facial Action Units and Facial Expression Recognition

Evaluation of 3D Facial Feature Selection for Individual Facial Model Identification

Robust Preprocessing Algorithm for Face Recognition

Robust face recognition under lighting variations

Exploring facial expressions with compositional features

A comparative evaluation of Average Face on holistic and local face recognition approaches

Robust Feature Set Matching for Partial Face Recognition

Facial expression recognition under illumination variation

Local feature analysis for robust face recognition

Joint Boosting Feature Selection for Robust Face Recognition

Similar Documents

Boosting Coded Dynamic Features for Facial Action Units and Facial Expression Recognition

Evaluation of 3D Facial Feature Selection for Individual Facial Model Identification

Robust Preprocessing Algorithm for Face Recognition

Robust face recognition under lighting variations

Exploring facial expressions with compositional features

A comparative evaluation of Average Face on holistic and local face recognition approaches

Robust Feature Set Matching for Partial Face Recognition

Facial expression recognition under illumination variation

Local feature analysis for robust face recognition

Joint Boosting Feature Selection for Robust Face Recognition