NDLI: A new approach using modified Hausdorff distances with eigenface for human face recognition

Content Provider	IEEE Xplore Digital Library
Author	Kwan-Ho Lin Kin-Man Lam Wan-Chi Siu
Copyright Year	2002
Description	Author affiliation: Dept. of Electron. & Inf. Eng., Hong Kong Polytech. Univ., China (Kwan-Ho Lin; Kin-Man Lam; Wan-Chi Siu)
Abstract	Hausdorff distance is an efficient measure of the similarity of two point sets. In this paper, we propose two new spatially weighted Hausdorff distance measures for human face recognition, namely, spatially eigen-weighted Hausdorff distance (SEWHD) and spatially eigen-weighted 'doubly' Hausdorff distance (SEW2HD). These new Hausdorff distances incorporate the information about the location of important facial features so that distances at those regions will be emphasized. The weighting function used in the Hausdorff distance measure is based on an eigenface, which has a large value at locations of important facial features and can reflect the face structure more effectively. Experimental results based on a combination of the ORL, MIT, and Yale face databases show that SEW2HD can achieve recognition rates of 83%, 90% and 92% for the first one, the first three and the first five likely matched faces, respectively, while the corresponding recognition rates of SEWHD are 80%, 83% and 88%, respectively.
Starting Page	980
Ending Page	984
File Size	486308
Page Count	5
File Format	PDF
ISBN	9810483643
DOI	10.1109/ICARCV.2002.1238557
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-12-02
Publisher Place	Singapore
Access Restriction	Subscribed
Rights Holder	Nanyang Technological Univ
Subject Keyword	Humans Face recognition Facial features Face detection Weight measurement Spatial databases Shape measurement Biomedical signal processing Electronic mail Anthropometry
Content Type	Text
Resource Type	Article

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

Human face recognition using a spatially weighted modified Hausdorff distance

Human face recognition using a spatially weighted Hausdorff distance

Efficient human face recognition based on shape and texture

Depth weighted modified hausdorff distance for range face recognition

An Automated Tool for Face Recognition using Visual Attention and Active Shape Models Analysis

Curvature based human face recognition using depth weighted Hausdorff distance

Face recognition using gender information

Eigenface Based Automatic Facial Feature Tagging

Human face recognition using Dempster-Shafer theory

A new approach using modified Hausdorff distances with eigenface for human face recognition

Similar Documents

Human face recognition using a spatially weighted modified Hausdorff distance

Human face recognition using a spatially weighted Hausdorff distance

Efficient human face recognition based on shape and texture

Depth weighted modified hausdorff distance for range face recognition

An Automated Tool for Face Recognition using Visual Attention and Active Shape Models Analysis

Curvature based human face recognition using depth weighted Hausdorff distance

Face recognition using gender information

Eigenface Based Automatic Facial Feature Tagging

Human face recognition using Dempster-Shafer theory

A new approach using modified Hausdorff distances with eigenface for human face recognition