Application of the Karhunen-Loeve procedure for the characterization of human faces

The use of natural symmetries (mirror images) in a well-defined family of patterns (human faces) is discussed within the framework of the Karhunen-Loeve expansion. This results in an extension of the data and imposes even and odd symmetry on the eigenfunctions of the covariance matrix, without incre...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on pattern analysis and machine intelligence 1990-01, Vol.12 (1), p.103-108
Main Authors: Kirby, M., Sirovich, L.
Format: Article
Language:English
Subjects:
Applied sciences
Artificial intelligence
Computer science
control theory
systems
Covariance matrix
Degradation
Eigenvalues and eigenfunctions
Exact sciences and technology
Face recognition
Humans
Linear regression
Mathematics
Mirrors
Neural networks
Pattern recognition. Digital image processing. Computational geometry
Speech
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c400t-1f3bbe7c2afa63e590149da3b459763843e1c49665beb1e6008582f4029893fe3
cites cdi_FETCH-LOGICAL-c400t-1f3bbe7c2afa63e590149da3b459763843e1c49665beb1e6008582f4029893fe3
container_end_page 108
container_issue 1
container_start_page 103
container_title IEEE transactions on pattern analysis and machine intelligence
container_volume 12
creator Kirby, M.
Sirovich, L.
description The use of natural symmetries (mirror images) in a well-defined family of patterns (human faces) is discussed within the framework of the Karhunen-Loeve expansion. This results in an extension of the data and imposes even and odd symmetry on the eigenfunctions of the covariance matrix, without increasing the complexity of the calculation. The resulting approximation of faces projected from outside of the data set onto this optimal basis is improved on average.< >
doi_str_mv 10.1109/34.41390
format article
fullrecord <record><control><sourceid>proquest_ieee_</sourceid><recordid>TN_cdi_ieee_primary_41390</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>41390</ieee_id><sourcerecordid>25825470</sourcerecordid><originalsourceid>FETCH-LOGICAL-c400t-1f3bbe7c2afa63e590149da3b459763843e1c49665beb1e6008582f4029893fe3</originalsourceid><addsrcrecordid>eNqF0E1LxDAQBuAgCq6r4NVbDyJeuk46aZocF_ELFzyo55JmJ7TSbWvSCvrrrdtlr57mMM-8DC9j5xwWnIO-QbEQHDUcsBnXqGNMUR-yGXCZxEol6pidhPABwEUKOGOvy66rK2v6qm2i1kV9SdGz8eXQUBOvWvqiqPOtpfXgKXKt3wJbGm9sT7762R-Ww8Y0kTOWwik7cqYOdLabc_Z-f_d2-xivXh6ebper2AqAPuYOi4IymxhnJFKqx5_02mAhUp1JVAKJW6GlTAsqOEkAlarECUi00ugI5-xqyh0__Bwo9PmmCpbq2jTUDiFPlFACUPwPx9xUZDDC6wla34bgyeWdrzbGf-cc8r96cxT5tt6RXu4yTbCmdt40tgp7L2UmOVcju5hYRUT77RTxC_zjgJQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>25825470</pqid></control><display><type>article</type><title>Application of the Karhunen-Loeve procedure for the characterization of human faces</title><source>IEEE Electronic Library (IEL) Journals</source><creator>Kirby, M. ; Sirovich, L.</creator><creatorcontrib>Kirby, M. ; Sirovich, L.</creatorcontrib><description>The use of natural symmetries (mirror images) in a well-defined family of patterns (human faces) is discussed within the framework of the Karhunen-Loeve expansion. This results in an extension of the data and imposes even and odd symmetry on the eigenfunctions of the covariance matrix, without increasing the complexity of the calculation. The resulting approximation of faces projected from outside of the data set onto this optimal basis is improved on average.&lt; &gt;</description><identifier>ISSN: 0162-8828</identifier><identifier>EISSN: 1939-3539</identifier><identifier>DOI: 10.1109/34.41390</identifier><identifier>CODEN: ITPIDJ</identifier><language>eng</language><publisher>Los Alamitos, CA: IEEE</publisher><subject>Applied sciences ; Artificial intelligence ; Computer science; control theory; systems ; Covariance matrix ; Degradation ; Eigenvalues and eigenfunctions ; Exact sciences and technology ; Face recognition ; Humans ; Linear regression ; Mathematics ; Mirrors ; Neural networks ; Pattern recognition. Digital image processing. Computational geometry ; Speech</subject><ispartof>IEEE transactions on pattern analysis and machine intelligence, 1990-01, Vol.12 (1), p.103-108</ispartof><rights>1990 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c400t-1f3bbe7c2afa63e590149da3b459763843e1c49665beb1e6008582f4029893fe3</citedby><cites>FETCH-LOGICAL-c400t-1f3bbe7c2afa63e590149da3b459763843e1c49665beb1e6008582f4029893fe3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/41390$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,4024,27923,27924,27925,54796</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=6676118$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Kirby, M.</creatorcontrib><creatorcontrib>Sirovich, L.</creatorcontrib><title>Application of the Karhunen-Loeve procedure for the characterization of human faces</title><title>IEEE transactions on pattern analysis and machine intelligence</title><addtitle>TPAMI</addtitle><description>The use of natural symmetries (mirror images) in a well-defined family of patterns (human faces) is discussed within the framework of the Karhunen-Loeve expansion. This results in an extension of the data and imposes even and odd symmetry on the eigenfunctions of the covariance matrix, without increasing the complexity of the calculation. The resulting approximation of faces projected from outside of the data set onto this optimal basis is improved on average.&lt; &gt;</description><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Covariance matrix</subject><subject>Degradation</subject><subject>Eigenvalues and eigenfunctions</subject><subject>Exact sciences and technology</subject><subject>Face recognition</subject><subject>Humans</subject><subject>Linear regression</subject><subject>Mathematics</subject><subject>Mirrors</subject><subject>Neural networks</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Speech</subject><issn>0162-8828</issn><issn>1939-3539</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1990</creationdate><recordtype>article</recordtype><recordid>eNqF0E1LxDAQBuAgCq6r4NVbDyJeuk46aZocF_ELFzyo55JmJ7TSbWvSCvrrrdtlr57mMM-8DC9j5xwWnIO-QbEQHDUcsBnXqGNMUR-yGXCZxEol6pidhPABwEUKOGOvy66rK2v6qm2i1kV9SdGz8eXQUBOvWvqiqPOtpfXgKXKt3wJbGm9sT7762R-Ww8Y0kTOWwik7cqYOdLabc_Z-f_d2-xivXh6ebper2AqAPuYOi4IymxhnJFKqx5_02mAhUp1JVAKJW6GlTAsqOEkAlarECUi00ugI5-xqyh0__Bwo9PmmCpbq2jTUDiFPlFACUPwPx9xUZDDC6wla34bgyeWdrzbGf-cc8r96cxT5tt6RXu4yTbCmdt40tgp7L2UmOVcju5hYRUT77RTxC_zjgJQ</recordid><startdate>199001</startdate><enddate>199001</enddate><creator>Kirby, M.</creator><creator>Sirovich, L.</creator><general>IEEE</general><general>IEEE Computer Society</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>199001</creationdate><title>Application of the Karhunen-Loeve procedure for the characterization of human faces</title><author>Kirby, M. ; Sirovich, L.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c400t-1f3bbe7c2afa63e590149da3b459763843e1c49665beb1e6008582f4029893fe3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1990</creationdate><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science; control theory; systems</topic><topic>Covariance matrix</topic><topic>Degradation</topic><topic>Eigenvalues and eigenfunctions</topic><topic>Exact sciences and technology</topic><topic>Face recognition</topic><topic>Humans</topic><topic>Linear regression</topic><topic>Mathematics</topic><topic>Mirrors</topic><topic>Neural networks</topic><topic>Pattern recognition. Digital image processing. Computational geometry</topic><topic>Speech</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kirby, M.</creatorcontrib><creatorcontrib>Sirovich, L.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>IEEE transactions on pattern analysis and machine intelligence</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kirby, M.</au><au>Sirovich, L.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Application of the Karhunen-Loeve procedure for the characterization of human faces</atitle><jtitle>IEEE transactions on pattern analysis and machine intelligence</jtitle><stitle>TPAMI</stitle><date>1990-01</date><risdate>1990</risdate><volume>12</volume><issue>1</issue><spage>103</spage><epage>108</epage><pages>103-108</pages><issn>0162-8828</issn><eissn>1939-3539</eissn><coden>ITPIDJ</coden><abstract>The use of natural symmetries (mirror images) in a well-defined family of patterns (human faces) is discussed within the framework of the Karhunen-Loeve expansion. This results in an extension of the data and imposes even and odd symmetry on the eigenfunctions of the covariance matrix, without increasing the complexity of the calculation. The resulting approximation of faces projected from outside of the data set onto this optimal basis is improved on average.&lt; &gt;</abstract><cop>Los Alamitos, CA</cop><pub>IEEE</pub><doi>10.1109/34.41390</doi><tpages>6</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0162-8828
ispartof IEEE transactions on pattern analysis and machine intelligence, 1990-01, Vol.12 (1), p.103-108
issn 0162-8828
1939-3539
language eng
recordid cdi_ieee_primary_41390
source IEEE Electronic Library (IEL) Journals
subjects Applied sciences
Artificial intelligence
Computer science
control theory
systems
Covariance matrix
Degradation
Eigenvalues and eigenfunctions
Exact sciences and technology
Face recognition
Humans
Linear regression
Mathematics
Mirrors
Neural networks
Pattern recognition. Digital image processing. Computational geometry
Speech
title Application of the Karhunen-Loeve procedure for the characterization of human faces
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-01T16%3A49%3A59IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_ieee_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Application%20of%20the%20Karhunen-Loeve%20procedure%20for%20the%20characterization%20of%20human%20faces&rft.jtitle=IEEE%20transactions%20on%20pattern%20analysis%20and%20machine%20intelligence&rft.au=Kirby,%20M.&rft.date=1990-01&rft.volume=12&rft.issue=1&rft.spage=103&rft.epage=108&rft.pages=103-108&rft.issn=0162-8828&rft.eissn=1939-3539&rft.coden=ITPIDJ&rft_id=info:doi/10.1109/34.41390&rft_dat=%3Cproquest_ieee_%3E25825470%3C/proquest_ieee_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c400t-1f3bbe7c2afa63e590149da3b459763843e1c49665beb1e6008582f4029893fe3%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=25825470&rft_id=info:pmid/&rft_ieee_id=41390&rfr_iscdi=true