Loading…

Near Infrared Face Image Quality Assessment System of Video Sequences

In near infrared face recognition systems, situations including head rotation, motion blur, darkness, eyes closed, mouth opened and the small face region will deteriorate the recognition accuracy. Thus, it is necessary to design a quality assessment system to select the best frame from the input vid...

Full description

Saved in:
Bibliographic Details
Main Authors: Jianfeng Long, Shutao Li
Format: Conference Proceeding
Language:English
Subjects:
Online Access:Request full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by
cites
container_end_page 279
container_issue
container_start_page 275
container_title
container_volume
creator Jianfeng Long
Shutao Li
description In near infrared face recognition systems, situations including head rotation, motion blur, darkness, eyes closed, mouth opened and the small face region will deteriorate the recognition accuracy. Thus, it is necessary to design a quality assessment system to select the best frame from the input video sequence before face recognition or saving it to database. In this paper we present a scoring evaluation system based on five features including sharpness, brightness, resolution, head pose and expression. Firstly, the score of each feature is computed independently, and then the final quality score is obtained by combining the scores of five features with weights. Center for Biometrics and Security Research (CBSR) Near Infrared Face Dataset is used to test the system. The experiment results demonstrate the effectiveness of the proposed quality assessment.
doi_str_mv 10.1109/ICIG.2011.45
format conference_proceeding
fullrecord <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6005595</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6005595</ieee_id><sourcerecordid>6005595</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-b03e58886d78b5455d9603a9571e5bcce1e6160d2bfff179c0c86f80644244573</originalsourceid><addsrcrecordid>eNotj81Kw0AURkdEUGt27tzMC6Tem8ydn2UJbQ0URVrclklyRyJNqpl0kbc3oGfz7Q7fEeIRYYkI7rksyu0yA8SloiuROGPBaEeKFJprcY-KjEHSALciifELZrR2GeKdWL-yH2TZh8EP3MiNr1mWnf9k-X7xp3ac5CpGjrHjfpT7KY7cyXOQH23DZ7nnnwv3NccHcRP8KXLyvwtx2KwPxUu6e9uWxWqXtg7GtIKcyVqrG2Or-R01TkPuHRlkquqakTVqaLIqhIDG1VBbHSxopTI1N-QL8fSnbZn5-D20nR-m49xF5Cj_BWGtSYc</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Near Infrared Face Image Quality Assessment System of Video Sequences</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Jianfeng Long ; Shutao Li</creator><creatorcontrib>Jianfeng Long ; Shutao Li</creatorcontrib><description>In near infrared face recognition systems, situations including head rotation, motion blur, darkness, eyes closed, mouth opened and the small face region will deteriorate the recognition accuracy. Thus, it is necessary to design a quality assessment system to select the best frame from the input video sequence before face recognition or saving it to database. In this paper we present a scoring evaluation system based on five features including sharpness, brightness, resolution, head pose and expression. Firstly, the score of each feature is computed independently, and then the final quality score is obtained by combining the scores of five features with weights. Center for Biometrics and Security Research (CBSR) Near Infrared Face Dataset is used to test the system. The experiment results demonstrate the effectiveness of the proposed quality assessment.</description><identifier>ISBN: 1457715600</identifier><identifier>ISBN: 9781457715600</identifier><identifier>EISBN: 9780769545417</identifier><identifier>EISBN: 0769545416</identifier><identifier>DOI: 10.1109/ICIG.2011.45</identifier><language>eng</language><publisher>IEEE</publisher><subject>Brightness ; Face ; face quality assessment ; Face recognition ; Image resolution ; Mouth ; near infrared ; scoring evaluation system ; Video sequences</subject><ispartof>2011 Sixth International Conference on Image and Graphics, 2011, p.275-279</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6005595$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2056,27924,54919</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6005595$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Jianfeng Long</creatorcontrib><creatorcontrib>Shutao Li</creatorcontrib><title>Near Infrared Face Image Quality Assessment System of Video Sequences</title><title>2011 Sixth International Conference on Image and Graphics</title><addtitle>icig</addtitle><description>In near infrared face recognition systems, situations including head rotation, motion blur, darkness, eyes closed, mouth opened and the small face region will deteriorate the recognition accuracy. Thus, it is necessary to design a quality assessment system to select the best frame from the input video sequence before face recognition or saving it to database. In this paper we present a scoring evaluation system based on five features including sharpness, brightness, resolution, head pose and expression. Firstly, the score of each feature is computed independently, and then the final quality score is obtained by combining the scores of five features with weights. Center for Biometrics and Security Research (CBSR) Near Infrared Face Dataset is used to test the system. The experiment results demonstrate the effectiveness of the proposed quality assessment.</description><subject>Brightness</subject><subject>Face</subject><subject>face quality assessment</subject><subject>Face recognition</subject><subject>Image resolution</subject><subject>Mouth</subject><subject>near infrared</subject><subject>scoring evaluation system</subject><subject>Video sequences</subject><isbn>1457715600</isbn><isbn>9781457715600</isbn><isbn>9780769545417</isbn><isbn>0769545416</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2011</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNotj81Kw0AURkdEUGt27tzMC6Tem8ydn2UJbQ0URVrclklyRyJNqpl0kbc3oGfz7Q7fEeIRYYkI7rksyu0yA8SloiuROGPBaEeKFJprcY-KjEHSALciifELZrR2GeKdWL-yH2TZh8EP3MiNr1mWnf9k-X7xp3ac5CpGjrHjfpT7KY7cyXOQH23DZ7nnnwv3NccHcRP8KXLyvwtx2KwPxUu6e9uWxWqXtg7GtIKcyVqrG2Or-R01TkPuHRlkquqakTVqaLIqhIDG1VBbHSxopTI1N-QL8fSnbZn5-D20nR-m49xF5Cj_BWGtSYc</recordid><startdate>201108</startdate><enddate>201108</enddate><creator>Jianfeng Long</creator><creator>Shutao Li</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201108</creationdate><title>Near Infrared Face Image Quality Assessment System of Video Sequences</title><author>Jianfeng Long ; Shutao Li</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-b03e58886d78b5455d9603a9571e5bcce1e6160d2bfff179c0c86f80644244573</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Brightness</topic><topic>Face</topic><topic>face quality assessment</topic><topic>Face recognition</topic><topic>Image resolution</topic><topic>Mouth</topic><topic>near infrared</topic><topic>scoring evaluation system</topic><topic>Video sequences</topic><toplevel>online_resources</toplevel><creatorcontrib>Jianfeng Long</creatorcontrib><creatorcontrib>Shutao Li</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Jianfeng Long</au><au>Shutao Li</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Near Infrared Face Image Quality Assessment System of Video Sequences</atitle><btitle>2011 Sixth International Conference on Image and Graphics</btitle><stitle>icig</stitle><date>2011-08</date><risdate>2011</risdate><spage>275</spage><epage>279</epage><pages>275-279</pages><isbn>1457715600</isbn><isbn>9781457715600</isbn><eisbn>9780769545417</eisbn><eisbn>0769545416</eisbn><abstract>In near infrared face recognition systems, situations including head rotation, motion blur, darkness, eyes closed, mouth opened and the small face region will deteriorate the recognition accuracy. Thus, it is necessary to design a quality assessment system to select the best frame from the input video sequence before face recognition or saving it to database. In this paper we present a scoring evaluation system based on five features including sharpness, brightness, resolution, head pose and expression. Firstly, the score of each feature is computed independently, and then the final quality score is obtained by combining the scores of five features with weights. Center for Biometrics and Security Research (CBSR) Near Infrared Face Dataset is used to test the system. The experiment results demonstrate the effectiveness of the proposed quality assessment.</abstract><pub>IEEE</pub><doi>10.1109/ICIG.2011.45</doi><tpages>5</tpages></addata></record>
fulltext fulltext_linktorsrc
identifier ISBN: 1457715600
ispartof 2011 Sixth International Conference on Image and Graphics, 2011, p.275-279
issn
language eng
recordid cdi_ieee_primary_6005595
source IEEE Electronic Library (IEL) Conference Proceedings
subjects Brightness
Face
face quality assessment
Face recognition
Image resolution
Mouth
near infrared
scoring evaluation system
Video sequences
title Near Infrared Face Image Quality Assessment System of Video Sequences
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-12T19%3A41%3A44IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-ieee_6IE&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Near%20Infrared%20Face%20Image%20Quality%20Assessment%20System%20of%20Video%20Sequences&rft.btitle=2011%20Sixth%20International%20Conference%20on%20Image%20and%20Graphics&rft.au=Jianfeng%20Long&rft.date=2011-08&rft.spage=275&rft.epage=279&rft.pages=275-279&rft.isbn=1457715600&rft.isbn_list=9781457715600&rft_id=info:doi/10.1109/ICIG.2011.45&rft.eisbn=9780769545417&rft.eisbn_list=0769545416&rft_dat=%3Cieee_6IE%3E6005595%3C/ieee_6IE%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-i90t-b03e58886d78b5455d9603a9571e5bcce1e6160d2bfff179c0c86f80644244573%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6005595&rfr_iscdi=true