The research and implementation of face detection and recognition based on video sequences
The detection and recognition of motive human face in video sequences is one of the international research hotspot currently. In order to achieve a face recognition system based on video, this paper used the method of difference in background images and the Kalman filter to track and extract the reg...
Gespeichert in:
Hauptverfasser: | , |
---|---|
Format: | Tagungsbericht |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext bestellen |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | V1-321 |
---|---|
container_issue | |
container_start_page | V1-318 |
container_title | |
container_volume | 1 |
creator | Qianqian Zhao Hualong Cai |
description | The detection and recognition of motive human face in video sequences is one of the international research hotspot currently. In order to achieve a face recognition system based on video, this paper used the method of difference in background images and the Kalman filter to track and extract the region of human body firstly, and then used the AdaBoost algorithm to detect human face in the region. Finally the improved Hidden Markov Model which is named as Pseudo-two-dimensional Hidden Markov Model was used for feature extraction and recognition in face image. In addition the effect of recognition was tested. |
doi_str_mv | 10.1109/ICFCC.2010.5497778 |
format | Conference Proceeding |
fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_5497778</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>5497778</ieee_id><sourcerecordid>5497778</sourcerecordid><originalsourceid>FETCH-LOGICAL-i90t-5f5f27278130f566f463bd591a979200a42e59a0534eeccc5ac5eddb677da77e3</originalsourceid><addsrcrecordid>eNpVkMFOwzAQRI0QEqjkB-DiH0hxbG8cH1FEoVIlLjlxqTb2mho1SYkDEn9PaHthL7tvtBqNhrG7QiyLQtiHdb2q66UUM4O2xpjqgmXWVIWWWkMllbr8x4W9ZllKH2IeDbIEuGFvzY74SIlwdDuOveexO-ypo37CKQ49HwIP6Ih7msgdlb-nkdzw3scjt5jI8_n4jp4Gnujzi3pH6ZZdBdwnys57wZrVU1O_5JvX53X9uMmjFVMOAYI0ck6pRICyDLpUrQdboDVWCoFaElgUoDSRcw7QAXnflsZ4NIbUgt2fbCMRbQ9j7HD82Z4LUb_VW1Ts</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>The research and implementation of face detection and recognition based on video sequences</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Qianqian Zhao ; Hualong Cai</creator><creatorcontrib>Qianqian Zhao ; Hualong Cai</creatorcontrib><description>The detection and recognition of motive human face in video sequences is one of the international research hotspot currently. In order to achieve a face recognition system based on video, this paper used the method of difference in background images and the Kalman filter to track and extract the region of human body firstly, and then used the AdaBoost algorithm to detect human face in the region. Finally the improved Hidden Markov Model which is named as Pseudo-two-dimensional Hidden Markov Model was used for feature extraction and recognition in face image. In addition the effect of recognition was tested.</description><identifier>ISBN: 9781424458219</identifier><identifier>ISBN: 1424458218</identifier><identifier>EISBN: 9781424458233</identifier><identifier>EISBN: 1424458242</identifier><identifier>EISBN: 1424458234</identifier><identifier>EISBN: 9781424458240</identifier><identifier>DOI: 10.1109/ICFCC.2010.5497778</identifier><language>eng</language><publisher>IEEE</publisher><subject>Face detection ; face detection and recognition ; Face recognition ; Feature extraction ; Filters ; Hidden Markov models ; Humans ; Image recognition ; Kalman filter ; Motion estimation ; P2D-HMM ; State estimation ; Video sequences</subject><ispartof>2010 2nd International Conference on Future Computer and Communication, 2010, Vol.1, p.V1-318-V1-321</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/5497778$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2051,27904,54898</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5497778$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Qianqian Zhao</creatorcontrib><creatorcontrib>Hualong Cai</creatorcontrib><title>The research and implementation of face detection and recognition based on video sequences</title><title>2010 2nd International Conference on Future Computer and Communication</title><addtitle>ICFCC</addtitle><description>The detection and recognition of motive human face in video sequences is one of the international research hotspot currently. In order to achieve a face recognition system based on video, this paper used the method of difference in background images and the Kalman filter to track and extract the region of human body firstly, and then used the AdaBoost algorithm to detect human face in the region. Finally the improved Hidden Markov Model which is named as Pseudo-two-dimensional Hidden Markov Model was used for feature extraction and recognition in face image. In addition the effect of recognition was tested.</description><subject>Face detection</subject><subject>face detection and recognition</subject><subject>Face recognition</subject><subject>Feature extraction</subject><subject>Filters</subject><subject>Hidden Markov models</subject><subject>Humans</subject><subject>Image recognition</subject><subject>Kalman filter</subject><subject>Motion estimation</subject><subject>P2D-HMM</subject><subject>State estimation</subject><subject>Video sequences</subject><isbn>9781424458219</isbn><isbn>1424458218</isbn><isbn>9781424458233</isbn><isbn>1424458242</isbn><isbn>1424458234</isbn><isbn>9781424458240</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVkMFOwzAQRI0QEqjkB-DiH0hxbG8cH1FEoVIlLjlxqTb2mho1SYkDEn9PaHthL7tvtBqNhrG7QiyLQtiHdb2q66UUM4O2xpjqgmXWVIWWWkMllbr8x4W9ZllKH2IeDbIEuGFvzY74SIlwdDuOveexO-ypo37CKQ49HwIP6Ih7msgdlb-nkdzw3scjt5jI8_n4jp4Gnujzi3pH6ZZdBdwnys57wZrVU1O_5JvX53X9uMmjFVMOAYI0ck6pRICyDLpUrQdboDVWCoFaElgUoDSRcw7QAXnflsZ4NIbUgt2fbCMRbQ9j7HD82Z4LUb_VW1Ts</recordid><startdate>201005</startdate><enddate>201005</enddate><creator>Qianqian Zhao</creator><creator>Hualong Cai</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201005</creationdate><title>The research and implementation of face detection and recognition based on video sequences</title><author>Qianqian Zhao ; Hualong Cai</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i90t-5f5f27278130f566f463bd591a979200a42e59a0534eeccc5ac5eddb677da77e3</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Face detection</topic><topic>face detection and recognition</topic><topic>Face recognition</topic><topic>Feature extraction</topic><topic>Filters</topic><topic>Hidden Markov models</topic><topic>Humans</topic><topic>Image recognition</topic><topic>Kalman filter</topic><topic>Motion estimation</topic><topic>P2D-HMM</topic><topic>State estimation</topic><topic>Video sequences</topic><toplevel>online_resources</toplevel><creatorcontrib>Qianqian Zhao</creatorcontrib><creatorcontrib>Hualong Cai</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>Qianqian Zhao</au><au>Hualong Cai</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>The research and implementation of face detection and recognition based on video sequences</atitle><btitle>2010 2nd International Conference on Future Computer and Communication</btitle><stitle>ICFCC</stitle><date>2010-05</date><risdate>2010</risdate><volume>1</volume><spage>V1-318</spage><epage>V1-321</epage><pages>V1-318-V1-321</pages><isbn>9781424458219</isbn><isbn>1424458218</isbn><eisbn>9781424458233</eisbn><eisbn>1424458242</eisbn><eisbn>1424458234</eisbn><eisbn>9781424458240</eisbn><abstract>The detection and recognition of motive human face in video sequences is one of the international research hotspot currently. In order to achieve a face recognition system based on video, this paper used the method of difference in background images and the Kalman filter to track and extract the region of human body firstly, and then used the AdaBoost algorithm to detect human face in the region. Finally the improved Hidden Markov Model which is named as Pseudo-two-dimensional Hidden Markov Model was used for feature extraction and recognition in face image. In addition the effect of recognition was tested.</abstract><pub>IEEE</pub><doi>10.1109/ICFCC.2010.5497778</doi></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISBN: 9781424458219 |
ispartof | 2010 2nd International Conference on Future Computer and Communication, 2010, Vol.1, p.V1-318-V1-321 |
issn | |
language | eng |
recordid | cdi_ieee_primary_5497778 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Face detection face detection and recognition Face recognition Feature extraction Filters Hidden Markov models Humans Image recognition Kalman filter Motion estimation P2D-HMM State estimation Video sequences |
title | The research and implementation of face detection and recognition based on video sequences |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-25T02%3A32%3A43IST&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=The%20research%20and%20implementation%20of%20face%20detection%20and%20recognition%20based%20on%20video%20sequences&rft.btitle=2010%202nd%20International%20Conference%20on%20Future%20Computer%20and%20Communication&rft.au=Qianqian%20Zhao&rft.date=2010-05&rft.volume=1&rft.spage=V1-318&rft.epage=V1-321&rft.pages=V1-318-V1-321&rft.isbn=9781424458219&rft.isbn_list=1424458218&rft_id=info:doi/10.1109/ICFCC.2010.5497778&rft_dat=%3Cieee_6IE%3E5497778%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&rft.eisbn=9781424458233&rft.eisbn_list=1424458242&rft.eisbn_list=1424458234&rft.eisbn_list=9781424458240&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=5497778&rfr_iscdi=true |