A fast method of face detection in video images
Face detection is the basis of all the face processing system, while in video the face detection problem has a more special significance. By studying the face detection based on Adaboost algorithm, this paper presents a fast and good robust face detection method. Firstly, the motion region which con...
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| creator | Lijing Zhang Yingli Liang |
| description | Face detection is the basis of all the face processing system, while in video the face detection problem has a more special significance. By studying the face detection based on Adaboost algorithm, this paper presents a fast and good robust face detection method. Firstly, the motion region which contains faces is obtained based on motion detection, excluding the background interference. Secondly, Adaboost algorithm is used to detect the face in the motion region and locate the face. The experiments show that this method can rapidly and accurately detect human faces. |
| doi_str_mv | 10.1109/ICACC.2010.5486903 |
| format | Conference Proceeding |
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By studying the face detection based on Adaboost algorithm, this paper presents a fast and good robust face detection method. Firstly, the motion region which contains faces is obtained based on motion detection, excluding the background interference. Secondly, Adaboost algorithm is used to detect the face in the motion region and locate the face. The experiments show that this method can rapidly and accurately detect human faces.</description><identifier>ISBN: 1424458455</identifier><identifier>ISBN: 9781424458455</identifier><identifier>EISBN: 9781424458486</identifier><identifier>EISBN: 1424458471</identifier><identifier>EISBN: 9781424458479</identifier><identifier>EISBN: 142445848X</identifier><identifier>DOI: 10.1109/ICACC.2010.5486903</identifier><language>eng</language><publisher>IEEE</publisher><subject>Adaboost ; background subtraction ; Cameras ; Face detection ; Face recognition ; Gray-scale ; Humans ; Image motion analysis ; Monitoring ; Motion detection ; Real time systems ; Robustness ; video images</subject><ispartof>2010 2nd International Conference on Advanced Computer Control, 2010, Vol.4, p.490-494</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/5486903$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,27925,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/5486903$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Lijing Zhang</creatorcontrib><creatorcontrib>Yingli Liang</creatorcontrib><title>A fast method of face detection in video images</title><title>2010 2nd International Conference on Advanced Computer Control</title><addtitle>ICACC</addtitle><description>Face detection is the basis of all the face processing system, while in video the face detection problem has a more special significance. By studying the face detection based on Adaboost algorithm, this paper presents a fast and good robust face detection method. Firstly, the motion region which contains faces is obtained based on motion detection, excluding the background interference. Secondly, Adaboost algorithm is used to detect the face in the motion region and locate the face. The experiments show that this method can rapidly and accurately detect human faces.</description><subject>Adaboost</subject><subject>background subtraction</subject><subject>Cameras</subject><subject>Face detection</subject><subject>Face recognition</subject><subject>Gray-scale</subject><subject>Humans</subject><subject>Image motion analysis</subject><subject>Monitoring</subject><subject>Motion detection</subject><subject>Real time systems</subject><subject>Robustness</subject><subject>video images</subject><isbn>1424458455</isbn><isbn>9781424458455</isbn><isbn>9781424458486</isbn><isbn>1424458471</isbn><isbn>9781424458479</isbn><isbn>142445848X</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2010</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1j81KQzEQhSMiVOt9gbrJC9w2f5PkLsvFPyh0U9clZiYasb3SBMG3N2A9m-E7DHPmMLaQYimlGFbP43ocl0o0BuPtIPQF6wbnpVHGgG_WJbv5B4AZ60r5EE0GlPXymq3WPIVS-YHq-4R8Sg0jcaRKsebpyPORf2ekiedDeKNyy65S-CzUneecvTzc78anfrN9bM9s-iwd1B4hCpAaorPYsh0IGYV71WQ0GoeYhhRUSDaS8gjJe6WDbnsYoiEbhJ6zu7-7mYj2X6eWfvrZnzvqX8HfQ5I</recordid><startdate>201003</startdate><enddate>201003</enddate><creator>Lijing Zhang</creator><creator>Yingli Liang</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201003</creationdate><title>A fast method of face detection in video images</title><author>Lijing Zhang ; Yingli Liang</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-d5c05135c76d4457501c07b3e43d47ddf9fa2af6ce28d5f8823a3457dac4e6a03</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Adaboost</topic><topic>background subtraction</topic><topic>Cameras</topic><topic>Face detection</topic><topic>Face recognition</topic><topic>Gray-scale</topic><topic>Humans</topic><topic>Image motion analysis</topic><topic>Monitoring</topic><topic>Motion detection</topic><topic>Real time systems</topic><topic>Robustness</topic><topic>video images</topic><toplevel>online_resources</toplevel><creatorcontrib>Lijing Zhang</creatorcontrib><creatorcontrib>Yingli Liang</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>Lijing Zhang</au><au>Yingli Liang</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>A fast method of face detection in video images</atitle><btitle>2010 2nd International Conference on Advanced Computer Control</btitle><stitle>ICACC</stitle><date>2010-03</date><risdate>2010</risdate><volume>4</volume><spage>490</spage><epage>494</epage><pages>490-494</pages><isbn>1424458455</isbn><isbn>9781424458455</isbn><eisbn>9781424458486</eisbn><eisbn>1424458471</eisbn><eisbn>9781424458479</eisbn><eisbn>142445848X</eisbn><abstract>Face detection is the basis of all the face processing system, while in video the face detection problem has a more special significance. By studying the face detection based on Adaboost algorithm, this paper presents a fast and good robust face detection method. Firstly, the motion region which contains faces is obtained based on motion detection, excluding the background interference. Secondly, Adaboost algorithm is used to detect the face in the motion region and locate the face. The experiments show that this method can rapidly and accurately detect human faces.</abstract><pub>IEEE</pub><doi>10.1109/ICACC.2010.5486903</doi><tpages>5</tpages></addata></record> |
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| ispartof | 2010 2nd International Conference on Advanced Computer Control, 2010, Vol.4, p.490-494 |
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| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Adaboost background subtraction Cameras Face detection Face recognition Gray-scale Humans Image motion analysis Monitoring Motion detection Real time systems Robustness video images |
| title | A fast method of face detection in video images |
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