Support vector regression based video quality prediction
Systems and methods of objective video quality measurement based on support vector machines. The video quality measurement systems can obtain information pertaining to features of a target training video, obtain corresponding information pertaining to features of a reference version of the target tr...
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| description | Systems and methods of objective video quality measurement based on support vector machines. The video quality measurement systems can obtain information pertaining to features of a target training video, obtain corresponding information pertaining to features of a reference version of the target training video, and employ the target training features and/or the reference training features to build video quality models using such support vector machines. Based on the target training features and/or the reference training features used to build such video quality models, the video quality models can be made to conform more closely to the human visual system. Moreover, using such video quality models in conjunction with target features of a target video whose perceptual quality is to be measured, and/or reference features of a reference video, the video quality measurement systems can be employed to predict measurements of the perceptual quality of such a target video with increased accuracy. |
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Moreover, using such video quality models in conjunction with target features of a target video whose perceptual quality is to be measured, and/or reference features of a reference video, the video quality measurement systems can be employed to predict measurements of the perceptual quality of such a target video with increased accuracy.</description><language>eng</language><subject>ELECTRIC COMMUNICATION TECHNIQUE ; ELECTRICITY ; PICTORIAL COMMUNICATION, e.g. TELEVISION ; TRANSMISSION</subject><creationdate>2014</creationdate><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20140812&DB=EPODOC&CC=US&NR=8804815B2$$EHTML$$P50$$Gepo$$Hfree_for_read</linktohtml><link.rule.ids>230,308,780,885,25563,76418</link.rule.ids><linktorsrc>$$Uhttps://worldwide.espacenet.com/publicationDetails/biblio?FT=D&date=20140812&DB=EPODOC&CC=US&NR=8804815B2$$EView_record_in_European_Patent_Office$$FView_record_in_$$GEuropean_Patent_Office$$Hfree_for_read</linktorsrc></links><search><creatorcontrib>WANG BEIBEI</creatorcontrib><creatorcontrib>ZOU DEKUN</creatorcontrib><title>Support vector regression based video quality prediction</title><description>Systems and methods of objective video quality measurement based on support vector machines. 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The video quality measurement systems can obtain information pertaining to features of a target training video, obtain corresponding information pertaining to features of a reference version of the target training video, and employ the target training features and/or the reference training features to build video quality models using such support vector machines. Based on the target training features and/or the reference training features used to build such video quality models, the video quality models can be made to conform more closely to the human visual system. Moreover, using such video quality models in conjunction with target features of a target video whose perceptual quality is to be measured, and/or reference features of a reference video, the video quality measurement systems can be employed to predict measurements of the perceptual quality of such a target video with increased accuracy.</abstract><oa>free_for_read</oa></addata></record> |
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| subjects | ELECTRIC COMMUNICATION TECHNIQUE ELECTRICITY PICTORIAL COMMUNICATION, e.g. TELEVISION TRANSMISSION |
| title | Support vector regression based video quality prediction |
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