Hybrid no-reference video quality metric based on multiway PLSR
In real-life applications, no-reference metrics are more useful than full-reference metrics. To design such metrics, we apply data analysis methods to objectively measurable features and to data originating from subjective testing. Unfortunately, the information about temporal variation of quality i...
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 | 1248 |
---|---|
container_issue | |
container_start_page | 1244 |
container_title | |
container_volume | |
creator | Keimel, C. Habigt, J. Diepold, K. |
description | In real-life applications, no-reference metrics are more useful than full-reference metrics. To design such metrics, we apply data analysis methods to objectively measurable features and to data originating from subjective testing. Unfortunately, the information about temporal variation of quality is often lost due to the temporal pooling over all frames. Instead of using temporal pooling, we have recently designed a H.264/AVC bitstream no-reference video quality metric employing multiway Partial Least Squares Regression (PLSR), which leads to an improved prediction performance. In this contribution we will utilize multiway PLSR to design a hybrid metric that combines both bitstream-based features with pixel-based features. Our results show that the additional inclusion of the pixel-based features improves the quality prediction even further. |
format | Conference Proceeding |
fullrecord | <record><control><sourceid>ieee_6IE</sourceid><recordid>TN_cdi_ieee_primary_6334343</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><ieee_id>6334343</ieee_id><sourcerecordid>6334343</sourcerecordid><originalsourceid>FETCH-LOGICAL-i175t-dd7d0a2840cf1fa80632b0bb9233dfcfe3e6ed4469ffdcb463c36ecd7e588b733</originalsourceid><addsrcrecordid>eNpNjMtKAzEYRoMXsNY-gZu8QCDJn0kyK5GitjCgtLouufyByFw0M1Xm7S3owu8szuLAd0YWUoqaVaoW5-RaKG1AcG3ri3_hiqzG8Z2fZmUlJV-Qu83sS460H1jBhAX7gPQrRxzo59G1eZpph1PJgXo3YqRDT7tjO-VvN9OXZr-7IZfJtSOu_rwkb48Pr-sNa56ftuv7hmVhqonFaCJ30ioekkjOcg3Sc-9rCRBTSAioMSql65Ri8EpDAI0hGqys9QZgSW5_fzMiHj5K7lyZDxpAnYAfCpFGVw</addsrcrecordid><sourcetype>Publisher</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Hybrid no-reference video quality metric based on multiway PLSR</title><source>IEEE Electronic Library (IEL) Conference Proceedings</source><creator>Keimel, C. ; Habigt, J. ; Diepold, K.</creator><creatorcontrib>Keimel, C. ; Habigt, J. ; Diepold, K.</creatorcontrib><description>In real-life applications, no-reference metrics are more useful than full-reference metrics. To design such metrics, we apply data analysis methods to objectively measurable features and to data originating from subjective testing. Unfortunately, the information about temporal variation of quality is often lost due to the temporal pooling over all frames. Instead of using temporal pooling, we have recently designed a H.264/AVC bitstream no-reference video quality metric employing multiway Partial Least Squares Regression (PLSR), which leads to an improved prediction performance. In this contribution we will utilize multiway PLSR to design a hybrid metric that combines both bitstream-based features with pixel-based features. Our results show that the additional inclusion of the pixel-based features improves the quality prediction even further.</description><identifier>ISSN: 2219-5491</identifier><identifier>ISBN: 1467310689</identifier><identifier>ISBN: 9781467310680</identifier><identifier>EISSN: 2219-5491</identifier><language>eng</language><publisher>IEEE</publisher><subject>Feature extraction ; hybrid metric ; Measurement ; multilinear data analysis ; multiway PLSR ; no-reference metric ; Quality assessment ; trilinear PLS ; Vectors ; Video coding ; Video quality metric ; Visualization</subject><ispartof>2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO), 2012, p.1244-1248</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/6334343$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,780,784,789,790,2058,54920</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6334343$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Keimel, C.</creatorcontrib><creatorcontrib>Habigt, J.</creatorcontrib><creatorcontrib>Diepold, K.</creatorcontrib><title>Hybrid no-reference video quality metric based on multiway PLSR</title><title>2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)</title><addtitle>EUSIPCO</addtitle><description>In real-life applications, no-reference metrics are more useful than full-reference metrics. To design such metrics, we apply data analysis methods to objectively measurable features and to data originating from subjective testing. Unfortunately, the information about temporal variation of quality is often lost due to the temporal pooling over all frames. Instead of using temporal pooling, we have recently designed a H.264/AVC bitstream no-reference video quality metric employing multiway Partial Least Squares Regression (PLSR), which leads to an improved prediction performance. In this contribution we will utilize multiway PLSR to design a hybrid metric that combines both bitstream-based features with pixel-based features. Our results show that the additional inclusion of the pixel-based features improves the quality prediction even further.</description><subject>Feature extraction</subject><subject>hybrid metric</subject><subject>Measurement</subject><subject>multilinear data analysis</subject><subject>multiway PLSR</subject><subject>no-reference metric</subject><subject>Quality assessment</subject><subject>trilinear PLS</subject><subject>Vectors</subject><subject>Video coding</subject><subject>Video quality metric</subject><subject>Visualization</subject><issn>2219-5491</issn><issn>2219-5491</issn><isbn>1467310689</isbn><isbn>9781467310680</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpNjMtKAzEYRoMXsNY-gZu8QCDJn0kyK5GitjCgtLouufyByFw0M1Xm7S3owu8szuLAd0YWUoqaVaoW5-RaKG1AcG3ri3_hiqzG8Z2fZmUlJV-Qu83sS460H1jBhAX7gPQrRxzo59G1eZpph1PJgXo3YqRDT7tjO-VvN9OXZr-7IZfJtSOu_rwkb48Pr-sNa56ftuv7hmVhqonFaCJ30ioekkjOcg3Sc-9rCRBTSAioMSql65Ri8EpDAI0hGqys9QZgSW5_fzMiHj5K7lyZDxpAnYAfCpFGVw</recordid><startdate>201208</startdate><enddate>201208</enddate><creator>Keimel, C.</creator><creator>Habigt, J.</creator><creator>Diepold, K.</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201208</creationdate><title>Hybrid no-reference video quality metric based on multiway PLSR</title><author>Keimel, C. ; Habigt, J. ; Diepold, K.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-dd7d0a2840cf1fa80632b0bb9233dfcfe3e6ed4469ffdcb463c36ecd7e588b733</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Feature extraction</topic><topic>hybrid metric</topic><topic>Measurement</topic><topic>multilinear data analysis</topic><topic>multiway PLSR</topic><topic>no-reference metric</topic><topic>Quality assessment</topic><topic>trilinear PLS</topic><topic>Vectors</topic><topic>Video coding</topic><topic>Video quality metric</topic><topic>Visualization</topic><toplevel>online_resources</toplevel><creatorcontrib>Keimel, C.</creatorcontrib><creatorcontrib>Habigt, J.</creatorcontrib><creatorcontrib>Diepold, K.</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>Keimel, C.</au><au>Habigt, J.</au><au>Diepold, K.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Hybrid no-reference video quality metric based on multiway PLSR</atitle><btitle>2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO)</btitle><stitle>EUSIPCO</stitle><date>2012-08</date><risdate>2012</risdate><spage>1244</spage><epage>1248</epage><pages>1244-1248</pages><issn>2219-5491</issn><eissn>2219-5491</eissn><isbn>1467310689</isbn><isbn>9781467310680</isbn><abstract>In real-life applications, no-reference metrics are more useful than full-reference metrics. To design such metrics, we apply data analysis methods to objectively measurable features and to data originating from subjective testing. Unfortunately, the information about temporal variation of quality is often lost due to the temporal pooling over all frames. Instead of using temporal pooling, we have recently designed a H.264/AVC bitstream no-reference video quality metric employing multiway Partial Least Squares Regression (PLSR), which leads to an improved prediction performance. In this contribution we will utilize multiway PLSR to design a hybrid metric that combines both bitstream-based features with pixel-based features. Our results show that the additional inclusion of the pixel-based features improves the quality prediction even further.</abstract><pub>IEEE</pub><tpages>5</tpages></addata></record> |
fulltext | fulltext_linktorsrc |
identifier | ISSN: 2219-5491 |
ispartof | 2012 Proceedings of the 20th European Signal Processing Conference (EUSIPCO), 2012, p.1244-1248 |
issn | 2219-5491 2219-5491 |
language | eng |
recordid | cdi_ieee_primary_6334343 |
source | IEEE Electronic Library (IEL) Conference Proceedings |
subjects | Feature extraction hybrid metric Measurement multilinear data analysis multiway PLSR no-reference metric Quality assessment trilinear PLS Vectors Video coding Video quality metric Visualization |
title | Hybrid no-reference video quality metric based on multiway PLSR |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-26T19%3A20%3A28IST&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=Hybrid%20no-reference%20video%20quality%20metric%20based%20on%20multiway%20PLSR&rft.btitle=2012%20Proceedings%20of%20the%2020th%20European%20Signal%20Processing%20Conference%20(EUSIPCO)&rft.au=Keimel,%20C.&rft.date=2012-08&rft.spage=1244&rft.epage=1248&rft.pages=1244-1248&rft.issn=2219-5491&rft.eissn=2219-5491&rft.isbn=1467310689&rft.isbn_list=9781467310680&rft_id=info:doi/&rft_dat=%3Cieee_6IE%3E6334343%3C/ieee_6IE%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rft_ieee_id=6334343&rfr_iscdi=true |