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Titel:

Saliency based video quality prediction using multi-way data analysis

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz
Autor(en):
Redl, Arne; Keimel, Christian; Diepold, Klaus
Seitenangaben Beitrag:
188-193
Abstract:
Saliency information allows us to determine which parts of an image or video frame attracts the focus of the observer and thus where distortions will be more obvious. Using this knowledge and saliency thresholds, we therefore combine the saliency information generated by a computational model and the features extracted from the H.264/AVC bitstream, and use the resulting saliency-weighted features in the design of a video quality metric with multi-way data analysis. We used two different multi-wa...     »
Kongress- / Buchtitel:
Quality of Multimedia Experience (QoMEX), 2013 Fifth International Workshop on
Jahr:
2013
Monat:
Jul
Reviewed:
ja
Sprache:
en
Volltext / DOI:
doi:10.1109/QoMEX.2013.6603235
Semester:
SS 13
TUM Einrichtung:
Lehrstuhl für Datenverarbeitung
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