Ofer Hadar

Senior Academic

No-Reference video quality assessment of H.264 video streams based on semantic saliency maps

H. Boujut, J. Benois-Pineau, T. Ahmed, O. Hadar, P. Bonnet

The paper contributes to No-Reference video quality assessment of broadcasted HD video over IP networks and DVB. In this work we have enhanced our bottom-up spatio-temporal saliency map model by considering semantics of the visual scene. Thus we propose a new saliency map model based on face detection that we called semantic saliency map. A new fusion method has been proposed to merge the bottom-up saliency maps with the semantic saliency map. We show that our NR metric WMBER weighted by the spatio-temporal-semantic saliency map provides higher results then the WMBER weighted by the bottom-up spatio-temporal saliency map. Tests are performed on two H.264/AVC video databases for video quality assessment over lossy networks.

Publication language English
Publication status Published - 13.02.2012
82930T

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering
Access to Document
10.1117/12.905379
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Link to publication in Scopus