Juan Vicente Talens-Noguera
ABSTRACT
Reliably predicting how humans assess video quality aspects remains an academic challenge, partly due to our limited understanding of human visual system and of how it affects the perception of spatial and temporal distortions. In current video chains, the perceived quality varies over time, depending on the compression level and video content. However, the impact of both factors on the extent of such variation is unknown, while this knowledge would be highly beneficial for video quality modeling. In this paper, a perception experiment is conducted with human observers rating the quality and meanwhile the extent of quality variation over time (QVT) for a set of video sequences. Preliminary results show that QVT tends to be less observed in the low and high quality regions; and that QVT seems to be sensitive to video content independent of compression level.
- Video Quality Experts Group. 2000. Final report from the Video Quality Experts Group on the validation of objective quality metrics for video quality assessment. DOI=http://www.its.bldrdoc.gov/vqeg/projects/frtv-phase-i/frtv-phase-i.aspxGoogle Scholar
- Hands, D. S., and Avons, S. E. 2001. Recency and duration neglect in subjective assessment of television picture quality. Applied Cognitive Psychology, 15: 639--657 (2001).Google ScholarCross Ref
- Chao, C., Choi, K. L., de Veciana, G., Caramanis, C., Heath, W., and Bovik, A. C. 2014. Modelling the Time-Varying Subjective Quality of HTTP Video Streams with Rate Adaptions. IEEE TIP, Vol.23, No.5.Google Scholar
- ITU-R Rec. BT.500--11, International Telecommunication Union, Geneva, Switzerland, 2002. Methodology for the Subjective Assessment of the Quality of Television Pictures.Google Scholar
- Pinson, M. H., and Wolf, S. 2009.DOI= http://www.cdvl.orgGoogle Scholar
- 2007. H.264/AVC software coordination. DOI= http://iphome.hhi.de/suehring/tmlGoogle Scholar
Index Terms
- Studying the Perceived Quality Variation over Time for Video Quality Assessment
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