Paper Info
Title
Salient Motion Features for Video Quality Assessment
Abstract
Design of algorithms that are able to estimate video quality as perceived by human observers is of interest for a number of applications. Depending on the video content, the artifacts introduced by the coding process can be more or less pronounced and diversely affect the quality of videos, as estimated by humans. While it is well understood that motion affects both human attention and coding quality, this relationship has only recently started gaining attention among the research community, when video quality assessment (VQA) is concerned. In this paper, the effect of calculating several objective measure features, related to video coding artifacts, separately for salient motion and other regions of the frames of the sequence is examined. In addition, we propose a new scheme for quality assessment of coded video streams, which takes into account salient motion. Standardized procedure has been used to calculate the Mean Opinion Score (MOS), based on experiments conducted with a group of non-expert observers viewing standard definition (SD) sequences. MOS measurements were taken for nine different SD sequences, coded using MPEG-2 at five different bit-rates. Eighteen different published approaches related to measuring the amount of coding artifacts objectively on a single-frame basis were implemented. Additional features describing the intensity of salient motion in the frames, as well as the intensity of coding artifacts in the salient motion regions were proposed. Automatic feature selection was performed to determine the subset of features most correlated to video quality. The results show that salient-motion-related features enhance prediction and indicate that the presence of blocking effect artifacts and blurring in the salient regions and variance and intensity of temporal changes in non-salient regions influence the perceived video quality.
Year
DOI
Venue
2011
10.1109/TIP.2010.2080279
IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Keywords
Field
DocType
account salient motion,quality assessment,salient motion features,video content,video stream,coding artifact,video quality,video coding artifact,video quality assessment,coding quality,salient motion,motion,saliency,computational modeling,pixel,mean opinion score,computer model,photography,regression tree,transform coding,algorithms,visualization
Computer vision,Pattern recognition,Computer science,Motion compensation,Image quality,Feature extraction,Coding (social sciences),Mean opinion score,Subjective video quality,Artificial intelligence,Video quality,Salient
Journal
Volume
Issue
ISSN
20
4
1941-0042
Citations 
PageRank 
References 
44
1.63
28
Authors
6
Name
Order
Citations
PageRank
Dubravko Culibrk127920.02
Milan Mirković2513.47
V. Zlokolica3492.55
Maja Pokric4675.07
Vladimir S. Crnojevic518617.82
Dragan D. Kukolj6512.71