Proceedings ArticleDOI
Machine learning based modeling of spatial and temporal factors for video quality assessment
Manish Narwaria,Weisi Lin +1 more
- pp 2513-2516
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TLDR
It is shown that apart from their individual contributions, the interaction of the two factors also plays a role in determining the overall video quality.Abstract:
Unlike image quality, video quality is affected by the temporal factor, in addition to the spatial one. In this paper, we investigate into the impact of both the factors on the overall perceived video quality and combine them into a metric. We use machine learning as a tool to study and analyze the relationship between the factors and the overall perceived video quality. It is shown that apart from their individual contributions, the interaction of the two factors also plays a role in determining the overall video quality. We report the experimental results and the related analysis using videos from two publicly available databases.read more
Citations
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Saliency-Aware Video Compression
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Visual quality assessment : recent developments, coding applications and future trends
TL;DR: This work provides an in-depth review of recent developments in the field of visual quality assessment and puts equal emphasis on video quality databases and metrics as this is a less investigated area.
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Constructing a No-Reference H.264/AVC Bitstream-Based Video Quality Metric Using Genetic Programming-Based Symbolic Regression
Nicolas Staelens,Dirk Deschrijver,Ekaterina Vladislavleva,Brecht Vermeulen,Tom Dhaene,Piet Demeester +5 more
TL;DR: A novel no-reference bitstream-based objective video quality metric is presented that is constructed by genetic programming-based symbolic regression and shows that perceived quality can be modeled with high accuracy using only parameters extracted from the received video bitstream.
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A Hybrid QoS-QoE Estimation System for IPTV Service
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A fusion approach to video quality assessment based on temporal decomposition
TL;DR: This work decomposes an input video clip into multiple smaller intervals, measure the quality of each interval separately, and applies a fusion approach to integrating these scores into a final one to improve MOVIE and is also competitive with other state-of-the-art video quality metrics.
References
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Proceedings ArticleDOI
Multiscale structural similarity for image quality assessment
TL;DR: This paper proposes a multiscale structural similarity method, which supplies more flexibility than previous single-scale methods in incorporating the variations of viewing conditions, and develops an image synthesis method to calibrate the parameters that define the relative importance of different scales.
Journal ArticleDOI
A new standardized method for objectively measuring video quality
M.H. Pinson,S. Wolf +1 more
TL;DR: The independent test results from the VQEG FR-TV Phase II tests are summarized, as well as results from eleven other subjective data sets that were used to develop the NTIA General Model.
Journal ArticleDOI
Motion Tuned Spatio-Temporal Quality Assessment of Natural Videos
TL;DR: A general, spatio-spectrally localized multiscale framework for evaluating dynamic video fidelity that integrates both spatial and temporal aspects of distortion assessment and is found to be quite competitive with, and even outperform, algorithms developed and submitted to the VQEG FRTV Phase 1 study, as well as more recent VQA algorithms tested on this database.
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