Subjective and objective quality assessment of Mobile Videos with In-Capture distortions

@article{Ghadiyaram2017SubjectiveAO,
  title={Subjective and objective quality assessment of Mobile Videos with In-Capture distortions},
  author={Deepti Ghadiyaram and Janice Pan and Alan C. Bovik and Anush K. Moorthy and Prasanjit Panda and Kai-Chieh Yang},
  journal={2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2017},
  pages={1393-1397}
}
We designed and created a new video database that models a variety of complex distortions generated during the video capturing process on hand-held mobile capturing devices. We describe the content and characteristics of the new database, which we call the LIVE Mobile In-Capture Video Quality Database. It comprises a total of 208 videos that were captured using eight different smart-phones and were affected by six common in-capture distortions. We also conducted a subjective video quality… CONTINUE READING

Figures, Tables, and Topics from this paper.

Explore Further: Topics Discussed in This Paper

Citations

Publications citing this paper.
SHOWING 1-6 OF 6 CITATIONS

Real-Time Quality Assessment of Videos from Body-Worn Cameras

VIEW 7 EXCERPTS
CITES METHODS & BACKGROUND
HIGHLY INFLUENCED

A Subjective and Objective Study of Stalling Events in Mobile Streaming Videos

How Video Object Tracking Is Affected by In-capture Distortions?

Learning a Continuous-Time Streaming Video QoE Model

VIEW 1 EXCERPT
CITES BACKGROUND

A no-reference video quality predictor for compression and scaling artifacts

VIEW 1 EXCERPT
CITES METHODS

References

Publications referenced by this paper.
SHOWING 1-10 OF 24 REFERENCES

CVD2014—A Database for Evaluating No-Reference Video Quality Assessment Algorithms

VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

Quality assessment of coded images using numerical category scaling

  • A. M. van Dijk, J.-B. Martens, A.B.Watson
  • Proc. SPIE Advanced Image and Video Communications and Storage Technologies, 1995.
  • 1995
VIEW 6 EXCERPTS
HIGHLY INFLUENTIAL

A Completely Blind Video Integrity Oracle

XGL Toolbox

  • J. S. Perry
  • [Online]. Available: https://github.com/jeffsp/xgl, 2015.
  • 2015
VIEW 1 EXCERPT

Blind Prediction of Natural Video Quality

VIEW 1 EXCERPT

Making a “Completely Blind” Image Quality Analyzer

VIEW 1 EXCERPT

Video Quality Assessment by Reduced Reference Spatio-Temporal Entropic Differencing

No-Reference Image Quality Assessment in the Spatial Domain

VIEW 1 EXCERPT