- Title
- QMET : A new quality assessment metric for no-reference video coding by using human eye traversal
- Creator
- Podder, Pallab; Paul, Manoranjan; Murshed, Manzur
- Date
- 2016
- Type
- Text; Conference proceedings
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/166132
- Identifier
- vital:13388
- Identifier
-
https://doi.org/10.1109/IVCNZ.2016.7804439
- Identifier
- ISBN:21512191 (ISSN); 9781509027484 (ISBN)
- Abstract
- The subjective quality assessment (SQA) is an ever demanding approach due to its in-depth interactivity to the human cognition. The addition of no-reference based scheme could equip the SQA techniques to tackle further challenges. Existing widely used objective metrics-peak signal-to-noise ratio (PSNR), structural similarity index (SSIM) or the subjective estimator-mean opinion score (MOS) requires original image for quality evaluation that limits their uses for the situation having no-reference. In this work, we present a no-reference based SQA technique that could be an impressive substitute to the reference-based approaches for quality evaluation. The High Efficiency Video Coding (HEVC) reference test model (HM15.0) is first exploited to generate five different qualities of the HEVC recommended eight class sequences. To assess different aspects of coded video quality, a group of ten participants are employed and their eye-tracker (ET) recorded data demonstrate closer correlation among gaze plots for relatively better quality video contents. Therefore, we innovatively calculate the amount of approximation of smooth eye traversal (ASET) by using distance, angle, and pupil-size feature from recorded gaze trajectory data and develop a new-quality metric based on eye traversal (QMET). Experimental results show that the quality evaluation carried out by QMET is highly correlated to the HM recommended coding quality. The performance of the QMET is also compared with the PSNR and SSIM metrics to justify the effectiveness of each other.; International Conference Image and Vision Computing New Zealand
- Publisher
- IEEE Computer Society
- Relation
- 2016 International Conference on Image and Vision Computing New Zealand, IVCNZ 2016; Palmerston North, New Zealand; 21st-22nd November 2016 p. 1-6
- Rights
- Copyright © 2016 IEEE.
- Rights
- This metadata is freely available under a CCO license
- Subject
- ASET; Eye-tracking; Eye-traversal; HEVC; QMET; Quality Assessment
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