- Title
- A novel quality metric using spatiotemporal correlational data of human eye maneuver
- Creator
- Podder, Pallab; Paul, Manoranjan; Murshed, Manzur
- Date
- 2017
- Type
- Text; Conference proceedings
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/166015
- Identifier
- vital:13389
- Identifier
-
https://doi.org/10.1109/DICTA.2017.8227396
- Identifier
- ISBN:9781538628393 (ISBN)
- Abstract
- The popularly used subjective estimator- mean opinion score (MOS) is often biased by the testing environment, viewers mode, domain expertise, and many other factors that may actively influence on actual assessment. We therefore, devise a no- reference subjective quality assessment metric by exploiting the nature of human eye browsing on videos. The participants' eye-tracker recorded gaze-data indicate more concentrated eye- traversing approach for relatively better quality. We calculate the Length, Angle, Pupil-size, and Gaze-duration features from the recorded gaze trajectory. The content and resolution invariant operation is carried out prior to synthesizing them using an adaptive weighted function to develop a new quality metric using eye traversal (QMET). Tested results reveal that the quality evaluation carried out by QMET demonstrates a strong correlation with the most widely used peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and the MOS.; DICTA 2017 - 2017 International Conference on Digital Image Computing: Techniques and Applications
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Relation
- 2017 International Conference on Digital Image Computing : Techniques and Applications, DICTA 2017; Sydney, Australia; 29th November-1st December 2017 Vol. 2017-December, p. 1-8
- Rights
- Copyright © 2017 IEEE.
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- Eye-traversal; Eye-tracking; Gaze-trajectory; HEVC; MOS; QMET; Quality assessment
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