A New Algorithm for Objective Video Quality Assessment on Eye Tracking Data

Maria Grazia Albanesi, Riccardo Amadeo

2014

Abstract

In this paper, we present an innovative algorithm based on a voting process approach, to analyse the data provided by an eye tracker during tasks of user evaluation of video quality. The algorithm relies on the hypothesis that a lower quality video is more “challenging” for the Human Visual System (HVS) than a high quality one, and therefore visual impairments influence the user viewing strategy. The goal is to generate a map of saliency of the human gaze on video signals, in order to create a No Reference objective video quality assessment metric. We consider the impairment of video compression (H.264/AVC algorithm) to generate different versions of video quality. We propose a protocol that assigns different playlists to different user groups, in order to avoid any effect of memorization of the visual stimuli on strategy. We applied our algorithm to data generated on a heterogeneous set of video clips, and the final result is the computation of statistical measures which provide a rank of the videos according to the perceived quality. Experimental results show that there is a strong correlation between the metric we propose and the quality of impaired video, and this fact confirms the initial hypothesis.

Paper Citation

in Harvard Style

Grazia Albanesi M. and Amadeo R. (2014). A New Algorithm for Objective Video Quality Assessment on Eye Tracking Data . In Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014) ISBN 978-989-758-003-1, pages 462-469. DOI: 10.5220/0004672104620469

in Bibtex Style

@conference{visapp14,
author={Maria Grazia Albanesi and Riccardo Amadeo},
title={A New Algorithm for Objective Video Quality Assessment on Eye Tracking Data},
booktitle={Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)},
year={2014},
pages={462-469},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004672104620469},
isbn={978-989-758-003-1},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 9th International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2014)
TI - A New Algorithm for Objective Video Quality Assessment on Eye Tracking Data
SN - 978-989-758-003-1
AU - Grazia Albanesi M.
AU - Amadeo R.
PY - 2014
SP - 462
EP - 469
DO - 10.5220/0004672104620469