A 3D Perceptual Metric using Just-Noticeable-Difference
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Date
2005
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
The Eurographics Association
Abstract
In multimedia applications, it is essential to distribute resources efficiently among different types of data in order to optimize overall quality. We propose a perceptual metric using Just-Noticeable-Difference (JND) to identify redundant mesh data so that available bandwidth can be allocated to improve texture resolution. Evaluation of perceptual impact during runtime is based on statistics in a lookup table generated during preprocessing. If the impact is less than the JND, no mesh refinement is performed. We apply Weber s fraction to compute the JND threshold, which is verified by perceptual evaluations. Experimental result shows that our JND model can accurately predict perceptual impact based on the human visual system.
Description
@inproceedings{10.2312:egs.20051033,
booktitle = {EG Short Presentations},
editor = {John Dingliana and Fabio Ganovelli},
title = {{A 3D Perceptual Metric using Just-Noticeable-Difference}},
author = {Cheng, Irene and Boulanger, Pierre},
year = {2005},
publisher = {The Eurographics Association},
ISBN = {},
DOI = {10.2312/egs.20051033}
}