3-D Visual Discomfort Assessment Considering Optical and Neural Attention Models

Abstract

In this paper, we find factors affecting visual comfort along the visual pathways. The statistics data used for the 3D visual discomfort predictor (3D-VDP) model extracted from the traditional optical statistical elements derived, retinal disparity and neurophysiological elements obtained from V1 and MT areas. These physiological statistics are used to create a new feature map for 3D-VDP models, known as MT importance map. The thirteen typical MT neurons are divided into four kinds of cells: tuned-excitatory cells, tuned-inhibitory cells, far cells and near cells based on their characteristics. Disparity map is also transformed by changing the viewing distance in the formula to calculate the horizontal angular disparity factor. We propose that variation of viewing distance will make the MT cells more intense reaction. As a result, three types of angular disparity maps are obtained: tuned-near, tuned-far and original disparity maps. Preliminary results on two public available databases exhibit the performance of the proposed approach outperforms previous S3D VDP models.