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Estimation of Virtual View Synthesis Distortion Toward Virtual View Position
Journal article   Peer reviewed

Estimation of Virtual View Synthesis Distortion Toward Virtual View Position

Lu Fang, Yijian Xiang, Ngai-Man Cheung and Feng Wu
IEEE transactions on image processing, Vol.25(5), pp.1961-1976
01/05/2016
PMID: 26978820

Abstract

Adaptation models Analytical models Cameras Distortion Image coding Linearity Three-dimensional displays
We propose an analytical model to estimate the depth-error-induced virtual view synthesis distortion (VVSD) in 3D video, taking the distance between reference and virtual views (virtual view position) into account. In particular, we start with a comprehensive preanalysis and discussion over several possible VVSD scenarios. Taking intrinsic characteristic of each scenario into consideration, we specifically classify them into four clusters: 1) overlapping region; 2) disocclusion and boundary region; 3) edge region; and 4) infrequent region. We propose to model VVSD as the linear combination of the distortion under different scenarios (DDSs) weighted by the probability under different scenarios (PDSs). We show analytically that DDS and PDS can be related to the virtual view position using quadratic/biquadratic models and linear models, respectively. Experimental results verify that the proposed model is capable of estimating the relationship between VVSD and the distance between reference and virtual views. Therefore, our model can be used to inform a reference view setup for capturing, or distortion at certain virtual view positions, when depth information is compressed.

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