Logo image
Depth Error Induced Virtual View Synthesis Distortion Estimation for 3D Video Coding
Conference proceeding

Depth Error Induced Virtual View Synthesis Distortion Estimation for 3D Video Coding

Yijian Xiang, Lu Fang, Ren Li and Ngai-Man Cheung
DCC (Los Alamitos, Calif.), Vol.2015-, pp.313-322
IEEE Data Compression Conference
01/01/2015

Abstract

Computer Science Computer Science, Theory & Methods Imaging Science & Photographic Technology Science & Technology Technology
We propose an analytical model to estimate the depth-error-induced virtual view synthesis distortion (VVSD) in 3D video, taking into account the configuration of the cameras. Focusing on view synthesis under depth error, we carefully analyze the merging operations under different situations that affect pixel availability: overlapping region, disocclusion and boundary region, disparity error region, and infrequent region. The analysis leads to quadratic/biquadratic models and linear models that explicitly relate the distance between camera positions (reference/virtual view) to Distortion under Different Situations (DDS) and Probability under Different Situations (PDS), respectively. We also show that VVSD is the linear combination of DDS weighted by PDS. Our careful analysis results in state-of-theart estimation accuracy. Experimental results verify that the proposed model is capable to produce accurate estimates of VVSD based on the distance between reference/virtual views. Therefore, our model can effectively inform camera setup for capturing, in particular, the set-up of the cameras in situation where depth information will be compressed subsequently.

Metrics

1 Record Views

Details

Logo image