Using region-of-interest for quality evaluation of DIBR-based view synthesis methods
As 3D media became more and more popular over the last years, new technologies are needed in the transmission, compression and creation of 3D content. One of the most commonly used techniques for aiding with the compression and creation of 3D content is known as view synthesis. The most effective class of view synthesis algorithms are using Depth-Image-Based-Rendering techniques, which use explicit scene geometry to render new views. However, these methods may produce geometrical distortions and localized artifacts which are difficult to evaluate as they are inherently different from encoding errors and they are perceived differently by human subjects. In this paper, we propose a region-of-interest evaluation technique for view synthesis based on DIBR methods. Based on the assumption that certain areas determined by the geometrical properties of the scene are prone to distortions, we select a ROI by analyzing the multiple DIBR methods together with the ground truth. The approach is tested using a subjective evaluation view synthesis database and show that our method improves the SSIM correlation with subjective scores We also test another similar method and traditional metrics.