Focus on visual rendering quality through content-based depth map coding

Multi-view video plus depth (MVD) data is a set of multiple sequences capturing the same scene at different viewpoints, with their associated per-pixel depth value. Overcoming this large amount of data requires an effective coding framework. Yet, a simple but essential question refers to the means assessing the proposed coding methods. While the challenge in compression is the optimization of the rate-distortion ratio, a widely used objective metric to evaluate the distortion is the Peak-Signal-to-Noise-Ratio (PSNR), because of its simplicity and mathematically easiness to deal with such purposes. This paper points out the problem of reliability, concerning this metric, when estimating 3D video codec performances. We investigated the visual performances of two methods, namely H.264/MVC and Locally Adaptive Resolution (LAR) method, by encoding depth maps and reconstructing existing views from those degraded depth images. The experiments revealed that lower coding efficiency, in terms of PSNR, does not imply a lower rendering visual quality and that LAR method preserves the depth map properties correctly.