Depth Map Quality Evaluation for Photographic Applications

As depth imaging is integrated into more and more consumer devices, manufacturers have to tackle new challenges. Applications such as computational bokeh and augmented reality require dense and precisely segmented depth maps to achieve good results. Modern devices use a multitude of different technologies to estimate depth maps, such as time-of-flight sensors, stereoscopic cameras, structured light sensors, phase-detect pixels or a combination thereof. Therefore, there is a need to evaluate the quality of the depth maps, regardless of the technology used to produce them. The aim of our work is to propose an end-result evaluation method based on a single scene, using a specifically designed chart. We consider the depth maps embedded in the photographs, which are not visible to the user but are used by specialized software, in association with the RGB pictures. Some of the aspects considered are spatial alignment between RGB and depth, depth consistency, and robustness to texture variations. This work also provides a comparison of perceptual and automatic evaluations.