Depth map artefacts reduction: A review

Abstract

Depth maps are crucial for many visual applications, where they represent the positioning information of the objects in a three-dimensional scene. Usually, depth maps can be acquired via various devices, including Time of Flight, Kinect or light field camera, in practical applications. However, a brutal truth is that both intrinsic and extrinsic artefacts can be found in these depth maps which limits the prosperity of three-dimensional visual applications. In this study, the authors survey the depth map artefacts reduction methods proposed in the literature, from mono- to multi-view, via spatial to temporal dimension, in local to global manner, with signal processing to learning-based methods. They also compare the state-of-the-arts via different metrics to show their potentials in future visual applications.