Depth map artefacts reduction: a review

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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.
Funding Information
  • National Natural Science Foundation of China (91848107, 61971203, 61571204)

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