Precision Enhancement of 3D Surfaces from Multiple Compressed Depth Maps
This addresses the issue of reduced quality in 3D scene reconstruction for applications like virtual reality or 3D imaging, but it appears incremental as it builds on existing compression and projection techniques.
The paper tackled the problem of distortion in decoded depth maps from lossy compression by proposing a method that treats depth maps from multiple viewpoints as multiple descriptions of the same 3D scene, resulting in higher precision for the converged depth maps.
In texture-plus-depth representation of a 3D scene, depth maps from different camera viewpoints are typically lossily compressed via the classical transform coding / coefficient quantization paradigm. In this paper we propose to reduce distortion of the decoded depth maps due to quantization. The key observation is that depth maps from different viewpoints constitute multiple descriptions (MD) of the same 3D scene. Considering the MD jointly, we perform a POCS-like iterative procedure to project a reconstructed signal from one depth map to the other and back, so that the converged depth maps have higher precision than the original quantized versions.