Precision enhancement of 3D surfaces from multiple quantized depth maps

Abstract

Transmitting from sender compressed texture and depth maps of multiple viewpoints enables image synthesis at receiver from any intermediate virtual viewpoint via depth-image-based rendering (DIBR). We observe that quantized depth maps from different viewpoints of the same 3D scene constitutes multiple descriptions (MD) of the same signal, thus it is possible to reconstruct the 3D scene in higher precision at receiver when multiple depth maps are considered jointly. In this paper, we cast the precision enhancement of 3D surfaces from multiple quantized depth maps as a combinatorial optimization problem. First, we derive a lemma that allows us to increase the precision of a subset of 3D points with certainty, simply by discovering special intersections of quantization bins (QB) from both views. Then, we identify the most probable voxel-containing QB intersections using a shortest-path formulation. Experimental results show that our method can significantly increase the precision of decoded depth maps compared with standard decoding schemes.