Abstract:

Currently, sharp discontinuities in depth and partial occlusions in multiview imaging systems pose serious challenges for many dense correspondence algorithms. However, it is important for 3D reconstruction methods to preserve depth edges as they correspond to important shampe features like silhouettes which are critical for understanding the structure of a scene. In this paper we show how active illumination algorithms can produce a rich set of feature maps that are useful in dense 3D reconstruction. We start by showing a method to compute a qualitative depth map from a single camera, which encodes object relative distances and can be used as a prior for stereo. In a multiview setup, we show that along with depth edges, binocular hal-occluded pixels can also be explicitly and reliably labeled. To demonstrate the usefulness of these feture maps, we show how they can be used in two different algorithms for dense stereo correspondence. Our experimental results how that our enhanced stereo algorithms are able to extract high quality, discontinuity preserving correspondence maps from scenes that are extremely challenging for conventional stereo methods.