Superresolution in 3D - Lidarboost

Thinking along the lines of our last year's CVPR contribution, we developed an algorithm - Lidarboost - that uses multiple shoots of the same scene to significantly enhance the quality of the 3D model of the scene. Based on a newly designed smoothness prior, we recover great details while keeping the level of noise down. To quantify the improvement, we not only show data captured with Swissranger SR3000 cameras, but also worked on synthetic data, where the gain in resolution is both visually and numerically exemplified. Download the pre-print along with some additional material here. Here's the poster we had on CVPR 2009 and our demo video:

Cite as:

@ARTICLE{schuon_lidarboost09,
title={LidarBoost: Depth Superresolution for ToF 3D Shape Scanning}, author={Schuon, Sebastian and Theobalt, Christian and Davis, James and Thrun, Sebastian},
journal={In Proc. of IEEE CVPR 2009}, year={2009}}

(This was joint work with Christian Theobalt, James Davis and Sebastian Thrun)

Motion Deblurring (revisited)

The previous work mon motion deblurring, namely comparing several methods with real captures images with well known properties has recently been accepted as a journal paper. Even though significant progress has been made since the paper was written in the field, the paper contains some good reference data, others might be interested to work with. They are available on the Motion Deblurring Page.

Cite as:

@ARTICLE{schuon_deblur09,
title={Comparison of Motion Deblur Algorithms and Real World Deployment},
author={Schuon, Sebastian and Diepold, Klaus},
journal={Acta Astronautica},
year={2009},
publisher={Elsevier}}