Event Location: Newell Simon Hall 1507

Abstract: There is much to benefit from 3D recovery of clouds and aerosol distributions, in high spatio-temporal resolution and wide coverage. Algorithms are developed for such tasks, including stereo triangulation (clouds) and tomography (aerosols). However, existing
remote sensing instruments may lack the spatio-temporal resolution desired to properly exploit these algorithms. There is a need to capture frequent samples of the atmospheric radiance field from many viewpoints. To help achieve this, we develop a new imaging system,
based on a wide, dense, scalable network of wide-angle cameras looking upward. The network uses low-cost units, to enable large scale deployment in the field. We demonstrate high-resolution 3D recovery of clouds based on data captured by a prototype system. We
use space carving to recover the volumetric distribution of clouds. This method leads directly to cloud shapes, bypassing surface triangulations that are based on image correspondence. Furthermore, network redundancy solves various radiometric problems
that exist in monocular or stereoscopic systems.

Work is joint with Dmitry Veikherman, Aviad Levis and Yoav Y. Schechner.