A more effective 3D-imaging system for Earth System Science and Navigation

3D image reconstruction or depth estimation is at the core of applications in navigation as well as Earth system science. Significant advances have been made in the field of computer vision to obtain 3D information from various types of cameras. Yet, these techniques still face limitations for a number of applications. In this project, the VITA (Prof. Alahi ) and EERL (Prof. Schmale) groups will pool their complementary skills to develop new machine-learning-based methods that can estimate depth from a large number of camera configurations, including from a novel 360° camera application. With their work, the teams will spearhead developments in the domain of 3D wave reconstruction and sea-ice classification, as well as autonomous navigation on water. iThe learning framework will be available as an open-source library that caters to the needs of many imaging applications.

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