AR3WS · Acquiring and Responding to the 3D World, Smartly

Recent advances in sensors and imaging systems have greatly simplified scanning and acquisition both in terms of setup cost and acquisition times. As scanners and sensors become ubiquitous, efficient registration of multi-modal sensor inputs (e.g., images, 3D scans, depth scans), suitably representing them, and most importantly the ability to automatically reason and efficiently interact with the acquired data becomes crucial for enabling a smart world. We propose advances to all the stages of such a digital shape acquisition and analysis pipeline preparing us with tools necessary for appropriate use the stream of 3D content that is to follow in next years. More specifically, we propose to: (i) develop algorithms to efficiently combine photographs and 3D LiDAR scans for large scale acquisitions ranging from facades to city blocks, (ii) support analysis of the acquired scenes with man-made objects (e.g., mechanical parts and assemblies) to reveal underlying data decomposition and relations such as coplanarity, orthogonality, symmetry, regularity, etc., and (iii) use the extracted relations to support interactive navigation of the scenes for detecting damaged scene parts, plan building modifications and predicting possible functions of the individual segmented parts. The work will have direct applications in surveillance for assisted living, disaster management, emergency response, city planning, and also towards archival of historical data, digital restoration, and understanding of natural geometric growth processes.