Multi-view Planarity Constraints for Skyline Estimation from UAV Images in City Scale Urban Environments

Ayyappa Swamy Thatavarthy    Tanu Sharma    Harshit Sankhla    Mukul Khanna    K. Madhava Krishna   

IIIT Hyderabad, India   

It is critical for aerial robots flying in city scale urban environments to make very quick estimates of a building depth with respect to itself. It should be done in a matter of few views to navigate itself, avoiding collisions with such a towering structure. As such, no one has attacked this problem. We bring together several modules combining deep learning and 3D vision to showcase a quick reconstruction in a few views. We exploit the inherent planar structure in the buildings (facades, windows) for this purpose. We evaluate the efficacy of our pipeline with various constraints and errors from multi-view geometry using ablation studies. We then retrieve the skyline of the buildings in synthetic as well as real-world scenes.