Computer vision for drones.

Friedrich Fraundorfer (TU Graz, Austria)

Abstract:

Drones are small scale flying robots and it is predicted that the drone market will see a major growth in the near future. Computer vision will play a major role in controlling and developing autonomous drones. In my talk I will give an overview of computer vision techniques that are used for drones in my lab. I will start by presenting IMU-assisted computer vision algorithms for ego-motion estimation, then talk about 3D reconstruction from drone imagery including semantic 3D and finally show application scenarios for drones that we developed.

Bio:

Friedrich Fraundorfer is Assistant Professor at Graz University of Technology, Austria since October 2014. He received the Ph.D. degree in computer science from TU Graz, Austria in 2006 working at the Institute of Computer Graphics and Vision headed by Franz Leberl and Horst Bischof. He had post-doc stays at the University of Kentucky (US), at the University of North Carolina at Chapel Hill (US) and at ETH Zürich (Switzerland). From 2012 to 2014 he acted as Deputy Director of the Chair of Remote Sensing Technology at the Faculty of Civil, Geo and Environmental Engineering at the Technische Universität München.

Friedrich Fraundorfer has been involved in multiple international and multinational research projects as project leader, investigator and collaborator, the EU project SFly (http://www.sfly.org/), a 4-year SNF project about autonomous micro UAV’s, the EU project VCHARGE (http://www.v-charge.eu/). Currently he acts as PI of an ongoing DACH project VMAV about autonomous micro UAV’s, as PI for the H2020 project SLIM (http://www.slim-project.eu/) and RESIST and as project leader for various industry collaborations. His main research areas are 3D Computer Vision, 3D Modeling, Robot Vision, Multi View Geometry, Visual-Inertial Fusion, Micro Aerial Vehicle, Autonomous Systems, Aerial Imaging, Image Analysis. He is the author of a well perceived two-part tutorial about visual odometry in the IEEE Robotics and Automation Magazine.