FollowMe: Person following and gesture recognition with a quadrocopter - Naseer, Tayyab; Sturm, Jurgen; Cremers, Daniel (IEEE International Conference on Intelligent Robots and Systems, 2013)
In this paper, we present an approach that allows a quadrocopter to follow a person and to recognize simple gestures using an onboard depth camera. This enables novel applications such as hands-free filming and picture taking. The problem of tracking a person with an onboard camera however is highly challenging due to the self-motion of the platform. To overcome this problem, we stabilize the depth image by warping it to a virtual-static camera, using the estimated pose of the quadrocopter obtained from vision and inertial sensors using an Extended Kalman filter. We show that such a stabilized depth video is well suited to use with existing person trackers such as the OpenNI tracker. Using this approach, the quadrocopter not only obtains the position and orientation of the tracked person, but also the full body pose - which can then for example be used to recognize hand gestures to control the quadrocopter's behaviour. We implemented a small set of example commands ('follow me', 'take picture', 'land'), and generate corresponding motion commands. We demonstrate the practical performance of our approach in an extensive set of experiments with a quadrocopter. Although our current system is limited to indoor environments and small motions due to the restrictions of the used depth sensor, it indicates that there is large potential for such applications in the near future. © 2013 IEEE.
CRIS-Team Scopus Importer:2023-03-08