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  Real-Time Video Stabilization for UAVs Based Only on IMU Data

Odelga, M., Kochanek, N., & Bülthoff, H. (2017). Real-Time Video Stabilization for UAVs Based Only on IMU Data. Poster presented at IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017), Vancouver, BC, Canada.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0000-C411-F Version Permalink: http://hdl.handle.net/21.11116/0000-0000-C412-E
Genre: Poster

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Odelga, M1, 2, 3, Author              
Kochanek, N2, 3, Author              
Bülthoff, HH2, 3, 4, Author              
Affiliations:
1Project group: Autonomous Robotics & Human-Machine Systems, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528704              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
3Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497797              
4Project group: Cybernetics Approach to Perception & Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_2528701              

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 Abstract: With improved batteries, motors, and rapidly falling prices, UAV have become increasingly popular for both military and civil applications. While some unmanned aerial vehicles (UAV) have the capacity to carry mechanically stabilized camera equipment, weight limits or other problems may make mechanical stabilization impractical, and so many UAV rely on fixed cameras to provide a video stream to an operator or observer. With a fixed camera, the video stream often shakes from quadrotor movement due to wind, and can change by large amounts from the quadrotor tilting to accelerate. For a human observer, unwanted movement may simply make it harder to follow the video, while for computer algorithms, this movement may severely impair the algorithm's intended function. The logical solution to stabilization of video from UAV is digital stabilization. Though many algorithms exist for digital stabilization of UAV video they all rely on feature tracking methods, or merge feature tracking with inertial measurement unit (IMU) data to stabilize the video feed. We, however, propose an algorithm for the digital stabilization of video that uses only data from a UAV’s IMU to stabilize the video feed in real time.

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 Dates: 2017-09-25
 Publication Status: Published in print
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 Identifiers: BibTex Citekey: OdelgaKB2017
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Title: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017)
Place of Event: Vancouver, BC, Canada
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Title: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017)
Source Genre: Proceedings
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