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We propose a method which can perform real-time 3D reconstruction from a single hand-held event camera with no additional sensing, and works in unstructured scenes of which it has no prior knowledge. It is based on three decoupled probabilistic filters, each estimating 6-DoF camera motion, scene logarithmic (log) intensity gradient and scene inverse depth(More)
Hanme Kim1 hanme.kim@imperial.ac.uk Ankur Handa2 ah781@cam.ac.uk Ryad Benosman3 ryad.benosman@upmc.fr Sio-Hoi Ieng3 sio-hoi.ieng@upmc.fr Andrew J. Davison1 a.davison@imperial.ac.uk 1 Department of Computing, Imperial College London, London, UK 2 Department of Engineering, University of Cambridge, Cambridge, UK 3 INSERM, U968, Paris, F-75012, France;(More)
Event-based cameras (Figure 1) offer much potential to the fields of robotics and computer vision, in part due to their large dynamic range and extremely high “frame rates”. These attributes make them, at least in theory, particularly suitable for enabling tasks like navigation and mapping on high speed robotic platforms under challenging lighting(More)
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