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Type Book Chapter
Scope Discipline-based scholarship
Title Asynchronous, Photometric Feature Tracking Using Events and Frames
Organization Unit
Authors
  • Daniel Gehrig
  • Henri Rebecq
  • Guillermo Gallego
  • Davide Scaramuzza
Editors
  • Vittorio Ferrari
  • Martial Hebert
  • Cristian Sminchisescu
  • Yair Weiss
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • German
Booktitle Computer Vision – ECCV 2018
ISBN 978-3-030-01257-1
Number 11216
Place of Publication Cham
Publisher Springer
Page Range 766 - 781
Date 2018
Abstract Text We present a method that leverages the complementarity of event cameras and standard cameras to track visual features with low latency. Event cameras are novel sensors that output pixel-level brightness changes, called "events". They offer signicant advantages over standard cameras, namely a very high dynamic range, no motion blur, and a latency in the order of microseconds. However, because the same scene pattern can produce different events depending on the motion direction, establishing event correspondences across time is challenging. By contrast, standard cameras provide intensity measurements (frames) that do not depend on motion direction. Our method extracts features on frames and subsequently tracks them asynchronously using events, thereby exploiting the best of both types of data: the frames provide a photometric representation that does not depend on motion direction and the events provide low-latency updates. In contrast to previous works, which are based on heuristics, this is the first principled method that uses raw intensity measurements directly, based on a generative event model within a maximum-likelihood framework. As a result, our method produces feature tracks that are both more accurate (subpixel accuracy) and longer than the state of the art, across a wide variety of scenes.
Official URL http://rpg.ifi.uzh.ch/docs/ECCV18_Gehrig.pdf
Digital Object Identifier 10.1007/978-3-030-01258-8_46
Other Identification Number merlin-id:18692
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Additional Information 978-3-030-01258-8 (E)