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Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings Yes
Title Feature detection and tracking with the dynamic and active-pixel vision sensor (DAVIS)
Organization Unit
Authors
  • David Tedaldi
  • Guillermo Gallego
  • Elias Müggler
  • Davide Scaramuzza
Presentation Type paper
Item Subtype Original Work
Refereed Yes
Status Published in final form
Language
  • English
Event Title International Conference on Event-Based Control, Communication and Signal Processing (EBCCSP)
Event Type conference
Event Location Krakow
Event Start Date June 13 - 2016
Event End Date June 15 - 2016
Place of Publication Krakow, Poland
Publisher s.n.
Abstract Text Because standard cameras sample the scene at constant time intervals, they do not provide any information in the blind time between subsequent frames. However, for many high-speed robotic and vision applications, it is crucial to provide high-frequency measurement updates also during this blind time. This can be achieved using a novel vision sensor, called DAVIS, which combines a standard camera and an asynchronous event-based sensor in the same pixel array. The DAVIS encodes the visual content between two subsequent frames by an asynchronous stream of events that convey pixel-level brightness changes at microsecond resolution. We present the first algorithm to detect and track visual features using both the frames and the event data provided by the DAVIS. Features are first detected in the grayscale frames and then tracked asynchronously in the blind time between frames using the stream of events. To best take into account the hybrid characteristics of the DAVIS, features are built based on large, spatial contrast variations (i.e., visual edges), which are the source of most of the events generated by the sensor. An event-based algorithm is further presented to track the features using an iterative, geometric registration approach. The performance of the proposed method is evaluated on real data acquired by the DAVIS.
Related URLs
Digital Object Identifier 10.1109/EBCCSP.2016.7605086
Other Identification Number merlin-id:13506
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