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Asynchronous Event-Based Binocular Stereo Matching

delete2012-02-01
delete121
PRE
AI
P
P. Rogister *
R
Ryad Benosman
S
Sio-Hoï Ieng
P
P. Lichtsteiner
T
Tobi Delbrück
DOI:10.1109/TNNLS.2011.2180025delete
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Abstract

Abstract

En 中文
We present a novel event-based stereo matching algorithm that exploits the asynchronous visual events from a pair of silicon retinas. Unlike conventional frame-based cameras, recent artificial retinas transmit their outputs as a continuous stream of asynchronous temporal events, in a manner similar to the output cells of the biological retina. Our algorithm uses the timing information carried by this representation in addressing the stereo-matching problem on moving objects. Using the high temporal resolution of the acquired data stream for the dynamic vision sensor, we show that matching on the timing of the visual events provides a new solution to the real-time computation of 3-D objects when combined with geometric constraints using the distance to the epipolar lines. The proposed algorithm is able to filter out incorrect matches and to accurately reconstruct the depth of moving objects despite the low spatial resolution of the sensor. This brief sets up the principles for further event-based vision processing and demonstrates the importance of dynamic information and spike timing in processing asynchronous streams of visual events.
Keywords:
Asynchronous acquisition
event-based vision
frameless vision
retinas
stereo vision
time impulse encoding
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

IEEE Transactions on Neural Networks and Learning Systems cover
IEEE Transactions on Neural Networks and Learning Systems
IF:
8.9
Papers:
7.6K
Citations:
7.2W

Organization

E
ETH Zurich
Scholars:
3.0W
Papers: 2.4W
Citations: 8.4W
S
swiss federal institutes of technology domain
Scholars:
9.0W
Papers: 8.0W
Citations: 163
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