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Sensors 2016, 16(4), 484; doi:10.3390/s16040484

Vision without the Image

Computation and Neural Systems, California Institute of Technology, 1200 E California Blvd, Pasadena, CA 91125, USA
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Author to whom correspondence should be addressed.
Academic Editor: Eric R. Fossum
Received: 2 February 2016 / Revised: 26 March 2016 / Accepted: 4 April 2016 / Published: 6 April 2016
(This article belongs to the Special Issue Photon-Counting Image Sensors)
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Abstract

Novel image sensors transduce the stream of photons directly into asynchronous electrical pulses, rather than forming an image. Classical approaches to vision start from a good quality image and therefore it is tempting to consider image reconstruction as a first step to image analysis. We propose that, instead, one should focus on the task at hand (e.g., detection, tracking or control) and design algorithms that compute the relevant variables (class, position, velocity) directly from the stream of photons. We discuss three examples of such computer vision algorithms and test them on simulated data from photon-counting sensors. Such algorithms work just-in-time, i.e., they complete classification, search and tracking with high accuracy as soon as the information is sufficient, which is typically before there are enough photons to form a high-quality image. We argue that this is particularly useful when the photons are few or expensive, e.g., in astronomy, biological imaging, surveillance and night vision. View Full-Text
Keywords: photon-counting sensors; visual recognition; low-light computer vision photon-counting sensors; visual recognition; low-light computer vision
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Chen, B.; Perona, P. Vision without the Image. Sensors 2016, 16, 484.

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