title: Vision without the Image.
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.
authors.affiliation: Computation and Neural Systems, California Institute of Technology, 1200 E California Blvd, Pasadena, CA 91125, USA. bchen3@caltech.edu.
authors.forename: Bo
authors.initials: B
authors.lastname: Chen
authors.affiliation: Computation and Neural Systems, California Institute of Technology, 1200 E California Blvd, Pasadena, CA 91125, USA. perona@caltech.edu.
authors.forename: Pietro
authors.initials: P
authors.lastname: Perona
keywords: low-light computer vision; photon-counting sensors; visual recognition