Visual Odometry for Pixel Processor Arrays

Laurie Bose, Jianing Chen, Stephen J. Carey, Piotr Dudek, Walterio Mayol-Cuevas

    Research output: Chapter in Book/Conference proceedingConference contributionpeer-review

    Abstract

    We present an approach of estimating constrained ego-motion on a Pixel Processor Array (PPA). These devices embed processing and data storage capability into the pix-els of the image sensor, allowing for fast and low power parallel computation directly on the image-plane. Rather than the standard visual pipeline whereby whole images are transferred to an external general processing unit, our ap-proach performs all computation upon the PPA itself, with the camera's estimated motion as the only information out-put. Our approach estimates 3D rotation and a 1D scale-less estimate of translation. We introduce methods of im-age scaling, rotation and alignment which are performed solely upon the PPA itself and form the basis for conduct-ing motion estimation. We demonstrate the algorithms on a SCAMP-5 vision chip, achieving frame rates >1000Hz at ∼2W power consumption.
    Original languageEnglish
    Title of host publication2017 IEEE International Conference on Computer Vision (ICCV)
    PublisherIEEE
    Pages4614-4622
    ISBN (Print)978-1-5386-1032-9
    DOIs
    Publication statusPublished - Oct 2017

    Publication series

    Name2017 IEEE International Conference on Computer Vision (ICCV)

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