Visual Odometry for Pixel Processor Arrays

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

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

13 Citations (Scopus)
306 Downloads (Pure)


We present an approach of estimating constrained egomotion on a Pixel Processor Array (PPA). These devices embed processing and data storage capability into the pixels 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 approach performs all computation upon the PPA itself, with the camera’s estimated motion as the only information output. Our approach estimates 3D rotation and a 1D scaleless estimate of translation. We introduce methods of image scaling, rotation and alignment which are performed solely upon the PPA itself and form the basis for conducting 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 International Conference on Computer Vision (ICCV 2017)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages8
ISBN (Electronic)9781538610329
ISBN (Print)9781538610336
Publication statusE-pub ahead of print - 25 Dec 2017
EventInternational Conference on Computer Vision - VENICE, Venice, Italy
Duration: 24 Oct 201727 Oct 2017

Publication series

ISSN (Print)2380-7504


ConferenceInternational Conference on Computer Vision
Abbreviated titleICCV


  • Visual Odometry
  • CPA
  • PPA
  • Vision Chip


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