Estimating heading direction from monocular video sequences using biologically-based sensors

M. J. Cree, J. A. Perrone, G. Anthonys, A. C. Garnett, H. Gouk

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The determination of one's movement through the environment (visual odometry or self-motion estimation) from monocular sources such as video is an important research problem because of its relevance to robotics and autonomous vehicles. The traditional computer vision approach to this problem tracks visual features across frames in order to obtain 2-D image motion estimates from which the camera motion can be derived. We present an alternative scheme which uses the properties of motion sensitive cells in the primate brain to derive the image motion and the camera heading vector. We tested heading estimation using a camera mounted on a linear translation table with the line of sight of the camera set at a range of angles relative to straight ahead (0° to 50° in 10° steps). The camera velocity was also varied (0.2, 0.4, 0.8, 1.2, 1.6 and 2.0 m/s). Our biologically-based method produced accurate heading estimates over a wide range of test angles and camera speeds. Our approach has the advantage of being a one-shot estimator and not requiring iterative search techniques for finding the heading.
Original languageEnglish
Title of host publication2016 International Conference on Image and Vision Computing New Zealand (IVCNZ)
EditorsDonald Bailey, Gourab Sen Gupta, Stephen Marsland
Place of PublicationPalmeston North
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1-6
Number of pages6
ISBN (Electronic)978-1-5090-2748-4 , 978-1-5090-2747-7
ISBN (Print)978-1-5090-2749-1
DOIs
Publication statusPublished - 5 Jan 2017
EventImage and Vision Computing New Zealand 2016 - Palmerston North, New Zealand
Duration: 21 Nov 201622 Nov 2016
http://ivcnz.massey.ac.nz/

Publication series

NameProceedings of the 2016 International Conference on Image and Vision Computing New Zealand (IVCNZ)
PublisherIEEE
ISSN (Electronic)2151-2205

Conference

ConferenceImage and Vision Computing New Zealand 2016
Abbreviated titleIVCNZ 2016
CountryNew Zealand
CityPalmerston North
Period21/11/1622/11/16
Internet address

Keywords

  • cameras
  • computer vision
  • motion estimation
  • video signal processing
  • heading direction estimation
  • monocular video sequences
  • biologically-based sensors
  • environment
  • visual odometry
  • self-motion estimation
  • visual features
  • 2D image motion estimates
  • camera motion
  • camera heading vector
  • linear translation table
  • Cameras
  • Detectors
  • Estimation
  • Visualization
  • Video sequences
  • Optical imaging
  • visual sensor
  • image motion

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