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dc.contributor.authorCree, Michael J.en_NZ
dc.contributor.authorPerrone, John A.en_NZ
dc.contributor.authorAnthonys, Gehanen_NZ
dc.contributor.authorGarnett, Aden C.en_NZ
dc.contributor.authorGouk, Henryen_NZ
dc.coverage.spatialPalmerston North, New Zealanden_NZ
dc.date.accessioned2017-02-13T02:08:11Z
dc.date.available2016en_NZ
dc.date.available2017-02-13T02:08:11Z
dc.date.issued2016en_NZ
dc.identifier.citationCree, M. J., Perrone, J. A., Anthonys, G., Garnett, A. C., & Gouk, H. (2016). Estimating heading direction from monocular video sequences using biologically-based sensor. Presented at the Image and Vision Computing New Zealand, Palmerston North, New Zealand. https://doi.org/10.1109/IVCNZ.2016.7804435en
dc.identifier.urihttps://hdl.handle.net/10289/10884
dc.description.abstractThe 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.
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.rightsThis is an author’s accepted version of an article presented at the Image and Vision Computing New Zealand (IVCNZ 2016), 21-22 November 2016, Palmerston North, New Zealand. © 2016 Crown.
dc.sourceImage and Vision Computing New Zealanden_NZ
dc.subjectCameras
dc.subjectDetectors
dc.subjectEstimation
dc.subjectVisualization
dc.subjectVideo sequences
dc.subjectOptical imaging
dc.subjectimage motion
dc.subjectvisual sensor
dc.subjectvisual odometry
dc.titleEstimating heading direction from monocular video sequences using biologically-based sensoren_NZ
dc.typeConference Contribution
dc.identifier.doi10.1109/IVCNZ.2016.7804435
pubs.elements-id143561
pubs.finish-date2016-11-22en_NZ
pubs.publisher-urlhttp://ivcnz.massey.ac.nz/default.aspen_NZ
pubs.start-date2016-11-21en_NZ


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