Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/129979
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dc.contributor.authorChin, T.J.-
dc.contributor.authorBagchi, S.-
dc.contributor.authorEriksson, A.-
dc.contributor.authorVan Schaik, A.-
dc.date.issued2019-
dc.identifier.citationConference on Computer Vision and Pattern Recognition Workshops IEEE Computer Society Conference on Computer Vision and Pattern Recognition. Workshops, 2019, vol.2019-June, pp.1646-1655-
dc.identifier.isbn9781728125060-
dc.identifier.issn2160-7508-
dc.identifier.issn2160-7516-
dc.identifier.urihttp://hdl.handle.net/2440/129979-
dc.description.abstractStar trackers are primarily optical devices that are used to estimate the attitude of a spacecraft by recognising and tracking star patterns. Currently, most star trackers use conventional optical sensors. In this application paper, we propose the usage of event sensors for star tracking. There are potentially two benefits of using event sensors for star tracking: lower power consumption and higher operating speeds. Our main contribution is to formulate an algorithmic pipeline for star tracking from event data that includes novel formulations of rotation averaging and bundle adjustment. In addition, we also release with this paper a dataset for star tracking using event cameras. With this work, we introduce the problem of star tracking using event cameras to the computer vision community, whose expertise in SLAM and geometric optimisation can be brought to bear on this commercially important application.-
dc.description.statementofresponsibilityTat-Jun Chin, Samya Bagchi, Anders Eriksson, André van Schaik-
dc.language.isoen-
dc.publisherIEEE-
dc.relation.ispartofseriesIEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops-
dc.rights©2019 IEEE-
dc.source.urihttps://ieeexplore.ieee.org/xpl/conhome/8972688/proceeding-
dc.titleStar tracking using an event camera-
dc.typeConference paper-
dc.contributor.conferenceIEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (16 Jun 2019 - 17 Jun 2019 : Long Beach, USA)-
dc.identifier.doi10.1109/CVPRW.2019.00208-
dc.publisher.placeonline-
dc.relation.granthttp://purl.org/au-research/grants/arc/LP160100495-
dc.relation.granthttp://purl.org/au-research/grants/arc/FT170100072-
pubs.publication-statusPublished-
dc.identifier.orcidBagchi, S. [0000-0001-5132-5727]-
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Computer Science publications

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