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Show simple item record Burke, Michael G Lasenby, J 2016-01-20T09:47:30Z 2016-01-20T09:47:30Z 2015-10
dc.identifier.citation Burke, M.G. and Lasenby, J. 2015. Pantomimic gestures for human-robot interaction. IEEE Transactions on Robotics, vol. 31(5), pp 1225- 1237 en_US
dc.identifier.issn 1552-3098
dc.description Copyright: 2015 IEEE XPLORE. Due to copyright restrictions, the attached PDF file only contains the abstract of the full text item. For access to the full text item, please consult the publisher's website. The definitive version of the work is published in the IEEE Transactions on Robotics, vol. 31(5), pp 1225- 1237 en_US
dc.description.abstract This paper introduces a pantomimic gesture interface, which classifies human hand gestures using unmanned aerial vehicle (UAV) behavior recordings as training data. We argue that pantomimic gestures are more intuitive than iconic gestures and show that a pantomimic gesture recognition strategy using micro-UAV behavior recordings can be more robust than one trained directly using hand gestures. Hand gestures are isolated by applying a maximum information criterion, with features extracted using principal component analysis and compared using a nearest neighbor classifier. These features are biased in that they are better suited to classifying certain behaviors. We show how a Bayesian update step accounting for the geometry of training features compensates for this, resulting in fairer classification results, and introduce a weighted voting system to aid in sequence labeling. en_US
dc.language.iso en en_US
dc.publisher IEEE Xplore en_US
dc.relation.ispartofseries Workflow;15659
dc.subject Gesture recognition en_US
dc.subject Human-robot interaction en_US
dc.subject Pantomimic en_US
dc.subject PCA en_US
dc.subject Time series classification en_US
dc.title Pantomimic gestures for human-robot interaction en_US
dc.type Article en_US

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