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Pedestrian behaviour analysis using the microsoft kinect

Chen, Junying, Rajasegarar, Sutharshan, Leckie, Christopher and Gygax, Andre 2016, Pedestrian behaviour analysis using the microsoft kinect, in PerCom Workshops 2016: Proceedings of the 13th IEEE International Conference on Pervasive Computing and Communication Workshops, IEEE, Piscataway, N.J., pp. 1-6, doi: 10.1109/PERCOMW.2016.7457094.

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Title Pedestrian behaviour analysis using the microsoft kinect
Author(s) Chen, Junying
Rajasegarar, Sutharshan
Leckie, Christopher
Gygax, Andre
Conference name Pervasive Computing and Communication Workshops. IEEE International Conference (13th : 2016 : Sydney, N.S.W.)
Conference location Sydney, N.S.W.
Conference dates 14-18 Mar. 2016
Title of proceedings PerCom Workshops 2016: Proceedings of the 13th IEEE International Conference on Pervasive Computing and Communication Workshops
Publication date 2016
Start page 1
End page 6
Total pages 6
Publisher IEEE
Place of publication Piscataway, N.J.
Summary An important challenge for brick-and-mortar retail businesses is how to monitor the interest of customers in displays and products in a store. We investigate the effectiveness of the Microsoft Kinect as a sensor to monitor the behaviour of pedestrians, which may reflect their interest in a store display or advertisement. In a controlled environment, participants acting as pedestrians are requested to show different levels of interest as they pass an object that is being monitored by a Kinect sensor. The sensor collected measurements such as the positions and orientation of the pedestrian's body and head, which were analysed to detect the movements of the pedestrians and thus infer the behaviour they exhibited. Our results demonstrate that when the Kinect is able to detect a behaviour that indicates a pedestrian's interest in an object, then the classification of the level of interest in terms of the type of behaviour is reasonably accurate under varying light conditions and numbers of pedestrians.
ISBN 9781509019410
Language eng
DOI 10.1109/PERCOMW.2016.7457094
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
ERA Research output type E Conference publication
Copyright notice ©2016, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30083727

Document type: Conference Paper
Collection: School of Information Technology
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Created: Thu, 18 Aug 2016, 16:03:48 EST

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