Comparative evaluation of pedestrian detection methods for mobile bus surveillance Leoputra, Wilson S., Venkatesh, Svetha and Tan, Tele 2009, Comparative evaluation of pedestrian detection methods for mobile bus surveillance, in ICASSP 2009 : Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, IEEE, Piscataway, N. J., pp. 3525-3528. Attached Files Name Description MIMEType Size Downloads venkatesh-comparativeevaluation-2009.pdf Published version application/pdf 343.42KB 97 Title Comparative evaluation of pedestrian detection methods for mobile bus surveillance Author(s) Leoputra, Wilson S. Venkatesh, Svetha orcid.org/0000-0001-8675-6631 Tan, Tele Conference name IEEE International Conference on Acoustics, Speech, and Signal Processing (2009 : Taipei, Taiwan) Conference location Taipei, Taiwan Conference dates 19-24 Apr. 2009 Title of proceedings ICASSP 2009 : Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing Editor(s) [Unknown] Publication date 2009 Conference series IEEE International Conference on Acoustics, Speech, and Signal Processing Start page 3525 End page 3528 Total pages 4 Publisher IEEE Place of publication Piscataway, N. J. Keyword(s) distributed mobile sensors large scale urban surveillance pedestrian detection Summary We present a comparative evaluation of the state-of-art algorithms for detecting pedestrians in low frame rate and low resolution footage acquired by mobile sensors. Four approaches are compared: a) The Histogram of Oriented Gradient (HoG) approach [1]; b) A new histogram feature that is formed by the weighted sum of both the gradient magnitude and the filter responses from a set of elongated Gaussian filters [2] corresponding to the quantised orientation, called Histogram of Oriented Gradient Banks (HoGB) approach; c) The codebook based HoG feature with branch-and-bound (efficient subwindow search) algorithm [3] and; d) The codebook based HoGB approach. Results show that the HoG based detector achieves the highest performance in terms of the true positive detection, the HoGB approach has the lowest false positives whilst maintaining a comparable true positive rate to the HoG, and the codebook approaches allow computationally efficient detection. Notes This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder. ISBN 1424423538 9781424423538 ISSN 1520-6149 Language eng Field of Research 089999 Information and Computing Sciences not elsewhere classified Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences HERDC Research category E1.1 Full written paper - refereed Copyright notice ©2009, IEEE Persistent URL http://hdl.handle.net/10536/DRO/DU:30044561 Document type: Conference Paper Collections: School of Information Technology Open Access Collection Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Fri, 20 Apr 2012, 11:32:18 EST Thu, 26 Apr 2012, 12:03:34 EST Thu, 26 Apr 2012, 12:05:41 EST Tue, 01 May 2012, 15:31:48 EST Tue, 29 Jul 2014, 14:34:19 EST Tue, 06 Sep 2016, 18:42:54 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 3 times in Scopus Search Google Scholar Access Statistics: 237 Abstract Views, 97 File Downloads  -  Detailed Statistics Created: Fri, 20 Apr 2012, 11:32:18 EST

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