Motion based pedestrian recognition

Chen, Y; Wu, Q; He, X

Motion based pedestrian recognition

Chen, Y Wu, Q

He, X

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Publication Type:: Conference Proceeding
Citation:: Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008, 2008, 2 pp. 376 - 380
Issue Date:: 2008-09-24

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Field	Value	Language
dc.contributor.author	Chen, Y	en_US
dc.contributor.author	Wu, Q https://orcid.org/0000-0001-5641-2483	en_US
dc.contributor.author	He, X https://orcid.org/0000-0001-8962-540X	en_US
dc.date.issued	2008-09-24	en_US
dc.identifier.citation	Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008, 2008, 2 pp. 376 - 380	en_US
dc.identifier.isbn	9780769531199	en_US
dc.identifier.uri	http://hdl.handle.net/10453/10776
dc.description.abstract	This paper proposed a method for discriminating pedestrians from rigid objects in a video. The method is a motion-based recognition of moving objects. This method is motivated by the assumptions that human beings are non-rigid and their movements are periodic. Moving objects and their skeletons are extracted. The motion cue is determined by the angle formed by the centroid point and the two bottom end points at object's skeleton. The histogram of the cue over a time period is used to determine if the object is pedestrian or not. This cue does not require any pre-built models. Neither does it need Fourier Transform to obtain the cycle of the objects. The proposed method is computation inexpensive, and it can be used for real-time video surveillance. ©2008 IEEE.	en_US
dc.relation.ispartof	Proceedings - 1st International Congress on Image and Signal Processing, CISP 2008	en_US
dc.relation.isbasedon	10.1109/CISP.2008.718	en_US
dc.title	Motion based pedestrian recognition	en_US
dc.type	Conference Proceeding
utslib.citation.volume	2	en_US
utslib.for	080106 Image Processing	en_US
utslib.for	080104 Computer Vision	en_US
utslib.for	080109 Pattern Recognition and Data Mining	en_US
dc.location.activity	Sanya, China	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Strength - CRIN - Realtime Information Networks
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
pubs.organisational-group	/University of Technology Sydney/Strength - INEXT - Innovation in IT Services and Applications
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	2	en_US

Abstract:

This paper proposed a method for discriminating pedestrians from rigid objects in a video. The method is a motion-based recognition of moving objects. This method is motivated by the assumptions that human beings are non-rigid and their movements are periodic. Moving objects and their skeletons are extracted. The motion cue is determined by the angle formed by the centroid point and the two bottom end points at object's skeleton. The histogram of the cue over a time period is used to determine if the object is pedestrian or not. This cue does not require any pre-built models. Neither does it need Fourier Transform to obtain the cycle of the objects. The proposed method is computation inexpensive, and it can be used for real-time video surveillance. ©2008 IEEE.

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http://hdl.handle.net/10453/10776