A size and position invariant event-based human posture recognition algorithm
In this paper we report a size and position invariant human posture recognition algorithm. The algorithm employs a simplified line segment Hausdorff distance classification and uses projection histograms to achieve size and position invariance....
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sg-ntu-dr.10356-915932020-03-07T13:24:46Z A size and position invariant event-based human posture recognition algorithm Chen, Shoushun Folowosele, Fopefolu Kim, Dongsoo Vogelstein, R. Jacob Etienne-Cummings, Ralph Culurciello, Eugenio School of Electrical and Electronic Engineering IEEE Biomedical Circuits and Systems Conference (2008 : Baltimore, Maryland, US) DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems In this paper we report a size and position invariant human posture recognition algorithm. The algorithm employs a simplified line segment Hausdorff distance classification and uses projection histograms to achieve size and position invariance. Compared to other existing method utilizing line segment Hausdorff distance, the proposed algorithm reduces the computation complexity by 36000 times, for our test images. Combining bioinspired event-based image acquisition and hardware friendly feature extraction and classification algorithm will lead to a promising technology for use in wireless sensor network. Published version 2010-08-31T01:07:41Z 2019-12-06T18:08:33Z 2010-08-31T01:07:41Z 2019-12-06T18:08:33Z 2008 2008 Conference Paper Chen, S., Folowosele, F., Kim, D., Vogelstein, R. J., Etienne-Cummings, R., & Culurciello, E. (2008). A size and position invariant event-based human posture recognition algorithm. IEEE Biomedical Circuits and Systems Conference: Baltimore,MD,USA, (pp.285-288). https://hdl.handle.net/10356/91593 http://hdl.handle.net/10220/6372 10.1109/BIOCAS.2008.4696930 en © 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. 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. http://www.ieee.org/portal/site 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. 4 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering::Computer hardware, software and systems Chen, Shoushun Folowosele, Fopefolu Kim, Dongsoo Vogelstein, R. Jacob Etienne-Cummings, Ralph Culurciello, Eugenio A size and position invariant event-based human posture recognition algorithm |
description |
In this paper we report a size and position invariant
human posture recognition algorithm. The algorithm employs a
simplified line segment Hausdorff distance classification and uses
projection histograms to achieve size and position invariance.
Compared to other existing method utilizing line segment Hausdorff
distance, the proposed algorithm reduces the computation
complexity by 36000 times, for our test images. Combining bioinspired
event-based image acquisition and hardware friendly
feature extraction and classification algorithm will lead to a
promising technology for use in wireless sensor network. |
author2 |
School of Electrical and Electronic Engineering |
author_facet |
School of Electrical and Electronic Engineering Chen, Shoushun Folowosele, Fopefolu Kim, Dongsoo Vogelstein, R. Jacob Etienne-Cummings, Ralph Culurciello, Eugenio |
format |
Conference or Workshop Item |
author |
Chen, Shoushun Folowosele, Fopefolu Kim, Dongsoo Vogelstein, R. Jacob Etienne-Cummings, Ralph Culurciello, Eugenio |
author_sort |
Chen, Shoushun |
title |
A size and position invariant event-based human posture recognition algorithm |
title_short |
A size and position invariant event-based human posture recognition algorithm |
title_full |
A size and position invariant event-based human posture recognition algorithm |
title_fullStr |
A size and position invariant event-based human posture recognition algorithm |
title_full_unstemmed |
A size and position invariant event-based human posture recognition algorithm |
title_sort |
size and position invariant event-based human posture recognition algorithm |
publishDate |
2010 |
url |
https://hdl.handle.net/10356/91593 http://hdl.handle.net/10220/6372 |
_version_ |
1681048620430786560 |