A biologically inspired system for human posture recognition

We present a biologically-motivated system to recognize human postures in realtime video sequences. The system employs event-based temporal difference image between video...

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Main Authors:	Chen, Shoushun, Akselrod, Polina, Culurciello, Eugenio
Other Authors:	School of Electrical and Electronic Engineering
Format:	Conference or Workshop Item
Language:	English
Published:	2010
Subjects:	DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
Online Access:	https://hdl.handle.net/10356/91595 http://hdl.handle.net/10220/6362
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Institution:	Nanyang Technological University
Language:	English

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spelling	sg-ntu-dr.10356-915952020-03-07T13:24:46Z A biologically inspired system for human posture recognition Chen, Shoushun Akselrod, Polina Culurciello, Eugenio School of Electrical and Electronic Engineering IEEE Biomedical Circuits and Systems Conference (2009 : Beijing, China) DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing We present a biologically-motivated system to recognize human postures in realtime video sequences. The system employs event-based temporal difference image between video sequences as input and builds a network of bio-inspired Gaborlike filters to detect contours of the active object. The detected contours are organized into vectorial line segments. After feature extraction, a classifier based on simplified line segment Hausdorff distance combined with projection histograms is implemented to achieve size and position invariant recognition. 86% average recognition rate is achieved in the experiment. Compared to state-of-the art bio-inspired categorization methods shows great computational savings, and is an ideal candidate for hardware implementation with event-based circuits. Published version 2010-08-30T04:24:45Z 2019-12-06T18:08:35Z 2010-08-30T04:24:45Z 2019-12-06T18:08:35Z 2009 2009 Conference Paper Chen, S. S., Akselrod, P., & Culurciello, E. (2009). A biologically inspired system for human posture recognition. In proceedings of the IEEE Biomedical Circuits and Systems Conference: Beijing, China, (pp.113-116). https://hdl.handle.net/10356/91595 http://hdl.handle.net/10220/6362 10.1109/BIOCAS.2009.5372070 en © 2009 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
institution	Nanyang Technological University
building	NTU Library
country	Singapore
collection	DR-NTU
language	English
topic	DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing
spellingShingle	DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Chen, Shoushun Akselrod, Polina Culurciello, Eugenio A biologically inspired system for human posture recognition
description	We present a biologically-motivated system to recognize human postures in realtime video sequences. The system employs event-based temporal difference image between video sequences as input and builds a network of bio-inspired Gaborlike filters to detect contours of the active object. The detected contours are organized into vectorial line segments. After feature extraction, a classifier based on simplified line segment Hausdorff distance combined with projection histograms is implemented to achieve size and position invariant recognition. 86% average recognition rate is achieved in the experiment. Compared to state-of-the art bio-inspired categorization methods shows great computational savings, and is an ideal candidate for hardware implementation with event-based circuits.
author2	School of Electrical and Electronic Engineering
author_facet	School of Electrical and Electronic Engineering Chen, Shoushun Akselrod, Polina Culurciello, Eugenio
format	Conference or Workshop Item
author	Chen, Shoushun Akselrod, Polina Culurciello, Eugenio
author_sort	Chen, Shoushun
title	A biologically inspired system for human posture recognition
title_short	A biologically inspired system for human posture recognition
title_full	A biologically inspired system for human posture recognition
title_fullStr	A biologically inspired system for human posture recognition
title_full_unstemmed	A biologically inspired system for human posture recognition
title_sort	biologically inspired system for human posture recognition
publishDate	2010
url	https://hdl.handle.net/10356/91595 http://hdl.handle.net/10220/6362
_version_	1681035086444625920

A biologically inspired system for human posture recognition

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