Real-time implementation of quaternion-based human footstep detection

Footstep detection, a main component in human surveillance system, requires effective algorithm to be developed to detect the presence of footstep for a desired detection range. In this project, a quaternion theory is applied to represent trajectory of particle velocity generated by footstep seismic...

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Main Author: Shen, Huizhi.
Other Authors: Andy Khong Wai Hoong
Format: Final Year Project
Language:English
Published: 2013
Subjects:
Online Access:http://hdl.handle.net/10356/54489
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-544892023-07-07T16:15:21Z Real-time implementation of quaternion-based human footstep detection Shen, Huizhi. Andy Khong Wai Hoong School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing Footstep detection, a main component in human surveillance system, requires effective algorithm to be developed to detect the presence of footstep for a desired detection range. In this project, a quaternion theory is applied to represent trajectory of particle velocity generated by footstep seismic waves and captured by tri-axial geophone. Directional statistics is used on the rotation axis, rotation angle and orientation quaternion to detect the presence of elliptical polarization and hence footsteps. The quaternion-based algorithm is implemented in real-time. Further, the rotational characteristics using quaternion is combined with kurtosis, an energy-based technique a more robust detection. Vehicle bearing estimation is another important task in most surveillance systems. Rotation axis given by quaternion provides significant information of source direction which can be considered as an indicator of location of source. Bachelor of Engineering 2013-06-21T02:37:10Z 2013-06-21T02:37:10Z 2013 2013 Final Year Project (FYP) http://hdl.handle.net/10356/54489 en Nanyang Technological University 64 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
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
Shen, Huizhi.
Real-time implementation of quaternion-based human footstep detection
description Footstep detection, a main component in human surveillance system, requires effective algorithm to be developed to detect the presence of footstep for a desired detection range. In this project, a quaternion theory is applied to represent trajectory of particle velocity generated by footstep seismic waves and captured by tri-axial geophone. Directional statistics is used on the rotation axis, rotation angle and orientation quaternion to detect the presence of elliptical polarization and hence footsteps. The quaternion-based algorithm is implemented in real-time. Further, the rotational characteristics using quaternion is combined with kurtosis, an energy-based technique a more robust detection. Vehicle bearing estimation is another important task in most surveillance systems. Rotation axis given by quaternion provides significant information of source direction which can be considered as an indicator of location of source.
author2 Andy Khong Wai Hoong
author_facet Andy Khong Wai Hoong
Shen, Huizhi.
format Final Year Project
author Shen, Huizhi.
author_sort Shen, Huizhi.
title Real-time implementation of quaternion-based human footstep detection
title_short Real-time implementation of quaternion-based human footstep detection
title_full Real-time implementation of quaternion-based human footstep detection
title_fullStr Real-time implementation of quaternion-based human footstep detection
title_full_unstemmed Real-time implementation of quaternion-based human footstep detection
title_sort real-time implementation of quaternion-based human footstep detection
publishDate 2013
url http://hdl.handle.net/10356/54489
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