3D Sensing and Tracking of Human Gait

Motion capture technology has been applied in many fields such as animation, medicine, military, etc. since it was first proposed in the 1970s. Based on the principles applied, motion capture technology is generally classified into six categories: 1) Optical; 2) Inertial; 3) Magnetic; 4) Mechanical;...

Full description

Bibliographic Details
Main Author: Yang, Lin
Other Authors: El Saddik, Abdulmotaleb
Language:en
Published: Université d'Ottawa / University of Ottawa 2015
Subjects:
Online Access:http://hdl.handle.net/10393/32540
http://dx.doi.org/10.20381/ruor-4256
id ndltd-uottawa.ca-oai-ruor.uottawa.ca-10393-32540
record_format oai_dc
spelling ndltd-uottawa.ca-oai-ruor.uottawa.ca-10393-325402018-01-05T19:02:25Z 3D Sensing and Tracking of Human Gait Yang, Lin El Saddik, Abdulmotaleb Motion capture multi-Kinect trilateration depth accuracy Kinect v2 gait tracking Motion capture technology has been applied in many fields such as animation, medicine, military, etc. since it was first proposed in the 1970s. Based on the principles applied, motion capture technology is generally classified into six categories: 1) Optical; 2) Inertial; 3) Magnetic; 4) Mechanical; 5) Acoustic and 6) Markerless. Different from the other five kinds of motion capture technologies which try to track path of specific points with different equipment, markerless systems recognize human or non-human body's motion with vision-based technology which focuses on analyzing and processing the captured images for motion capture. The user doed not need to wear any equipment and is free to do any action in an extensible measurement area while a markerless motion capture system is working. Though this kind of system is considered as the preferred solution for motion capture, the difficulty for realizing an effective and high accuracy markerless system is much higher than the other technologies mentioned, which makes markerless motion capture development a popular research direction. Microsoft Kinect sensor has attracted lots of attention since the launch of its first version with its depth sensing feature which gives the sensor the ability to do motion capture without any extra devices. Recently, Microsoft released a new version of Kinect sensor with improved hardware and and targeted at the consumer market. However, to the best of our knowlege, the accuracy assessment of the sensor remains to be answered since it was released. In this thesis, we measure the depth accuracy of the newly released Kinect v2 depth sensor from different aspects and propose a trilateration method to improve the depth accuracy with multiple Kinects simultaneously. Based on the trilateration method, a low-cost, no wearable equipment requirement and easy setup human gait tracking system is realized. 2015-07-17T17:17:58Z 2015-07-17T17:17:58Z 2015 2015 Thesis http://hdl.handle.net/10393/32540 http://dx.doi.org/10.20381/ruor-4256 en Université d'Ottawa / University of Ottawa
collection NDLTD
language en
sources NDLTD
topic Motion capture
multi-Kinect trilateration
depth
accuracy
Kinect v2
gait tracking
spellingShingle Motion capture
multi-Kinect trilateration
depth
accuracy
Kinect v2
gait tracking
Yang, Lin
3D Sensing and Tracking of Human Gait
description Motion capture technology has been applied in many fields such as animation, medicine, military, etc. since it was first proposed in the 1970s. Based on the principles applied, motion capture technology is generally classified into six categories: 1) Optical; 2) Inertial; 3) Magnetic; 4) Mechanical; 5) Acoustic and 6) Markerless. Different from the other five kinds of motion capture technologies which try to track path of specific points with different equipment, markerless systems recognize human or non-human body's motion with vision-based technology which focuses on analyzing and processing the captured images for motion capture. The user doed not need to wear any equipment and is free to do any action in an extensible measurement area while a markerless motion capture system is working. Though this kind of system is considered as the preferred solution for motion capture, the difficulty for realizing an effective and high accuracy markerless system is much higher than the other technologies mentioned, which makes markerless motion capture development a popular research direction. Microsoft Kinect sensor has attracted lots of attention since the launch of its first version with its depth sensing feature which gives the sensor the ability to do motion capture without any extra devices. Recently, Microsoft released a new version of Kinect sensor with improved hardware and and targeted at the consumer market. However, to the best of our knowlege, the accuracy assessment of the sensor remains to be answered since it was released. In this thesis, we measure the depth accuracy of the newly released Kinect v2 depth sensor from different aspects and propose a trilateration method to improve the depth accuracy with multiple Kinects simultaneously. Based on the trilateration method, a low-cost, no wearable equipment requirement and easy setup human gait tracking system is realized.
author2 El Saddik, Abdulmotaleb
author_facet El Saddik, Abdulmotaleb
Yang, Lin
author Yang, Lin
author_sort Yang, Lin
title 3D Sensing and Tracking of Human Gait
title_short 3D Sensing and Tracking of Human Gait
title_full 3D Sensing and Tracking of Human Gait
title_fullStr 3D Sensing and Tracking of Human Gait
title_full_unstemmed 3D Sensing and Tracking of Human Gait
title_sort 3d sensing and tracking of human gait
publisher Université d'Ottawa / University of Ottawa
publishDate 2015
url http://hdl.handle.net/10393/32540
http://dx.doi.org/10.20381/ruor-4256
work_keys_str_mv AT yanglin 3dsensingandtrackingofhumangait
_version_ 1718598339148120064