Camera based 3-D object tracking

3-D Object tracking is a procedure to generate the trajectory of an object over time by locating its position in consecutive frames of the online or offline video and at the same time extract its depth information. It is a sub-category of vision based motion analysis. There are numerous method...

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Bibliographic Details
Main Author: Ru, Shanshan.
Other Authors: Xie Lihua
Format: Final Year Project (FYP)
Language:English
Published: 2011
Subjects:
Online Access:http://hdl.handle.net/10356/45867
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author Ru, Shanshan.
author2 Xie Lihua
author_facet Xie Lihua
Ru, Shanshan.
author_sort Ru, Shanshan.
collection NTU
description 3-D Object tracking is a procedure to generate the trajectory of an object over time by locating its position in consecutive frames of the online or offline video and at the same time extract its depth information. It is a sub-category of vision based motion analysis. There are numerous methods to solve for object localization problem, mainly based on object features. Compared with 2-D object tracking, besides object localization, 3-D projection needs one more step to reproject the 2-D pixels to 3-D real world space. 3-D object tracking mostly requires at least two cameras to model the binocular vision mechanism and further to retrieve the depth information. In this paper, one color based probabilistic tracking method is used for object localization known as CamShift. In addition, for 3-D reprojection, one set of stereo camera with disparity extraction interface is utilized. The object tracker designed can work in both online and offline modes. The tracker is a primitive model of a computerized arm tracking system. The intention of computerized arm tracking is to monitor the motion the patients to provide an objective measure of the condition and the progress of patients as they undergo therapy.
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spelling ntu-10356/458672023-07-07T17:29:56Z Camera based 3-D object tracking Ru, Shanshan. Xie Lihua School of Electrical and Electronic Engineering DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision 3-D Object tracking is a procedure to generate the trajectory of an object over time by locating its position in consecutive frames of the online or offline video and at the same time extract its depth information. It is a sub-category of vision based motion analysis. There are numerous methods to solve for object localization problem, mainly based on object features. Compared with 2-D object tracking, besides object localization, 3-D projection needs one more step to reproject the 2-D pixels to 3-D real world space. 3-D object tracking mostly requires at least two cameras to model the binocular vision mechanism and further to retrieve the depth information. In this paper, one color based probabilistic tracking method is used for object localization known as CamShift. In addition, for 3-D reprojection, one set of stereo camera with disparity extraction interface is utilized. The object tracker designed can work in both online and offline modes. The tracker is a primitive model of a computerized arm tracking system. The intention of computerized arm tracking is to monitor the motion the patients to provide an objective measure of the condition and the progress of patients as they undergo therapy. Bachelor of Engineering 2011-06-22T08:28:49Z 2011-06-22T08:28:49Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/45867 en Nanyang Technological University 56 p. application/pdf
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Ru, Shanshan.
Camera based 3-D object tracking
title Camera based 3-D object tracking
title_full Camera based 3-D object tracking
title_fullStr Camera based 3-D object tracking
title_full_unstemmed Camera based 3-D object tracking
title_short Camera based 3-D object tracking
title_sort camera based 3 d object tracking
topic DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
url http://hdl.handle.net/10356/45867
work_keys_str_mv AT rushanshan camerabased3dobjecttracking