Accuracy comparision of 2D-3D point correspondence algorithms for pose estimation

Pose estimation is one of the most basic steps when interfacing a camera with respect to the world. It has seen an increase in usage with the development of autonomy across various fields, mainly robotics. This thesis aims to compare the various 2d-3d point correspondence methods for pose estimat...

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Main Author: Srinath, Hanumantha Rao
Other Authors: Cheah Chien Chern
Format: Theses and Dissertations
Language:English
Published: 2019
Subjects:
Online Access:http://hdl.handle.net/10356/78644
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-786442023-07-04T15:56:50Z Accuracy comparision of 2D-3D point correspondence algorithms for pose estimation Srinath, Hanumantha Rao Cheah Chien Chern School of Electrical and Electronic Engineering Robotics Research Centre DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision Pose estimation is one of the most basic steps when interfacing a camera with respect to the world. It has seen an increase in usage with the development of autonomy across various fields, mainly robotics. This thesis aims to compare the various 2d-3d point correspondence methods for pose estimation available to us using three different conditions: distance from camera, resolution and pattern used. There is no documentation available today that describes which pattern, distance and algorithm configuration gives us the best results possible. After getting various correspondences, a hand-eye calibration will be performed and then later used for testing which correspondence environment produces the most accurate results. Accuracy would be the metric used to calculate the results produced from the correspondence algorithms Master of Science (Computer Control and Automation) 2019-06-25T03:03:10Z 2019-06-25T03:03:10Z 2019 Thesis http://hdl.handle.net/10356/78644 en 81 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::Computer science and engineering::Computing methodologies::Image processing and computer vision
spellingShingle DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Srinath, Hanumantha Rao
Accuracy comparision of 2D-3D point correspondence algorithms for pose estimation
description Pose estimation is one of the most basic steps when interfacing a camera with respect to the world. It has seen an increase in usage with the development of autonomy across various fields, mainly robotics. This thesis aims to compare the various 2d-3d point correspondence methods for pose estimation available to us using three different conditions: distance from camera, resolution and pattern used. There is no documentation available today that describes which pattern, distance and algorithm configuration gives us the best results possible. After getting various correspondences, a hand-eye calibration will be performed and then later used for testing which correspondence environment produces the most accurate results. Accuracy would be the metric used to calculate the results produced from the correspondence algorithms
author2 Cheah Chien Chern
author_facet Cheah Chien Chern
Srinath, Hanumantha Rao
format Theses and Dissertations
author Srinath, Hanumantha Rao
author_sort Srinath, Hanumantha Rao
title Accuracy comparision of 2D-3D point correspondence algorithms for pose estimation
title_short Accuracy comparision of 2D-3D point correspondence algorithms for pose estimation
title_full Accuracy comparision of 2D-3D point correspondence algorithms for pose estimation
title_fullStr Accuracy comparision of 2D-3D point correspondence algorithms for pose estimation
title_full_unstemmed Accuracy comparision of 2D-3D point correspondence algorithms for pose estimation
title_sort accuracy comparision of 2d-3d point correspondence algorithms for pose estimation
publishDate 2019
url http://hdl.handle.net/10356/78644
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