Visual localization on NTU campus

The advancement of technology in localization system has been growing in demand among the industries in the modern civilisation. Localization system technology enables location identification of an environment depending on the location of the user or device. Numerous data can be extracted from locat...

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Main Author: Ngiam, Zhen Ying
Other Authors: Lin Weisi
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2022
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Online Access:https://hdl.handle.net/10356/156367
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1563672022-04-15T07:35:31Z Visual localization on NTU campus Ngiam, Zhen Ying Lin Weisi School of Computer Science and Engineering WSLin@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence The advancement of technology in localization system has been growing in demand among the industries in the modern civilisation. Localization system technology enables location identification of an environment depending on the location of the user or device. Numerous data can be extracted from location information of an environment such as set of images, 3D scene models and points cloud. With the extracted data, it can be used in a localization framework of Visual Localization. Visual localization estimates the 6 Degree-of-Freedom (DoF) camera pose from an image relative to a reference scene representation, which allows it to be feasible for indoor and outdoor environments. The objective of this project is to focus on improving and implementing a visual localization framework that can detect the accurate position of a user with a picture taken from gadgets such as smartphones. The project application aids the user to navigate and locate oneself within the NTU Campus. However, visual localization framework has limitations that has yet to overcome such as dynamic scenes with moving objects, changes in the lighting and shadow from day to night. As such, this report explores the existing research methods, mainly scene coordinate regression module of visual localization framework, and improvements that can be implemented to the framework. Bachelor of Engineering (Computer Science) 2022-04-15T07:34:32Z 2022-04-15T07:34:32Z 2022 Final Year Project (FYP) Ngiam, Z. Y. (2022). Visual localization on NTU campus. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156367 https://hdl.handle.net/10356/156367 en SCSE21-0164 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
spellingShingle Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence
Ngiam, Zhen Ying
Visual localization on NTU campus
description The advancement of technology in localization system has been growing in demand among the industries in the modern civilisation. Localization system technology enables location identification of an environment depending on the location of the user or device. Numerous data can be extracted from location information of an environment such as set of images, 3D scene models and points cloud. With the extracted data, it can be used in a localization framework of Visual Localization. Visual localization estimates the 6 Degree-of-Freedom (DoF) camera pose from an image relative to a reference scene representation, which allows it to be feasible for indoor and outdoor environments. The objective of this project is to focus on improving and implementing a visual localization framework that can detect the accurate position of a user with a picture taken from gadgets such as smartphones. The project application aids the user to navigate and locate oneself within the NTU Campus. However, visual localization framework has limitations that has yet to overcome such as dynamic scenes with moving objects, changes in the lighting and shadow from day to night. As such, this report explores the existing research methods, mainly scene coordinate regression module of visual localization framework, and improvements that can be implemented to the framework.
author2 Lin Weisi
author_facet Lin Weisi
Ngiam, Zhen Ying
format Final Year Project
author Ngiam, Zhen Ying
author_sort Ngiam, Zhen Ying
title Visual localization on NTU campus
title_short Visual localization on NTU campus
title_full Visual localization on NTU campus
title_fullStr Visual localization on NTU campus
title_full_unstemmed Visual localization on NTU campus
title_sort visual localization on ntu campus
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/156367
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