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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Nanyang Technological University
2022
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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 |
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Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Ngiam, Zhen Ying Visual localization on NTU campus |
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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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1731235742561075200 |