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Title: | Visual localization on NTU campus | Authors: | Ngiam, Zhen Ying | Keywords: | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence | Issue Date: | 2022 | Publisher: | Nanyang Technological University | Source: | Ngiam, Z. Y. (2022). Visual localization on NTU campus. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/156367 | Project: | SCSE21-0164 | Abstract: | 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. | URI: | https://hdl.handle.net/10356/156367 | Schools: | School of Computer Science and Engineering | Fulltext Permission: | restricted | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Student Reports (FYP/IA/PA/PI) |
Files in This Item:
File | Description | Size | Format | |
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Ngiam Zhen Ying_U1922497F_FYP Report.pdf Restricted Access | 1.36 MB | Adobe PDF | View/Open |
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