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Author: | Noreikis, Marius |
Title: | Image Based Indoor Navigation |
Publication type: | Master's thesis |
Publication year: | 2014 |
Pages: | 87 Language: eng |
Department/School: | Tietotekniikan laitos |
Main subject: | Tietokoneverkot (T-110) |
Supervisor: | Ylä-Jääski, Antti ; Sjödin, Peter |
Instructor: | Xiao, Yu |
Electronic version URL: | http://urn.fi/URN:NBN:fi:aalto-201409252674 |
OEVS: | Electronic archive copy is available via Aalto Thesis Database.
Instructions Reading digital theses in the closed network of the Aalto University Harald Herlin Learning CentreIn the closed network of Learning Centre you can read digital and digitized theses not available in the open network. The Learning Centre contact details and opening hours: https://learningcentre.aalto.fi/en/harald-herlin-learning-centre/ You can read theses on the Learning Centre customer computers, which are available on all floors.
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Location: | P1 Ark Aalto 2426 | Archive |
Keywords: | navigation structure from motion point clouds feature extraction indoor localisation navigation mesh pathnding |
Abstract (eng): | Over the last years researchers proposed numerous indoor localization and navigation systems. However, solutions that use WiFi or Radio Frequency Identification require infrastructure to be deployed in the navigation area and infrastructure less techniques, e.g. the ones based on mobile cell ID or dead reckoning suffer from large accuracy errors. In this Thesis, we present a novel approach of infrastructure-less indoor navigation system based on computer vision Structure from Motion techniques. We implemented a prototype localization and navigation system which can build a navigation map using area photos as input and accurately locate a user in the map. In our client-server architecture based system, a client is a mobile application, which allows a user to locate her or his position by simply taking a photo. The server handles map creation, localization queries and path finding. After the implementation, we evaluated the localization accuracy and latency of the system by benchmarking navigation queries and the model creation algorithm. The system is capable of successfully navigating in Aalto University computer science department library. We were able to achieve an average error of 0.26 metres for successfully localised photos. In the Thesis, we also present challenges that we solved to adapt computer vision techniques for localisation purposes. Finally we observe the possible future work topics to adapt the system to a wide use. |
ED: | 2014-09-16 |
INSSI record number: 49704
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