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- W613121688 abstract "Over the last years researchers proposed numerous indoor localisation and navigationsystems. However, solutions that use WiFi or Radio Frequency Identi_cationrequire infrastructure to be deployed in the navigation area and infrastructurelesstechniques, e.g. the ones based on mobile cell ID or dead reckoning sufferfrom large accuracy errors. In this Thesis, we present a novel approach ofinfrastructure-less indoor navigation system based on computer vision Structurefrom Motion techniques. We implemented a prototype localisation and navigationsystem which can build a navigation map using area photos as input andaccurately 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 hisposition by simply taking a photo. The server handles map creation, localisationqueries and path_nding. After the implementation, we evaluated the localisationaccuracy and latency of the system by benchmarking navigation queries and themodel creation algorithm. The system is capable of successfully navigating inAalto University computer science department library. We were able to achievean average error of 0.26 metres for successfully localised photos. In the Thesis,we also present challenges that we solved to adapt computer vision techniquesfor localisation purposes. Finally we observe the possible future work topics toadapt the system to a wide use." @default.
- W613121688 created "2016-06-24" @default.
- W613121688 creator A5054420854 @default.
- W613121688 date "2014-01-01" @default.
- W613121688 modified "2023-09-27" @default.
- W613121688 title "Image Based Indoors Navigation" @default.
- W613121688 hasPublicationYear "2014" @default.
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