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City-scale visual SLAM

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Title: City-scale visual SLAM
Author(s): Anttila, Jesse
Contributor: University of Helsinki, Faculty of Science, none
Discipline: none
Degree program: Master's Programme in Data Science
Specialisation: no specialization
Language: English
Acceptance year: 2020
Visual simultaneous localization and mapping (visual SLAM) is a method for consistent self-contained localization using visual observations. Visual SLAM can produce very precise pose estimates without any specialized hardware, enabling applications such as AR navigation. The use of visual SLAM in very large areas and over long distances is not presently possible due to a number of significant scalability issues. In this thesis, these issues are discussed and solutions for them explored, culminating in a concept for a real-time city-scale visual SLAM system. A number of avenues for future work towards a practical implementation are also described.
Keyword(s): visual slam

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