<abstract xmlns="http://www.w3.org/1999/xhtml"><p> In the last decade huge research work has been put to the indoor visual localization of personal smartphones. Considering the available sensor capabilities monocular odometry provides promising solution, even reecting requirements of augmented reality applications. This paper is aimed to give an overview of state-of-the-art results regarding monocular visual localization. For this purpose essential basics of computer vision are presented and the most promising solutions are reviewed.</p></abstract>

In the last decade huge research work has been put to the indoor visual localization of personal smartphones. Considering the available sensor capabilities monocular odometry provides promising solution, even reecting requirements of augmented reality applications. This paper is aimed to give an overview of state-of-the-art results regarding monocular visual localization. For this purpose essential basics of computer vision are presented and the most promising solutions are reviewed.

Monocular indoor localization techniques for smartphones

Budapest University of Technology and Economics, Budapest,

Acta Universitatis Sapientiae, Informatica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

{"article-title":"Monocular indoor localization techniques for smartphones"}

In the last decade huge research work has been put to the indoor visual localization of personal smartphones. Considering the available sensor capabilities...

Monocular indoor localization techniques for smartphones

Online veröffentlicht: 30. Dez. 2016

Seitenbereich: 186 - 215

Eingereicht: 30. Mai 2016

DOI: https://doi.org/10.1515/ausi-2016-0009

Schlüsselwörter
computer vision, visual odometry, SLAM, indoor localization

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Monocular indoor localization techniques for smartphones

Online veröffentlicht: 30. Dez. 2016

Seitenbereich: 186 - 215

Eingereicht: 30. Mai 2016

DOI: https://doi.org/10.1515/ausi-2016-0009

Schlüsselwörtercomputer vision, visual odometry, SLAM, indoor localization

© 2017

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Schlüsselwörter
computer vision, visual odometry, SLAM, indoor localization