Title: Indoor Positioning Using PnP Problem on Mobile Phone Images
Authors: Kubíčková, Hana
Jedlička, Karel
Fiala, Radek
Beran, Daniel
Citation: KUBÍČKOVÁ, H., JEDLIČKA, K., FIALA, R., BERAN, D. Indoor Positioning Using PnP Problem on Mobile Phone Images. ISPRS International journal of geo-information, 2020, roč. 9, č. 6. ISSN 2220-9964.
Issue Date: 2020
Publisher: MDPI
Document type: článek
URI: 2-s2.0-85086242963
ISSN: 2220-9964
Keywords in different language: indoor positioning system;image-based positioning system;computer vision;SIFT;feature detection;feature description;cell phone camera;PnP problem;projection matrix;epipolar geometry;OpenCV
Abstract in different language: As people grow accustomed to effortless outdoor navigation, there is a rising demand for similar possibilities indoors as well. Unfortunately, indoor localization, being one of the requirements for navigation, continues to be a problem without a clear solution. In this article, we are proposing a method for an indoor positioning system using a single image. This is made possible using a small preprocessed database of images with known control points as the only preprocessing needed. Using feature detection with the SIFT (Scale Invariant Feature Transform) algorithm, we can look through the database and find an image that is the most similar to the image taken by a user. Such a pair of images is then used to find coordinates of a database of images using the PnP problem. Furthermore, projection and essential matrices are determined to calculate the user image localization-determining the position of the user in the indoor environment. The benefits of this approach lie in the single image being the only input from a user and the lack of requirements for new onsite infrastructure. Thus, our approach enables a more straightforward realization for building management.
Rights: © MDPI
Appears in Collections:Články / Articles (NTIS)
Články / Articles (KGM)

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Please use this identifier to cite or link to this item: http://hdl.handle.net/11025/42616

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