Indoor Positioning Using PnP Problem on Mobile Phone Images
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 me...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2020-06-01
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| Series: | ISPRS International Journal of Geo-Information |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2220-9964/9/6/368 |
| _version_ | 1797566287351644160 |
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| author | Hana Kubíčková Karel Jedlička Radek Fiala Daniel Beran |
| author_facet | Hana Kubíčková Karel Jedlička Radek Fiala Daniel Beran |
| author_sort | Hana Kubíčková |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T19:24:34Z |
| format | Article |
| id | doaj.art-3b244c5a45a64c05b1d7f613f854b247 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T19:24:34Z |
| publishDate | 2020-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-3b244c5a45a64c05b1d7f613f854b2472023-11-20T02:39:49ZengMDPI AGISPRS International Journal of Geo-Information2220-99642020-06-019636810.3390/ijgi9060368Indoor Positioning Using PnP Problem on Mobile Phone ImagesHana Kubíčková0Karel Jedlička1Radek Fiala2Daniel Beran3Plan4all, 33012 Horní Bříza, Czech RepublicDepartment of Geomatics, University of West Bohemia, 30100 Plzeň, Czech RepublicDepartment of Geomatics, University of West Bohemia, 30100 Plzeň, Czech RepublicDepartment of Geomatics, University of West Bohemia, 30100 Plzeň, Czech RepublicAs 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.https://www.mdpi.com/2220-9964/9/6/368indoor positioning systemimage-based positioning systemcomputer visionSIFTfeature detectionfeature description |
| spellingShingle | Hana Kubíčková Karel Jedlička Radek Fiala Daniel Beran Indoor Positioning Using PnP Problem on Mobile Phone Images ISPRS International Journal of Geo-Information indoor positioning system image-based positioning system computer vision SIFT feature detection feature description |
| title | Indoor Positioning Using PnP Problem on Mobile Phone Images |
| title_full | Indoor Positioning Using PnP Problem on Mobile Phone Images |
| title_fullStr | Indoor Positioning Using PnP Problem on Mobile Phone Images |
| title_full_unstemmed | Indoor Positioning Using PnP Problem on Mobile Phone Images |
| title_short | Indoor Positioning Using PnP Problem on Mobile Phone Images |
| title_sort | indoor positioning using pnp problem on mobile phone images |
| topic | indoor positioning system image-based positioning system computer vision SIFT feature detection feature description |
| url | https://www.mdpi.com/2220-9964/9/6/368 |
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