Skip to Main content Skip to Navigation
Journal articles

Accurate Indoor Localization through Constrained Visual SLAM

Olivier Gomez 1, 2 Achkan Salehi 1, 2 Vincent Gay-Bellile 1, 2 Mathieu Carrier 1, 2 
1 LVIC - Laboratoire Vision et Ingénierie des Contenus
DIASI - Département Intelligence Ambiante et Systèmes Interactifs : DRT/LIST/DIASI
Abstract : — In this paper, we focus on navigation in indoor environments using Visual SLAM (VSLAM). We propose an approach to suppress the known drifting issue of VSLAM and express its localization in building coordinate frame. It relies on a database built offline through a coarse to fine strategy that registers and refines a VSLAM reconstruction by taking advantage of the building 3D model. The database can then be extended online when the user goes out and comes back in the known environment. We present experimental results on synthetic and real data.
Document type :
Journal articles
Complete list of metadata

Cited literature [10 references]  Display  Hide  Download
Contributor : Vincent Gay-Bellile Connect in order to contact the contributor
Submitted on : Thursday, July 5, 2018 - 9:48:06 AM
Last modification on : Thursday, February 17, 2022 - 10:08:05 AM
Long-term archiving on: : Monday, October 1, 2018 - 4:01:21 PM


Files produced by the author(s)


  • HAL Id : cea-01830464, version 1


Olivier Gomez, Achkan Salehi, Vincent Gay-Bellile, Mathieu Carrier. Accurate Indoor Localization through Constrained Visual SLAM. 2017 International Conference on Indoor Positioning and Indoor Navigation (IPIN), 2017. ⟨cea-01830464⟩



Record views


Files downloads