Skip to Main content Skip to Navigation
Conference papers

Bundle adjustment revisited for SLAM with RGBD sensors

Kathia Melbouci 1 Sylvie Naudet Collette 1 Vincent Gay-Bellile 1 Omar Ait-Aider 2 Mathieu Carrier 1 Michel Dhome 2 
1 LVIC - Laboratoire Vision et Ingénierie des Contenus
DIASI - Département Intelligence Ambiante et Systèmes Interactifs : DRT/LIST/DIASI
Abstract : We present a method of using depth information provided by an RGB-D sensor, for visual simultaneous localization and mapping (SLAM), in order to improve its accuracy. We present a constraint bundle adjustment which allows to easily combine depth and visual data in cost function entirely expressed in pixel. The proposed approach is evaluated on a public benchmark dataset and compared to the state of art methods.
Document type :
Conference papers
Complete list of metadata
Contributor : Vincent Gay-Bellile Connect in order to contact the contributor
Submitted on : Thursday, July 5, 2018 - 9:40:24 AM
Last modification on : Thursday, February 17, 2022 - 10:08:04 AM



Kathia Melbouci, Sylvie Naudet Collette, Vincent Gay-Bellile, Omar Ait-Aider, Mathieu Carrier, et al.. Bundle adjustment revisited for SLAM with RGBD sensors. 2015 14th IAPR International Conference on Machine Vision Applications (MVA), May 2015, Tokyo, Japan. ⟨10.1109/MVA.2015.7153159⟩. ⟨cea-01830455⟩



Record views