Bundle adjustment revisited for SLAM with RGBD sensors

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.
Type de document :
Communication dans un congrès
2015 14th IAPR International Conference on Machine Vision Applications (MVA), May 2015, Tokyo, Japan. IEEE, 〈10.1109/MVA.2015.7153159〉
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https://hal-cea.archives-ouvertes.fr/cea-01830455
Contributeur : Vincent Gay-Bellile <>
Soumis le : jeudi 5 juillet 2018 - 09:40:24
Dernière modification le : vendredi 19 octobre 2018 - 10:28:01

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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. IEEE, 〈10.1109/MVA.2015.7153159〉. 〈cea-01830455〉

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