Real-Time Localization and 3D Reconstruction

Abstract : In this paper we describe a method that estimates the motion of a calibrated camera (settled on an experimental vehicle) and the tridimensional geometry of the environment. The only data used is a video input. In fact, interest points are tracked and matched between frames at video rate. Robust estimates of the camera motion are computed in real-time, key-frames are selected and permit the features 3D reconstruction. The algorithm is particularly appropriate to the reconstruction of long images sequences thanks to the introduction of a fast and local bundle adjustment method that ensures both good accuracy and consistency of the estimated camera poses along the sequence. It also largely reduces computational complexity compared to a global bundle adjustment. Experiments on real data were carried out to evaluate speed and robustness of the method for a sequence of about one kilometer long. Results are also compared to the ground truth measured with a differential GPS.
Type de document :
Communication dans un congrès
2006, IEEE, pp.0, 2006
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Contributeur : Maxime Lhuillier <>
Soumis le : mardi 5 septembre 2006 - 12:41:03
Dernière modification le : jeudi 7 février 2019 - 16:52:21
Document(s) archivé(s) le : vendredi 13 mai 2011 - 18:59:28



  • HAL Id : hal-00091145, version 1



Etienne Mouragnon, Maxime Lhuillier, Michel Dhome, Fabien Dekeyser, Patrick Sayd. Real-Time Localization and 3D Reconstruction. 2006, IEEE, pp.0, 2006. 〈hal-00091145〉



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