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Conference papers

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.
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Contributor : Maxime Lhuillier Connect in order to contact the contributor
Submitted on : Tuesday, September 5, 2006 - 12:41:03 PM
Last modification on : Thursday, February 17, 2022 - 10:08:04 AM
Long-term archiving on: : Friday, May 13, 2011 - 6:59:28 PM


  • HAL Id : hal-00091145, version 1



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



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