Abstract
Monocular SLAM reconstruction algorithm advancements enable their integration in various applications: trajectometry, 3D model reconstruction, etc. However, proposed methods still have drift limitations when applied to large-scale sequences. In this paper, we propose a two steps post-processing algorithm which exploits a CAD model of the environment to correct SLAM reconstructions. First, a specific non-rigid ICP between the reconstructed 3D point cloud and the known CAD model is proposed. Then, a new constrained bundle adjustment process is presented to improve the accuracy of the obtained reconstructions. Experimental results on both synthetic and real sequences point out that the 3D scene geometry regains its consistency and that the camera trajectory is improved: mean distance between the reconstructed cameras and the ground truth is less than 50 centimetres on several hundreds of meters.
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Lothe, P., Bourgeois, S., Dekeyser, F., Royer, E., Dhome, M. (2010). Monocular SLAM Reconstructions and 3D City Models: Towards a Deep Consistency. In: Ranchordas, A., Pereira, J.M., Araújo, H.J., Tavares, J.M.R.S. (eds) Computer Vision, Imaging and Computer Graphics. Theory and Applications. VISIGRAPP 2009. Communications in Computer and Information Science, vol 68. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11840-1_15
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DOI: https://doi.org/10.1007/978-3-642-11840-1_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-11839-5
Online ISBN: 978-3-642-11840-1
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