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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References
Nister, D., Naroditsky, O., Bergen, J.: Visual odometry. In: Computer Vision and Pattern Recognition, pp. 652–659 (2004)
Davison, A., Reid, I., Molton, N., Stasse, O.: MonoSLAM: Real-time single camera SLAM. Pattern Analysis and Machine Intelligence 26(6), 1052–1067 (2007)
Royer, E., Lhuillier, M., Dhome, M., Chateau, T.: Localization in urban environments: Monocular vision compared to a differential gps sensor. In: Computer Vision and Pattern Recognition, pp. 114–121 (2005)
Mouragnon, E., Lhuillier, M., Dhome, M., Dekeyser, F., Sayd, P.: Real time localization and 3d reconstruction. In: Computer Vision and Pattern Recognition, pp. 363–370 (2006)
Levin, A., Szeliski, R.: Visual odometry and map correlation. In: Computer Vision and Pattern Recognition, pp. 611–618 (2004)
Sourimant, G., Morin, L., Bouatouch, K.: Gps, gis and video fusion for urban modeling. In: Computer Graphics International (May 2007)
Rusinkiewicz, S., Levoy, M.: Efficient variants of the ICP algorithm. In: 3-D Digital Imaging and Modeling, pp. 145–152 (2001)
Zhao, W., Nister, D., Hsu, S.: Alignment of continuous video onto 3d point clouds. Pattern Analysis and Machine Intelligence 27(8), 1305–1318 (2005)
Fitzgibbon, A.: Robust registration of 2d and 3d point sets. In: British Machine Vision Conference, pp. 411–420 (2001)
Castellani, U., Gay-Bellile, V., Bartoli, A.: Joint reconstruction and registration of a deformable planar surface observed by a 3d sensor. In: 3-D Digital Imaging and Modeling, pp. 201–208 (2007)
Lowe, D.G.: Three-dimensional object recognition from single two-dimensional images. Artificial Intelligence 31(3), 355–395 (1987)
Huber, P.: Robust Statistics. Wiley, New-York (1981)
Levenberg, K.: A method for the solution of certain non-linear problems in least squares. Quart. Appl. Math. 2, 164–168 (1944)
Triggs, B., McLauchlan, P.F., Hartley, R.I., Fitzgibbon, A.W.: Bundle adjustment - a modern synthesis. In: International Conference on Computer Vision, pp. 298–372 (2000)
Bartoli, A., Gay-Bellile, V., Castellani, U., Peyras, J., Olsen, S., Sayd, P.: Coarse-to-fine low-rank structure-from-motion. In: Computer Vision and Pattern Recognition (2008)
Pilet, J., Lepetit, V., Fua, P.: Fast non-rigid surface detection, registration and realistic augmentation. International Journal of Computer Vision 76(2) (2008)
Ramalingam, S., Lodha, S., Sturm, P.: A generic structure-from-motion framework. Computer Vision and Image Understanding 103(3), 218–228 (2006)
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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
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