Abstract
In this paper we present a method for mapping 3D unknown environments from stereo images. It is based on a dense disparity image obtained by a process of window correlation. To each image in the sequence a geometrical rectification process is applied, which is essential to remove the conical perspective of the images obtained with a photographic camera. This process corrects the errors in coordinates x and y to obtain a better matching for the map information. The mapping method is an application of the geometrical rectification and the 3D reconstruction, whose main purpose is to obtain a realistic appearance of the scene.
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References
Sanchiz, J.M., Fisher, R.B.: Viewpoint Estimation in Three-Dimensional Images Taken with Perspective Range Sensors. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(11), 1324–1329 (2000)
Moravec, H.P.: Robot spatial perception by stereoscopic vision and 3D evidence grids. The Robotics Institute Carnegie Mellon University. Pittsburgh, Pennsylvania (1996)
Se, S., Lowe, D., Little, J.: Vision-based mobile robot localization and mapping using scale-invariant features. In: Proc. of IEEE International Conference on Robotics and Automation, Seoul, Korea (2001)
Martin, C., Thrun, S.: Real-time acquisition of compact volumetric maps with mobile robots. In: Proceedings of ICRA 2002: IEEE International Conference on Robotics and Automation (2002)
Martinsanz, G.P., de la Cruz García, J.M.: Visión por computador: imágenes digitales y aplicaciones. In: Ra-Ma, D.L. (ed.), Madrid (2001)
Broggi, A.: Robust Real-Time Lane and Road Detection in Critical Shadow Conditions. In: Proceedings IEEE International Symposium on Computer Vision, Coral Gables, Florida. IEEE Computer Society, Los Alamitos (1995)
Trucco, E., Verri, A.: Introductory techniques for 3-D Computer Vision. Prentice Hall, Englewood Cliffs (1998)
Cox, I., Ignoran, S., Rao, S.: A maximum lilelihood stereo algorithm. Computer Vision and Image Understanding 63 (1996)
Faugeras, O.: Three-dimensional computer vision: a geometric viewpoint. The MIT Press, Cambridge (1993)
Compañ, P., Satorre, R., Rizo, R.: Disparity estimation in stereoscopic vision by simulated annealing. In: Artificial Intelligence research and development, pp. 160–167. IOS Press, Amsterdam (2003)
Compañ, P., Satorre, R., Rizo, R., Molina, R.: Inproving depth estimation using colour information in stereo vision. In: IASTED International Conference on Visualization, Imaging and Image Processing (VIIP 2005), Benidorm (Spain), pp. 377–389 (2005)
Sánchez, A.J.G., Carmona, R.M., Arnedo, C.V.: Scene reconstruction and geometrical rectification from stereo images. In: World Multi-Conference on Systemics, Cybernetics and Informatics (WMSCI), Orlando (2005)
Sánchez, A.J.G., Carmona, R.M., Arnedo, C.V.: Discrete and Continuous Reconstruction of 3D Scenes from Disparity Maps. In: IASTED International Conference on Visualization, Imaging, and Image Processing, Benidorm (Spain), pp. 366–371 (2005)
Pollefeys, M., Koch, R., Van Gool, L.: A simple and efficient rectification method for general motion. In: Proc. International Conference on Computer Vision, Corfu (Greece), pp. 496–501 (1999)
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© 2006 Springer-Verlag Berlin Heidelberg
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Sánchez, A.J.G., Carmona, R.M., Arnedo, C.V. (2006). Three-Dimensional Mapping from Stereo Images with Geometrical Rectification. In: Perales, F.J., Fisher, R.B. (eds) Articulated Motion and Deformable Objects. AMDO 2006. Lecture Notes in Computer Science, vol 4069. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11789239_22
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DOI: https://doi.org/10.1007/11789239_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36031-5
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