Abstract
In mobile robotics, the inference of the 3D layout of large-scale indoor environments is a critical problem for achieving exploration and navigation tasks. This article presents a framework for building a 3D model of an indoor environment from partial data using a mobile robot. The modeling of a large-scale environment involves the acquisition of a huge amount of range data to extract the geometry of the scene. This task is physically demanding and time consuming for many real systems. Our approach overcomes this problem by allowing a robot to rapidly collect a set of intensity images and a small amount of range information. The method integrates and analyzes the statistical relationships between the visual data and the limited available depth on terms of small patches and is capable of recovering complete dense range maps. Experiments on real-world data are given to illustrate the suitability of our approach.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Cobzas, D.: Image-Based Models with Applications in Robot Navigation. PhD thesis, University of Alberta, Canada (2003)
Fitzgibbon, A.W., Zisserman, A.: Automatic 3d model acquisition and generation of new images from video sequences. In: Proceedings of European Signal Processing Conference, pp. 1261–1269 (1998)
Freeman, W.T., Pasztor, E.C., Carmichael, O.T.: Learning low-level vision. International Journal of Computer Vision 20(1), 25–47 (2000)
Hammersley, J.M., Clifford, P.: Markov field on finite graphs and lattices (unpublished, 1971)
Kuipers, B.: Modelling spatial knowledge. Cognitive Science 2, 1153–1291 (1978)
Lee, A., Pedersen, K., Mumford, D.: The complex statistics of high-contrast patches in natural images, private correspondence (2001)
Levoy, M., Pulli, K., Curless, B., Rusinkiewicz, S., Koller, D., Pereira, L., Ginzton, M., Anderson, S., Davis, J., Ginsberg, J., Shade, J., Fulk, D.: The digital michelangelo project: 3d scanning of large statues. In: SIGGRAPH (July 2000)
Little, J.J., Gillett, W.E.: Direct evidence for oclussion in stereo and motion. Image and Vision Computing 8, 328–340 (1990)
Murray, D., Little, J.J.: Using real-time stereo vision for mobile robot navigation. Autonomous Robots 8(2), 161–171 (2000)
Nyland, L., McAllister, D., Popescu, V., McCue, C., Lastra, A., Rademacher, P., Oliveira, M., Bishop, G., Meenakshisundaram, G., Cutts, M., Fuchs, H.: The impact of dense range data on computer graphics. In: Proceedings of Multi-View Modeling and Analysis Workshop (MVIEW part of CVPR), June 1999, p. 8 (1999)
Pollefeys, M., Koch, R., Vergauwen, M., Van Gool, L.: Metric 3d surface reconstruction from uncalibrated images sequences. In: Proceedings of SMILE Workshop (post-ECCV), pp. 138–153 (1998)
Stamos, I., Allen, P.K.: 3d model construction using range and image data. In: CVPR (June 2000)
Abril Torres-Méndez, L.: Statistics of Visual and Partial Depth Data for Mobile Robot Environment Modeling. PhD thesis, McGill University (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Torres-Méndez, L.A., Dudek, G. (2006). Statistics of Visual and Partial Depth Data for Mobile Robot Environment Modeling. In: Gelbukh, A., Reyes-Garcia, C.A. (eds) MICAI 2006: Advances in Artificial Intelligence. MICAI 2006. Lecture Notes in Computer Science(), vol 4293. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11925231_68
Download citation
DOI: https://doi.org/10.1007/11925231_68
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49026-5
Online ISBN: 978-3-540-49058-6
eBook Packages: Computer ScienceComputer Science (R0)