Antone, M.E. and Teller, S. 2000. Automatic recovery of relative camera rotations for urban scenes. In Proc. IEEE Conf. on ComputerVision andPattern Recognition, Hilton Head Island, pp. 282–289.
Besl, P. and McKay,N. 1992.Amethod for registration of 3-D shapes. Trans. PAMI, 14(2).
Brenner, C., Haala, N., and Fritsch, D. 2001.Towards fully automated 3D city model generation. Workshop on Automatic Extraction of Man-Made Objects from Aerial and Space Images III.
Burgard,W., Fox, D., Hennig, D., and Schmidt, T. 1996. Estimating the absolute position of a mobile robot using position probability grids, AAAI.
Chan, R., Jepson,W., and Friedman, S. 1998. Urban simulation: An innovative tool for interactive planning and consensus building. In Proceedings of the 1998 American Planning Association National Conference, Boston, MA, pp. 43–50.
Cox, I.J. 1991. Blanche-An experiment in guidance and navigation of an autonomous robot vehicle. IEEE Transactions on Robotics and Automation
, 7:193–204.Google Scholar
Debevec, P.E., Taylor, C.J., and Malik, J. 1996. Modeling and rendering architecture from photographs. In Proc. of ACM SIGGRAPH.
Dellaert, F., Seitz, S., Thorpe, C., and Thrun, S. 2000. Structure from motion without correspondence. In IEEE Conference on Computer Vision and Pattern Recognition.
Fox, D., Burgard,W., Thrun, S. 1999. Markov localization for mobile robots in dynamic environments.Journal of Artificial Intelligence Research
, 11:391–427.Google Scholar
Fox. D., Thrun, S., Dellaert, F., and Burgard,W. 2000. Particle filters for mobile robot localization. In Sequential Monte Carlo Methods in Practice
, A. Doucet, N. de Freitas, and N. Gordon (Eds.), Springer Verlag, New York.Google Scholar
Früh, C. and Zakhor, A. 2001. Fast 3D model generation in urban environments. In IEEE Conf. on Multisensor Fusion and Integration for Intelligent Systems
, Baden-Baden, Germany, pp. 165–170.Google Scholar
Früh, C. and Zakhor, A. 2001. 3D model generation of cities using aerial photographs and ground level laser scans. Computer Vision and Pattern Recognition
, Hawaii, USA, vol. 2. 2, pp. II-31–8.Google Scholar
Früh, C. and Zakhor, A. 2002. Data processing algorithms for generating textured 3D building facade meshes from laser scans and camera images. In Proc. Int'l Symposium on 3D Processing, Visualization and Transmission 2002
, Padua, Italy, pp. 834–847.Google Scholar
Früh, C. 2002. Automated 3D model generation for urban environments. PhD Thesis, University of Karlruhe, Germany.Google Scholar
Frere, D., Vandekerckhove, J., Moons, T., and Van Gool, L. 1998. Automatic modelling and 3D reconstruction of urban buildings from aerial imagery. In IEEE International Geoscience and Remote Sensing Symposium Proceedings, Seattle, pp. 2593–2596.
Gutmann, J.-S. and Konolige, K. 1999. "Incremental mapping of large cyclic environments. In International Symposium on Computational Intelligence in Robotics and Automation (CIRA'99), Monterey.
Gutmann, J.-S. and Schlegel, C. 1996. Amos: Comparison of scan matching approaches for self-localization in indoor environments. In Proceedings of the 1st Euromicro Workshop on Advanced Mobile Robots.
Hähnel, D., Burgard, W., and Thrun, S. 2001. Learning compact 3D models of indoor and outdoor environments with a mobile robot. 4th European Workshop on Advanced Mobile Robots (EUROBOT' 01).
Huertas, A., Nevatia, R., and Landgrebe, D. 1999. Use of hyperspectral data with intensity images for automatic building modeling. In Proc. of the Second International Conference on Information Fusion
, Sunnyvale, vol. 2, no. 2, pp. 680–687.Google Scholar
Jensfelt, P. and Kristensen, S. 1999. Active global localization for a mobile robot using multiple hypothesis tracking. In Proceedings of the IJCAI Workshop on Reasoning with Uncertainty in Robot Navigation
, pp. 13–22, Stockholm, Sweden, IJCAI.Google Scholar
Kawasaki, H., Yatabe, T., Ikeuchi, K., and Sakauchi, M. 1999. Automatic modeling of a 3D city map from real-world video. In Proceedings ACM Multimedia, Orlando, USA, pp. 11–18.
Koenig, S. and Simmons, R. 1998. A robot navigation architecture based on partially observable Markov decision process models.
Koch, R., Pollefeys, M., and van Gool, L. 1999. Realistic 3D scene modeling from uncalibrated image sequences. ICIP'99, Kobe: Japan, pp. II 500–504.
Konolige, K. and Chou, K. 1999. Markov localization using correlation. In Proc. International Joint Conference on Artificial Intelligence (IJCAI'99), Stockholm.
Lu, F. and Milios, E. 1994. Robot pose estimation in unknown environments by matching 2D range scans. IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
Lu, F. and Milios, E. 1997. Robot pose estimation in unknown environments by matching 2D range scans. Journal of Intelligent and Robotic Systems, 18.
Lu, F. and Milios, E. 1997. Globally consistent range scan alignment for environment mapping.Autonomous Robots
, 4:333–349.Google Scholar
Maas, H.-G. 2001. The suitability of airborne laser scanner data for automatic 3D object reconstruction. Third Int'l Workshop on Automatic Extraction of Man-Made Objects, Ascona, Switzerland.
Roumeliotis, S.I. and Bekey, G.A. 2000. Bayesian estimation and Kalman filtering: A unified framework for mobile robot localization. In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), San Francisco, CA, pp. 2985–2992.
Russell, S.J. and Norvig, P. 1995. Articial Intelligence: A modern approach. Chap. 17, Series in Articial Intelligence, Prentice Hall.
Seitz, S. and Dyer, C. 1997. Photorealistic scene reconstruction by voxel coloring. In Proc. CVPR 1997, pp. 1067–1073.
Simmons, R. and Koenig, S. 1995. Probabilistic robot navigation in partially observable environments. In Proc. of International Joint Conference on Artificial Intelligence
, Montreal, vol. 2, pp. 1080-1087.Google Scholar
Stamos, I. and Allen, P.E. 2000. 3-D model construction using range and image data. In Proceedings IEEE Conf. on Computer Vision and Pattern Recognition, Hilton Head Island, pp. 531–536.
Szeliski, R. and Kang, S. 1995. Direct methods for visual scene reconstruction. IEEEWorkshop on Representation of Visual Scenes, pp. 26–33.
Thrun, S. 2000. Probabilistic algorithms in robotics. AI Magazine, vol. 21, American Assoc. Artificial Intelligence, pp. 93–109.
Thrun, S., Burgard, W., and Fox, D. 2000. A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping. In Proc. of ICRA 2000
, San Francisco, vol. 1, no. 4, pp. 321–328.Google Scholar
Thrun, S., Fox, D., Burgard,W., and Dellaert, F. 2001. Robust Monte Carlo localization for mobile robots. Artificial Intelligence Journal.
Thrun, S. 2001. A probabilistic online mapping algorithm for teams of mobile robots. International Journal of Robotics Research
, 20(5):335–363.Google Scholar
Triggs, B., McLauchlan, P.F., Hartley, R.I., and Fitzgibbon, A.W. 2000.Bundle adjustment-A modern synthesis. In Proc. International Workshop on Vision Algorithms, Corfu, pp. 298–372.
Weiss, G., Wetzler, C., and von Puttkamer, E. 1994. Keeping track of position and orientation of moving indoor systems by correlation of range-finder scans. In Proc. of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
Zhao, H. and Shibasaki, R. 1999. A system for reconstructing urban 3D objects using ground-based range and CCD images. In Proc. of International Workshop on Urban Multi-Media/3D Mapping, Tokyo.