Abstract
This paper presents a system for monocular obstacle and lane boundary detection running in real-time. A Kalman Filter based depth from motion algorithm is used for the reconstruction of the three-dimensional scene. Using multiple filters in parallel the rate of convergence is significantly higher than in direct methods, especially if the vehicle drives slowly. In addition a pitch correction is introduced which improves the overall estimation in typical road scenarios. Real world examples illustrate the results of the proposed system.
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References
Carlsson, S.: Recursive Estimation of Ego-Motion and Scene Structure from a Moving Platform. Proceedings of the 7th Scandinavian Conference on Image Analysis, Aalborg, pp. 958–965, 1991
Franke, U. and Rabe, C: Kalman Filter based Depth from Motion with Fast Convergence. Proceedings of the IEEE Intelligent Vehicles Symposium 2005, Las Vegas, NV, June 2005
Grünewald, M. and Sitte, J.: A Resource-Efficient Approach to Obstacle Avoidance via Optical Flow. Proceedings of the 5th International Heinz Nixdorf Symposium: Autonomous Minirobots for Research and Edutainment, Paderborn, pp. 205–214, October 2001
Matthies, L. and Kanade, T. and Szeliski, R.: Kalman Filter-based Algorithms for Estimating Depth from Image Sequences. International Journal of Computer Vision, Nr. 3, pp. 209–236, 1989
Pollefeys, M.: Self-Calibration and metric 3D reconstruction from uncalibrated image sequences. Leuven, 1999
Tomasi, C. and Kanade, T.: Detection and Tracking of Point Features. Technical Report CMU-CS-91-132, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, April 1991
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© 2006 Springer-Verlag Berlin Heidelberg
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Rabe, C., Volmer, C., Franke, U. (2006). Kalman Filter based Detection of Obstacles and Lane Boundary in Monocular Image Sequences. In: Levi, P., Schanz, M., Lafrenz, R., Avrutin, V. (eds) Autonome Mobile Systeme 2005. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-30292-1_7
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DOI: https://doi.org/10.1007/3-540-30292-1_7
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30291-9
Online ISBN: 978-3-540-30292-6
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