Abstract
This paper describes an algorithm for visually computing the ego-motion of a vehicle relative to the road under the assumption of planar motion. The algorithm uses only images taken by a single omnidirectional camera mounted on the roof of the vehicle. The front ends of the system are two different trackers. The first one is a homography-based tracker that detects and matches robust scale invariant features that most likely belong to the ground plane. The second one uses an appearance based approach and gives high resolution estimates of the rotation of the vehicle. This 2D pose estimation method has been successfully applied to videos from an automotive platform. We give an example of camera trajectory estimated purely from omnidirectional images over a distance of 400 meters. For performance evaluation, the estimated path is superimposed onto an aerial image. In the end, we use image mosaicing to obtain a textured 2D reconstruction of the estimated path.
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References
Moravec, H.: Obstacle Avoidance and Navigation in the Real World by a Seeing Robot Rover. PhD thesis, Stanford University (1980)
Jung, I., Lacroix, S.: Simultaneous localization and mapping with stereovision. In: Robotics Research: The 11th International Symposium (2005)
Nister, D., Naroditsky, O., Bergen, J.: Visual odometry for ground vehicle applications. Journal of Field Robotics (2006)
Maimone, M., Cheng, Y., Matthies, L.: Two years of visual odometry on the mars exploration rovers: Field reports. Journal of Field Robotics 24(3), 169–186 (2007)
Corke, P.I., Strelow, D., Singh, S.: Omnidirectional visual odometry for a planetary rover. In: IROS (2004)
Wang, H., Yuan, K., Zou, W., Zhou, Q.: Visual odometry based on locally planar ground assumption. In: IEEE International Conference on Information Acquisition, pp. 59–64 (2005)
Ke, Q., Kanade, T.: Transforming camera geometry to a virtual downward-looking camera: Robust ego-motion estimation and ground-layer detection. In: CVPR 2003 (June 2003)
Guerrero, J.J., Martinez-Cantin, R., Sagues, C.: Visual map-less navigation based on homographies. Journal of Robotic Systems 22(10), 569–581 (2005)
Liang, B., Pears, N.: Visual navigation using planar homographies. In: IEEE ICRA, pp. 205–210 (2002)
Lowe, D.: Distinctive image features from scale-invariant keypoints. International Journal of Computer Vision 20, 91–110 (2003)
Tsai, R., Huang, T.: Estimating three-dimensional motion parameters of a rigid planar patch. IEEE Trans. Acoustics, Speech and Signal Processing 29(6), 1147–1152 (1981)
Longuet-Higgins, H.C.: The reconstruction of a plane surface from two perspective projections. Royal Society London 277, 399–410 (1986)
Faugeras, O.D., Lustman, F.: Motion and structure from motion in a piecewise planar environment. International Journal of Pattern Recognition and Artificial Inteligence (3), 485–508 (1988)
Fischler, M.A., Bolles, R.C.: Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. Commun. ACM 24(6), 381–395 (1981)
Scaramuzza, D., Martinelli, A., Siegwart, R.: A flexible technique for accurate omnidirectional camera calibration and structure from motion. In: ICVS (january 2006)
Labrosse, F.: The visual compass: performance and limitations of an appearance-based method. Journal of Field Robotics 23(10), 913–941 (2006)
Wunderlich, W.: Rechnerische Rekonstruktion eines ebenen Objekts aus zwei Photographien. Mitteilungen der geodaetischen Institute, TU Graz 40, 365–377 (1982)
Triggs, B.: Autocalibration from planar scenes. In: Burkhardt, H.-J., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1406, pp. 89–105. Springer, Heidelberg (1998)
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Scaramuzza, D., Siegwart, R. (2008). Monocular Omnidirectional Visual Odometry for Outdoor Ground Vehicles. In: Gasteratos, A., Vincze, M., Tsotsos, J.K. (eds) Computer Vision Systems. ICVS 2008. Lecture Notes in Computer Science, vol 5008. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79547-6_20
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DOI: https://doi.org/10.1007/978-3-540-79547-6_20
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