Fundamentals of Mathematics, Volume II: Geometry by H. Behnke, F. Bachmann, K. Fladt, W. Süss, H. Kunle, S. H.

By H. Behnke, F. Bachmann, K. Fladt, W. Süss, H. Kunle, S. H. Gould

Quantity II of a distinct survey of the entire box of natural mathematic

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2 Interpretation of RADAR Noise . . . . . . . . . . . . . . . 1 Thermal noise . . . . . . . . . . . . . . . . . . . 2 Phase noise . . . . . . . . . . . . . . . . . . . . . 3 Noise Analysis during Target Absence and Presence . . . . 1 Power-noise estimation in target absence . . . . . 2 Power-noise estimation in target presence . . . . 4 Initial Range Spectra Prediction . . . . . . . .

After that, the range data are transformed from angular to Cartesian (x-y-z) coordinates. Feature extraction and clustering. Surface normals are calculated from x-y-z points. Normals are clustered into patches with similar normal orientations. Region growth is used to expand the patches until the fitting error is larger than a given threshold. The smoothness of a patch is evaluated by fitting a surface (plane or quadric). Defect detection. Flat, traversable surfaces will have vertical surface normals.

6. N. Zeng and J. D. Crisman. Categorical color projection for robot road following. In Proceedings of 12th International Conference on Robotics and Automation, pp. 1080–1085, 1995. 7. J. D. Crisman and C. E. Thorpe. Scarf: a color vision system that tracks roads and intersections. IEEE Transactions on Robotics and Automations, 9: 49–58, 1993. 8. C. Geyer and K. Daniilidis. A unifying theory for central panoramic systems and practical applications. In ECCV (2), pp. 445–461. Springer-Verlag, Heidelberg, 2000.

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