Summary
In this paper, we propose a real-time method to detect obstacles using theoretical models of the ground plane, first in a 3D point cloud given by a stereo camera, and then in an optical flow field given by one of the stereo pair’s camera.
The idea of our method is to combine two partial occupancy grids from both sensor modalities with an occupancy grid framework. The two methods do not have the same range, precision and resolution. For example, the stereo method is precise for close objects but cannot see further than 7 m (with our lenses), while the optical flow method can see considerably further but has lower accuracy.
Experiments that have been carried on the CyCab mobile robot and on a tractor demonstrate that we can combine the advantages of both algorithms to build local occupancy grids from incomplete data (optical flow from a monocular camera cannot give depth information without time integration).
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References
Barron, J.L., Fleet, D.J., Beauchemin, S.S.: Performance of optical flow techniques. In: IJCV, vol. 12, pp. 43–77 (1994)
Braillon, C., Pradalier, C., Crowley, J.L., Laugier, C.: Real-time moving obstacle detection using optical flow models (2006)
Brox, T., Bruhn, A., Papenberg, N., Weickert, J.: High accuracy optical flow estimation based on a theory for warping, vol. 3024, pp. 25–36 (May 2004)
Bruhn, A., Weickert, J., Feddern, C., Kohlberger, T., Schnorr, C.: Variational optical flow computation in real-time. IEEE Transactions on Image Processing 14(5), 608–615 (2005)
Bruhn, A., Weickert, J., Schnörr, C.: Lucas/kanade meets horn/schunck: Combining local and global optic flow methods 61(3), 211–231 (2005)
Collins, R., Lipton, A., Fujiyoshi, H., Kanade, T.: Algorithms for cooperative multisensor surveillance. In: Proc. of the IEEE, pp. 1456–1477 (October 2001)
Dicksmanns, E.D.: The development of machine vision for road vehicles in the last decade (2002)
Elfes, A.: Using occupancy grids for mobile robot perception and navigation 22(6), 46–57 (1989)
Horn, B.K.P., Schunck, B.G.: Determining optical flow. In: Artificial intelligence, vol. 17, pp. 185–203 (1981)
Ke, Q., Kanade, T.: Transforming camera geometry to a virtual downward-looking camera: robust ego-motion estimation and ground layer detection (2003)
Konolige, K.: Improved occupancy grids for map building 4, 351–367 (1997)
Longuet-Higgins, H.C.: The visual ambiguity of a moving plane. In: Royal Society London, London, Great Britain (1984)
Nelder, J.A., Mead, R.: A simplex method for function minimization, pp. 308–313 (1965)
Stauffer, C., Grimson, W.E.L.: Adaptative background mixture models for real-time tracking (January 1998)
Talukder, A., Matthies, L.: Real-time detection of moving objects from moving vehicle using dense stereo and optical flow (October 2004)
Young-Geun, K., Hakil, K.: Layered ground floor detection fo vision-based mobile robot navigation. In: ICRA, New Orleans, pp. 13–18 (April 2004)
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Braillon, C., Pradalier, C., Usher, K., Crowley, J.L., Laugier, C. (2008). Occupancy Grids from Stereo and Optical Flow Data. In: Khatib, O., Kumar, V., Rus, D. (eds) Experimental Robotics. Springer Tracts in Advanced Robotics, vol 39. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77457-0_34
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DOI: https://doi.org/10.1007/978-3-540-77457-0_34
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