Scientific and Technical Journal


ISSN Print 2221-3937
ISSN Online 2221-3805

Overviewed technical vision unit usage for solving walking robot's navigational task and, also, determination of the robot's angular orientation relative to observed scene. Shown, that single moving camera can be used for a stereo image acquisition with future computation of optical flow, instead of rigid stereo-camera module. That allows to minimize computational requirements of the data transfer unit. Shown basic overview of the robot's kinematic model and walking principle. Described general task of optical flow computation. Provided overview of optical flow computation principle and results of quantitative comparison of nine different techniques, including instances of differential methods, region-based matching energy-based and phase-based techniques namely those of Horn and Schunck, Lucas and Kanade, Uras et al., Nagel, Anandan, Singh, Heeger, Waxman et al. and Fleet and Jepson. Shown Lucas-Kanade approach for optical flow computation technique. Provided general principle and implementation for obstacle avoidance basing on optical flow technique, provided quantitative results implemented in current robot. Shown next stages of obstacle avoidance: obstacle detection by means of optical flow relative velocities threshold ; distance to the obstacle determination by means of known stereo-image parameters; obstacle relative speed determination by means of optical flow of obstacle and it's direction and position; obstacle size, also by means of optical flow and known configuration of scene, and relative to robot angular position by means of optical eigenvectors computation with future differentiation and solving Poisson's equation.

  1. Horn, B. K. P., (1986) Robot Vision. MIT Press, Cambridge
  2. Verri, A., Poggio, T., (1987) Against quantitative optical flow. Proc. IEEE ICCV, London,    pp. 171–180
  3. Schunck, B. G., (1986) Image flow continuity equations for motion and density. Proc. IEEE Workshop on Visual Motion, Charleston, pp. 89–94
  4. Lucas, B.D., (1984) Generalized Image Matching by the Method of Differences. PhD Dissertation, Dept. of Computer Science, Carnegie-Mellon University
  5. Uras, S., Girosi, F., Verri, A., Torre, V., (1988) A computational approach to motion perception. Biol. Cybern. 60, pp. 79–97
  6. Singh, A., (1990) An estimation-theoretic framework for image flow computation. Proc. IEEE ICCV, Osaka, pp. 168–177
  7. Little, J. J., Verri A., (1989) Analysis of differential and matching methods for optical flow. IEEE Workshop on Visual Motion, Irvine CA,      pp. 173–180
  8. Batavia, P., Singh, S., (2002) Obstacle detection in smooth high curvature terrain. In Proceedings of the IEEE Conference on Robotics and Automation (ICRA ’02)
  9. Matthies, L., Kelly, A., Litwin, T., Tharp, G. (1996) Obstacle detection for unmanned ground vehicles: a progress report. Robotics Research 7, Springer-Verlag.
  10. Wolff, L., (1996) Polarization phased-based method for material classification and object recognition in computer vision. In IEEE Conf. Computer Vision and Pattern Recognition.
  11. Zhang, Z., Weiss, R., Hanson, A.R., (1994) Qualitative obstacle detection. In IEEE Conf. Computer Vision and Pattern Recognition,            pp. 554–559.
  12. Boufama, B., Mohr, R., (1995) Epipole andfundamental matrix estimation using the virtual parallax property, Proceedings of the 5th International Conference on Computer Vision, IEEE Computer Society Press, Boston, MA, pp. 1030–1036
  13. Barron, J. L., Fleet, D. J., Beauchemin, S. S., (1994) Performance of optical flow techniques. International Journal of Computer Vision 12 (1), рр. 43–77
  14. Fleet, D. J., Weiss, Y., (2006) Optical flow estimation. Handbook of Mathematical Models in Computer Vision, рр. 237–257
  15. Kearney, J. K., Thompson, W. B., Boley D. L., (1997) Optical flow estimation: An error analysis of gradient-based methods with local optimisation. IEEE Trans. on PAMI 9, pp. 229–244
  16. Willick, D., Yang Y. H., (1991) Experimental evaluation of motion constraints equations. CVGIP: Image Understanding, 54, pp. 206–214
  17. Horn, B. K. P., Schunck, B. G., (1981) Determining optical flow. AI 17, pp. 185–204
  18. Schunck, B. G., (1984) The motion constraint equation for optical flow. Proc. ICPR Montreal, pp. 20–22
  19. Nagel, H. H., (1989) On a constraint equation for the estimation of displacement rates in image sequences. IEEE Trans. PAMI 11, pp. 13–30
  20. Lucas, B., Kanade, T., (1981) An iterative image registration technique with an application to stereo vision. Proc. DARPA IU Workshop,          pp. 121–130
  21. Nagel, H. H., (1987) On the estimation of optical flow. Relations between different approaches and some new results. AI 33, pp. 299–324
  22. Ancona, N., (1992) A fast obstacle detection method based on optical flow. In Proceedings of ECCV, pages 267–271, Santa Mangherita Ligure, Italy
  23. Barman, H., Haglund, L., Knutsson, H., Granlund, G. H. (1992) Estimation of velocity, acceleration and disparity in time sequences. In IEEE Proceedings of Workshop on Visual Motion, pages 44-51, Irvine, California
  24. Singh, A., (1992) Optic Flow Computation A Unied Perspective. IEEE Computer Society Press
  25. Heeger, D. J., (1988) Optical flow using spatiotemporal filters. Int. J. Comp. Vision 1,        pp. 279–302
  26. Waxman, A. M., Wu, J., Bergholm, F., (1988) Convected activation profiles and receptive fields for real time measurement of short range visual motion. Proc. IEEE CVPR, Ann Arbor,            pp. 717–723
  27. Fleet, D. J., Jepson, A. D., (1990) Computation of component image velocity from local phase information. Int. J. Comp. Vision 5, pp. 77–104
  28. Fleet, D. J., (1992) Measurement of Image Velocity. Kluwer Academic Publishers, Norwell
  29. Camera Calibration Toolbox for Matlab. Available online: bouguetj/calib_doc/.
  30. Pratt, W. K., (2007) Digital Image Processing; John Wiley & Sons: Hoboken, NJ, USA
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