Visual Form pp 29-37 | Cite as

Perception of 3-D Objects by a Robotic Stereo Eye-in-Hand Vision System

  • Massimo A. Arlotti
  • Mario Notturno Granieri


A 3-D machine perception technique is presented using stereo intensity images and an anthropomorphic robot. Multiple stereo views allow the perception of the third dimension by the solution of a correspondence problem defined in two stereo pairs. The zero crossing technique is used to detect edges on the images and to classify them in order to reduce the number of possible solutions. By the eye-in-hand configuration, several stereo pairs of a scene can be taken moving the robot arm. For a limited number of objects, stationary on the robot table, this technique allows the derivation of a set of three-dimensional sample points that correspond to the physical object edges. The technique mainly consist in a geometrical match, in the 3-D space, of some hypothesized solutions formulated on a couple of stereo pairs, taken from two points of view. Considering objects with straight edges and with no highly textured surfaces, some geometrical properties are statistically verified for the most solution points, so the correspondence problem can be robustly solved.


Edge Point Stereo Pair Correspondence Problem Anthropomorphic Robot Image Formation Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. [1]
    V. Cappellini, R. Casini, M.T. Pareschi, C. Raspollini From multiple view to Object Recognition IEEE Trans.on Circuits and Systems, vol. cas-34, n.11, nov.1987.Google Scholar
  2. [2]
    D. Marr, T. Poggio A theory of human stereo vision M.I.T. Tech. Rep. A.P. 451, 1977.Google Scholar
  3. [3]
    D. Marr, T. Poggio A computational theory of human vision Proc.Roy.Soc. London, vol. B204, 1979.Google Scholar
  4. [4]
    H. Itoh, A. Miyauchi, S. Ozawa Distance measuring method using only simple vision constructed for moving robots IEEE Proc. 7th Conf. Pattern Rec, vol.1, Montreal, Canada, 1984.Google Scholar
  5. [5]
    N. Alvertos, D. Brzakovic, R. Gonzalez Camera geometries for Image Matching in 3-D Machine Vision IEEE Trans.on P.A.M.I., vol.11, n.9, September 1989.Google Scholar
  6. [6]
    R.Y. Tsai A versatile camera calibration technique for high accuracy 3-D machine vision metrology using off-the-shelf tv cameras and lenses IEEE J. Robotics and Automation, RA 3, n.4, Aug. 1987.Google Scholar
  7. [7]
    O.D. Faugeras, G. Toscani The calibration problem for stereo Proc. CVPR’86 Miami Beach, Fl, pp. 15-20, 1986.Google Scholar
  8. [8]
    A.C. Kak Depth perception for robots TR-EE 83-44, Purdue University, 1983.Google Scholar

Copyright information

© Springer Science+Business Media New York 1992

Authors and Affiliations

  • Massimo A. Arlotti
    • 1
  • Mario Notturno Granieri
    • 1
  1. 1.IBM Rome Scientific CenterRomaItaly

Personalised recommendations