This Article 
 Bibliographic References 
 Add to: 
Sampling of Images for Efficient Model-Based Vision
January 1999 (vol. 21 no. 1)
pp. 4-11

Abstract—The problem of matching two planar sets of points in the presence of geometric uncertainty has important applications in pattern recognition, image understanding, and robotics. The first set of points corresponds to the "template." The other set corresponds to the "image" that—possibly—contains one or more deformed versions of the "template" embedded in a cluttered image. Significant progress has been made on this problem and various polynomial-time algorithms have been proposed. In this article, we show how to sample the "image" in linear time, reducing the number of foreground points n by a factor of two-six (for commonly occurring images) without degrading the quality of the matching results. The direct consequence is a time-saving by a factor of 2p−6p for an O(np) matching algorithm. Our result applies to a fairly large class of available matching algorithms.

[1] H.S. Baird, Model-Based Image Matching Using Location. Cambridge, Mass.: MIT Press, 1985.
[2] A.C. Cass,“Feature matching for object localization in the presence of uncertainty,” Proc. 3rd Int’l Conf. on Comp. Vis.,Osaka, 1991, pp. 360–364.
[3] T. Cass, "Polynomial-Time Geometric Matching for Object Recognition," PhD dissertation, Massachusetts Institute of Tech nology, 1992.
[4] T. Cass, "Robust Affine Structure Matching for 3D Object Recognition," Fourth European Conf. on Computer Vision, vol. 1, pp. 492-503, Apr. 1996.
[5] B. Chazelle, "The Polygon Containment Problem," Advances in Computing Research, vol. 1, pp. 1-33, 1983.
[6] T. Breuel, "Geometric Aspects of Visual Object Recognition," PhD dissertation, Massachusetts Institute of Tech nology, 1992.
[7] D. Huttenlocher and K. Kedem, "Computing the Minimum Hausdorff Distance of Point Sets Under Translation," Sixth ACM Symp. Computational Geometry, vol. 1, pp. 340-349, 1990.
[8] D.P. Huttenlocher and S. Ullman, “Recognizing Solid Objects by Alignment with an Image,” Int'l J. Computer Vision, vol. 5, no. 2, pp. 195-212, 1990.
[9] D. Huttenlocher, G. Klanderman, and W. Rucklidge, "Comparing Images Using the Hausdorff Distance Under Translation," Proc. IEEE Computer Vision and Pattern Recognition, pp. 654-656, 1992.
[10] X. Yi and O. Camps, "Line Feature-Based Recognition Using Hausdorff Distance," Proc. Int'l Symp. Computer Vision, pp. 79-84, 1995.

Index Terms:
Sampling, model-based vision, matching under uncertainty, approximate matching, image understanding.
Mohamad Akra, Louay Bazzi, Sanjoy Mitter, "Sampling of Images for Efficient Model-Based Vision," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, no. 1, pp. 4-11, Jan. 1999, doi:10.1109/34.745729
Usage of this product signifies your acceptance of the Terms of Use.