Matching of road segments using probabilistic relaxation: reducing the computational requirements

William J. Christmas; Josef Kittler; Maria Petrou

doi:10.1117/12.179601

13 July 1994 Matching of road segments using probabilistic relaxation: reducing the computational requirements

William J. Christmas, Josef Kittler, Maria Petrou

Proceedings Volume 2220, Sensing, Imaging, and Vision for Control and Guidance of Aerospace Vehicles; (1994) https://doi.org/10.1117/12.179601
Event: SPIE's International Symposium on Optical Engineering and Photonics in Aerospace Sensing, 1994, Orlando, FL, United States

Abstract

In previous work we presented an algorithm for matching features extracted from an image with those extracted from a model, using a probabilistic relaxation method. Because the algorithm compares each possible match with all other possible matches, the main obstacle to its use on large data sets is that both the computation time and the memory usage are proportional to the square of the number of possible matches. This paper describes some improvements to the algorithm to alleviate these problems. The key sections of the algorithm are the generation, storage, and use of the compatibility coefficients. We describe three different schemes that reduce the number of these coefficients. The execution time is improved in each case, even when the number of iterations required for convergence is greater than in the unmodified algorithm. We show that the new methods also perform well, generating good matches in all cases.

Citation Download Citation

William J. Christmas, Josef Kittler, and Maria Petrou "Matching of road segments using probabilistic relaxation: reducing the computational requirements", Proc. SPIE 2220, Sensing, Imaging, and Vision for Control and Guidance of Aerospace Vehicles, (13 July 1994); https://doi.org/10.1117/12.179601

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