Some trade-offs and a new algorithm for geometric hashing

Model-based object recognition is a fundamental task of computer vision. In this paper we consider the performance of the popular geometric hashing (GH) algorithm for model based recognition and, in a probabilistic setting, examine the influence of some design decisions and derive several trade-offs between two measures of performance: reliability and time complexity. We also propose a variation of the GH algorithm, which alleviates some of its inherent problems and demonstrate its enhanced performance in experiments.

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