Performance Comparison of Ten Variations on the Interpretation-Tree Matching Algorithm
نویسنده
چکیده
The best known algorithm for symbolic model matching in computer vision is the Interpretation Tree search algorithm. This algorithm has a high computational complexity when applied to matching problems with large numbers of features. This paper examines ten variations of this algorithm in a search for improved performance, and concludes that the non-wildcard and hierarchical algorithms have reduced theoretical complexity and run faster than the standard algorithm.
منابع مشابه
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تاریخ انتشار 1994