Adaptive low resolution pruning for fast full search-equivalent pattern matching
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摘要Several recent proposals have shown the feasibility of significantly speeding-up pattern matching by means of Full Search-equivalent techniques, i.e. without approximating the outcome of the search with respect to a brute force investigation. These techniques are generally heavily based on efficient incremental calculation schemes aimed at avoiding unnecessary computations. In a very recent and extensive experimental evaluation, Low Resolution Pruning turned out to be in most cases the best performing approach. In this paper we propose a computational analysis of several incremental techniques specifically designed to enhance the efficiency of LRP. In addition, we propose a novel LRP algorithm aimed at minimizing the theoretical number of operations by adaptively exploiting different incremental approaches. We demonstrate the effectiveness of our proposal by means of experimental evaluation on a large dataset. © 2011 Elsevier B.V. All rights reserved.
著者Tombari F., Ouyang W., Di Stefano L., Cham W.-K.
期刊名稱Pattern Recognition Letters
出版年份2011
月份11
日期1
卷號32
期次15
出版社Elsevier BV
出版地Netherlands
頁次2119 - 2127
國際標準期刊號0167-8655
電子國際標準期刊號1872-7344
語言英式英語
關鍵詞Full Search-equivalent, Low Resolution Pruning, Pattern matching, Template matching

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