一种基于显著性排序的骨架剪枝方法

Guo Siyu, Huang Pingping, L. Zhigang, Wen He, Liu Min
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引用次数: 1

摘要

虚假骨架的修剪是将骨架应用于目标分析和识别的一个重要问题。现有的剪枝方法大多采用类阈值参数来控制剪枝效果。这种方法通常在参数调整和剪枝质量方面遇到困难。本文提出了一种骨架剪枝方法。该方法将骨骼分解为许多骨骼成分(SCs),并根据显着性测量逐个去除末端sc。每次移除SCs后,SCs可能合并成一个新的SCs。去除过程继续进行,直到达到所需数量的终端。该方法本质上可以看作是对终端进行排序,对给定数量的终端进行截断。这种方法适用于可以预先确定所需端子数量的应用。实验结果表明,该方法可以有效地从测试图像基中剔除骨架,并且终端数参数非常直观,易于设置,适用于相关应用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A skeleton pruning method based on saliency sorting
The pruning of spurious skeletons is an important issue when apply skeletons for object analysis and recognition. Most existing pruning methods use threshold-like parameter to control the effects of pruning. Such approaches usually encounter difficulties in parameter tuning and the quality of pruning. A skeleton pruning method is proposed in this work. This method decomposes a skeleton into a number of skeletal components (SCs), and the terminal SCs are removed one by one according to a saliency measure. SCs may be merged into a new one after each removal. The removal process continues until the desirable number of terminals are achieved. The method can essentially be regarded as the sorting of the terminals, and the truncation of the terminals at the given number. This method is suitable for applications where the desired number of terminals can be determined a priori. Experimental results show that the method can effectively prune the skeletons from the test image bases, and it has the advantage that the terminal number parameter is very intuitive and easy to set for the applications under concern.
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