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Recognition and autocompletion of partially drawn symbols by using polar histograms as spatial relation descriptors

机译:通过使用极坐标直方图作为空间关系描述符来识别和自动填充部分绘制的符号

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We present an approach for recognizing multi-stroke hand-drawn symbols. The main feature of the approach is its capacity of recognizing partially drawn symbols. Furthermore, it is invariant with respect to scale, and supports symbol recognition independently from the number and order of strokes. The recognition technique is based on subgraph isomorphism and exploits a novel spatial descriptor, based on polar histograms, to represent relations between two stroke primitives. Using different symbol sets, both hand-drawn and artificially deformed, we evaluated the effectiveness of the approach in recognizing the symbols as a function of the number of primitives already drawn by the users. The results show that the approach gives a satisfactory recognition rate with partially drawn symbols, also with a very low level of drawing completion, and outperforms the existing approaches proposed in the literature. We also report the results of a user study aimed at evaluating whether the users can efficiently exploit symbol autocompletion.
机译:我们提出一种识别多冲程手绘符号的方法。该方法的主要特征是其识别部分绘制的符号的能力。此外,它在比例方面是不变的,并且支持与笔划的数量和顺序无关的符号识别。识别技术基于子图同构,并利用基于极性直方图的新颖空间描述符来表示两个笔划基元之间的关系。使用手绘和人工变形的不同符号集,我们根据用户已经绘制的图元数量评估了该方法在识别符号方面的有效性。结果表明,该方法在部分绘制符号的情况下也具有令人满意的识别率,并且绘制完成的水平也非常低,并且优于文献中提出的现有方法。我们还报告了旨在评估用户是否可以有效利用符号自动完成功能的用户研究结果。

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