Sketch Classification and Classification-driven Analysis using Fisher Vectors
Sketch Classification and Classification-driven Analysis using Fisher Vectors
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DOI：
10.1145/2661229.2661231
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发表时间：
2014-11-01
影响因子：
6.2
通讯作者：
Tuytelaars, Tinne
中科院分区：
文献类型：
--
作者：
Schneider, Rosalia G.;Tuytelaars, Tinne
我们介绍了一种基于Fisher向量的草图分类方法，该方法显著优于现有的技术。对于TU-Berlin草图基准[Eitz et al. 2012 a]，我们的识别率接近人类在相同任务中的表现。出于这些结果，我们提出了一个不同的基准评估草图分类算法。我们的核心思想是，识别草图时的相关方面不是绘制者的意图，而是有效表达的信息。我们修改了原来的基准，以更精确地捕捉这个概念，因此，提供了一个更充分的工具，草图分类技术的评估。最后，我们进行分类驱动的分析，这是能够恢复单个草图的语义方面，如图纸的质量和识别的草图的每个部分的重要性。
We introduce an approach for sketch classification based on Fisher vectors that significantly outperforms existing techniques. For the TU-Berlin sketch benchmark [Eitz et al. 2012a], our recognition rate is close to human performance on the same task. Motivated by these results, we propose a different benchmark for the evaluation of sketch classification algorithms. Our key idea is that the relevant aspect when recognizing a sketch is not the intention of the person who made the drawing, but the information that was effectively expressed. We modify the original benchmark to capture this concept more precisely and, as such, to provide a more adequate tool for the evaluation of sketch classification techniques. Finally, we perform a classification-driven analysis which is able to recover semantic aspects of the individual sketches, such as the quality of the drawing and the importance of each part of the sketch for the recognition.