Sketch-based manga retrieval using manga109 dataset
Sketch-based manga retrieval using manga109 dataset
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DOI：
10.1007/s11042-016-4020-z
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发表时间：
2017-10-01
影响因子：
3.6
通讯作者：
Aizawa, Kiyoharu
中科院分区：
文献类型：
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作者：
Matsui, Yusuke;Ito, Kota;Aizawa, Kiyoharu
漫画（日本漫画）在世界范围内流行。但是，当前的e-manga档案提供了非常有限的搜索支持，即按标题或作者进行基于关键字的搜索。为了使漫画搜索更加直观，高效和愉悦，我们提出了一个漫画特定的图像检索系统。所提出的系统包括有效的边距标签，使用产品量化的边缘方向直方图特征描述以及屏幕音调的去除以及近似最近的邻居搜索。为了查询，系统提供了基于草图的接口。基于接口，提出了两个交互式的重新计算方案：相关反馈和查询修饰。为了进行评估，我们构建了一个新颖的漫画图像数据集，即Manga109，其中包括109本由专业漫画艺术家绘制的21,142页的漫画书。据我们所知，Manga109目前是可用于研究的最大漫画图像数据集。实验结果表明，所提出的框架是有效且可扩展的（使用204 MB RAM的一台计算机，从21,142页开始）。
Manga (Japanese comics) are popular worldwide. However, current e-manga archives offer very limited search support, i.e., keyword-based search by title or author. To make the manga search experience more intuitive, efficient, and enjoyable, we propose a manga-specific image retrieval system. The proposed system consists of efficient margin labeling, edge orientation histogram feature description with screen tone removal, and approximate nearest-neighbor search using product quantization. For querying, the system provides a sketch-based interface. Based on the interface, two interactive reranking schemes are presented: relevance feedback and query retouch. For evaluation, we built a novel dataset of manga images, Manga109, which consists of 109 comic books of 21,142 pages drawn by professional manga artists. To the best of our knowledge, Manga109 is currently the biggest dataset of manga images available for research. Experimental results showed that the proposed framework is efficient and scalable (70 ms from 21,142 pages using a single computer with 204 MB RAM).