KUSK Dataset: Toward a Direct Understanding of Recipe Text and Human Cooking Activity

被引:9
作者
Hashimoto, Atsushi [1 ]
Sasada, Tetsuro [2 ]
Yamakata, Yoko [3 ]
Mori, Shinsuke [2 ]
Minoh, Michihiko [2 ]
机构
[1] Kyoto Univ, Grad Sch Law, Sakyo Ku, Yoshida Honmachi, Kyoto 6068501, Japan
[2] Kyoto Univ, Acad Ctr Comp & Media Studies, Sakyo Ku, Kyoto 6068501, Japan
[3] Kyoto Univ, Grad Sch Informat, Sakyo Ku, Kyoto 6068501, Japan
来源
PROCEEDINGS OF THE 2014 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING (UBICOMP'14 ADJUNCT) | 2014年
关键词
Dataset; Multimedia; Text Generation; Activity Recognition;
D O I
10.1145/2638728.2641338
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
In this paper, we provide a multimodal dataset for understanding cooking activities. To build the dataset, we instructed the subjects to perform cooking according to instructional texts shown on a display one by one. The instructional texts were generated from flow graphs, which were automatically extracted from recipes sampled from a Web site. The main identity of this dataset is the correspondence between the steps automatically extracted from recipes, and real human activities. Typical uses of our dataset are to construct classifiers for understanding human activities in the kitchen, text generation through observing the activities, and so on.
引用
收藏
页码:583 / 588
页数:6
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