A Hierarchical Task Assignment for Manual Image Labeling

Chia Ming Chang, Siddharth Deepak Mishra, Takeo Igarashi

研究成果: Conference contribution同行評審

9 引文 斯高帕斯(Scopus)

摘要

Manual image labeling (selecting an appropriate 'category' for an image) is very tedious and time consuming especially when selecting labels from a large number of categories. In this study, we propose a hierarchical assignment of labeling tasks where the labelers recursively classify images in a category group into sub category groups, working on a single level at a time. This significantly makes each labeler's task easier, reducing the number of choices from 1,000 to 27 on average. In the user study, we compared our hierarchical assignment to a normal (non-hierarchical) assignment for a labeling task. The results show that the hierarchical assignment requires less total time to complete the labeling task. In addition, the learning effect in the labeling process is more profound in the hierarchical assignment.

原文English
主出版物標題Proceedings - 2019 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2019
編輯Justin Smith, Christopher A. Bogart, Judith Good, Scott D. Fleming
發行者IEEE Computer Society
頁面139-143
頁數5
ISBN(電子)9781728108100
DOIs
出版狀態Published - 10月 2019
事件2019 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2019 - Memphis, United States
持續時間: 14 10月 201918 10月 2019

出版系列

名字Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC
2019-October
ISSN(列印)1943-6092
ISSN(電子)1943-6106

Conference

Conference2019 IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC 2019
國家/地區United States
城市Memphis
期間14/10/1918/10/19

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