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Vis Inf  2020, Vol. 4 Issue (1): 58-70    DOI: 10.1016/j.visinf.2020.02.001
论文     
AntVis:基于网络分析蚂蚁移动数据的可视分析工具
Tianxiao Hua, Hao Zhengb, Chen Liangc, Sirou Zhuc, Natalie Imirziand, Yizhe Zhangb, Chaoli Wangb, David P.Hughesd, Danny Z.Chenb
aFacebook, Inc., Menlo Park, CA 94025, United States bUniversity of Notre Dame, Notre Dame, IN 46556, United States  cCarnegie Mellon University, Pittsburgh, PA 15213, United States  dPennsylvania State University, University Park, PA 16802, United States
AntVis: A web-based visual analytics tool for exploring ant movement data
Tianxiao Hua, Hao Zhengb, Chen Liangc, Sirou Zhuc, Natalie Imirziand, Yizhe Zhangb, Chaoli Wangb, David P.Hughesd, Danny Z.Chenb
aFacebook, Inc., Menlo Park, CA 94025, United States bUniversity of Notre Dame, Notre Dame, IN 46556, United States  cCarnegie Mellon University, Pittsburgh, PA 15213, United States  dPennsylvania State University, University Park, PA 16802, United States
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摘要: 本文介绍了一种基于网络的可视分析工具——AntVis,用于分析蚂蚁在树枝上移动的视频数据。我们的目标是使该领域的专家能够观察探究大量的蚂蚁移动数据并通过有效的可视化、过滤和比较,获得有价值的见解。为了实现这一目标,我们构建了一个深度学习框架,对视频中的蚂蚁进行自动检测、分割和标记,对轨迹相似的蚂蚁移动数据进行聚类,并设计和开发了五个协同视图(分别对应移动、相似性、时间线、统计和属性)以便用户交互和分析。 通过与这一领域内的专家合作,我们开发了多个案例,验证了AntVis的有效性。 最后,提供了一份来自昆虫学家的评估报告,并给出了未来的研究方向。
关键词: 蚂蚁移动目标检测图像分割可视分析知识发现    
Abstract: We present AntVis, a web-based visual analytics tool for exploring ant movement data collected from the video recording of ants moving on tree branches. Our goal is to enable domain experts to visually explore massive ant movement data and gain valuable insights via effective visualization, filtering, and comparison. This is achieved through a deep learning framework for automatic detection, segmentation, and labeling of ants, ant movement clustering based on their trace similarity, and the design and development of five coordinated views (the movement, similarity, timeline, statistical, and attribute views) for user interaction and exploration. We demonstrate the effectiveness of AntVis with several case studies developed in close collaboration with domain experts. Finally, we report the expert evaluation conducted by an entomologist and point out future directions of this study.
Key words: Ant movement    Object detection    Image segmentation    Visual analytics    Knowledge discovery
出版日期: 2020-03-17
通讯作者: Tianxiao Hu     E-mail: tianxiaohu@fb.com
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Tianxiao Hu
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引用本文:

Tianxiao Hu, Hao Zheng, Chen Liang, Sirou Zhu, Natalie Imirzian, Yizhe Zhang, Chaoli Wang, David P.Hughes, Danny Z.Chen. AntVis: A web-based visual analytics tool for exploring ant movement data . Vis Inf, 2020, 4(1): 58-70.

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http://www.zjujournals.com/vi/CN/10.1016/j.visinf.2020.02.001        http://www.zjujournals.com/vi/CN/Y2020/V4/I1/58

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