AntVis：基于网络分析蚂蚁移动数据的可视分析工具
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
全文信息
AntVis: A web-based visual analytics tool for exploring ant movement data
BY: Tianxiao Hu, Hao Zheng, Chen Liang, Sirou Zhu, Natalie Imirzian, Yizhe Zhang, Chaoli Wang, David P.Hughes, Danny Z.Chen
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.
Keywords: Ant movement, Object detection, Image segmentation, Visual analytics, Knowledge discovery
Link: https://www.sciencedirect.com/science/article/pii/S2468502X20300036（免费下载）
期刊信息
Visual Informatics（中文名《可视信息学》）是由浙江大学主办、浙江大学出版社和Elsevier出版集团联合出版、在线发行、开放获取的国际学术期刊。该刊聚焦于面向人类感知的视觉信息的建模、分析、合成、增强与自然交互。主编是周昆教授、Hans-Peter Seidel教授。
Elsevier link (including First Online Articles): https://www.journals.elsevier.com/visual-informatics
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