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AntVis: A web-based visual analytics tool for exploring ant movement data

delete2020-03-01
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OA
AI
T
Tianxiao Hu
H
Hao Zheng *
L
Liang Chen
S
Sirou Zhu
N
Natalie Imirzian
Y
Yizhe Zhang
C
Chaoli Wang
D
David Hughes
D
Danny Z. Chen
DOI:10.1016/j.visinf.2020.02.001delete
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Abstract

Abstract

En 中文
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. (C) 2020 Zhejiang University and Zhejiang University Press. Published by Elsevier B.V.
Keywords:
Ant movement
Object detection
Image segmentation
Visual analytics
Knowledge discovery
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Visual Informatics cover
Visual Informatics
IF:
3.9
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237
Citations:
628

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facebook inc
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588
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C
Carnegie Mellon University
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University of Notre Dame
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pennsylvania commonwealth system of higher education (pcshe)
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