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 a...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.展开更多
基金the US National Science Foundation through grants IIS-1456763,IIS-1455886,CNS-1629914,CCF-1617735,and DUE-1833129the US National Institutes of Health through grant R01 GM116927.T.Hu,S.Zhu,and C.Liang conducted this work as iSURE(International Summer Undergraduate Research Experience)students at the University of Notre Dame during Summer 2017.
文摘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.
