Approaches and Challenges in the Visual-Interactive Comparison of Human Motion Data

Jürgen Bernard, Anna Vögele, Reinhard Klein und D. Fellner
In proceedings of Proceedings of the 8th International Conference on Information Visualization Theory and Applications, IVAPP 2017, 2017
 

Abstract

Many analysis goals involving human motion capture (MoCap) data require the comparison of motion patterns. Pioneer works in visual analytics recently recognized visual comparison as substantial for visual-interactive analysis. This work reflects the design space for visual-interactive systems facilitating the visual comparison of human MoCap data, and presents a taxonomy comprising three primary factors, following the general visual analytics process: algorithmic models, visualizations for motion comparison, and back propagation of user feedback. Based on a literature review, relevant visual comparison approaches are discussed. We outline remaining challenges and inspiring works on MoCap data, information visualization, and visual analytics.

Stichwörter: Data Mining, Human Motion Capture Data, Human-Computer Interaction, Information Retrieval, Information Visualization, Machine Learning, Motion Capture Analysis, visual analytics, Visual Comparison

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Bibtex

@INPROCEEDINGS{bernard2017b,
     author = {Bernard, J{\"u}rgen and V{\"o}gele, Anna and Klein, Reinhard and Fellner, D.},
      title = {Approaches and Challenges in the Visual-Interactive Comparison of Human Motion Data},
    journal = {IVAPP},
  booktitle = {Proceedings of the 8th International Conference on Information Visualization Theory and
               Applications, IVAPP 2017},
       year = {2017},
   keywords = {Data Mining, Human Motion Capture Data, Human-Computer Interaction, Information Retrieval,
               Information Visualization, Machine Learning, Motion Capture Analysis, visual analytics, Visual
               Comparison},
   abstract = {Many analysis goals involving human motion capture (MoCap) data require the comparison of motion
               patterns. Pioneer works in visual analytics recently recognized visual comparison as substantial for
               visual-interactive analysis. This work reflects the design space for visual-interactive systems
               facilitating the visual comparison of human MoCap data, and presents a taxonomy comprising three
               primary factors, following the general visual analytics process: algorithmic models, visualizations
               for motion comparison, and back propagation of user feedback. Based on a literature review, relevant
               visual comparison approaches are discussed. We outline remaining challenges and inspiring works on
               MoCap data, information visualization, and visual analytics.}
}