MotionExplorer: Exploratory Search in Human Motion Capture Data Based on Hierarchical Aggregation

Jürgen Bernard, Nils Wilhelm, Björn Krüger, Thorsten May, Tobias Schreck und Jörn Kohlhammer
In: IEEE Transactions on Visualization and Computer Graphics (Proc. VAST) (Dez. 2013)
 

Abstract

We present MotionExplorer, an exploratory search and analysis system for sequences of human motion in large motion capture data collections. This special type of multivariate time series data is relevant in many research fields including medicine, sports and animation. Key tasks in working with motion data include analysis of motion states and transitions, and synthesis of motion vectors by interpolation and combination. In the practice of research and application of human motion data, challenges exist in providing visual summaries and drill-down functionality for handling large motion data collections. We find that this domain can benefit from appropriate visual retrieval and analysis support to handle these tasks in presence of large motion data. To address this need, we developed MotionExplorer together with domain experts as an exploratory search system based on interactive aggregation and visualization of motion states as a basis for data navigation, exploration, and search. Based on an overview-first type visualization, users are able to search for interesting sub-sequences of motion based on a query-by-example metaphor, and explore search results by details on demand. We developed MotionExplorer in close collaboration with the targeted users who are researchers working on human motion synthesis and analysis, including a summative field study. Additionally, we conducted a laboratory design study to substantially improve MotionExplorer towards an intuitive, usable and robust design. MotionExplorer enables the search in human motion capture data with only a few mouse clicks. The researchers unanimously confirm that the system can efficiently support their work.

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Bibtex

@ARTICLE{bernard2013,
    author = {Bernard, J{\"u}rgen and Wilhelm, Nils and Kr{\"u}ger, Bj{\"o}rn and May, Thorsten and Schreck, Tobias and
              Kohlhammer, J{\"o}rn},
     title = {MotionExplorer: Exploratory Search in Human Motion Capture Data Based on Hierarchical Aggregation},
   journal = {IEEE Transactions on Visualization and Computer Graphics (Proc. VAST)},
      year = {2013},
     month = dec,
  location = {Atlanta, Georgia, USA},
  abstract = {We present MotionExplorer, an exploratory search and analysis system for sequences of human motion
              in large motion capture data collections. This special type of multivariate time series data is
              relevant in many research fields including medicine, sports and animation. Key tasks in working with
              motion data include analysis of motion states and transitions, and synthesis of motion vectors by
              interpolation and combination. In the practice of research and application of human motion data,
              challenges exist in providing visual summaries and drill-down functionality for handling large
              motion data collections. We find that this domain can benefit from appropriate visual retrieval and
              analysis support to handle these tasks in presence of large motion data. To address this need, we
              developed MotionExplorer together with domain experts as an exploratory search system based on
              interactive aggregation and visualization of motion states as a basis for data navigation,
              exploration, and search. Based on an overview-first type visualization, users are able to search for
              interesting sub-sequences of motion based on a query-by-example metaphor, and explore search results
              by details on demand. We developed MotionExplorer in close collaboration with the targeted users who
              are researchers working on human motion synthesis and analysis, including a summative field study.
              Additionally, we conducted a laboratory design study to substantially improve MotionExplorer towards
              an intuitive, usable and robust design. MotionExplorer enables the search in human motion capture
              data with only a few mouse clicks. The researchers unanimously confirm that the system can
              efficiently support their work.}
}