Authors:
Jürgen Bernard
1
;
Anna Vögele
2
;
Reinhard Klein
2
and
Dieter Fellner
3
Affiliations:
1
TU Darmstadt, Germany
;
2
University of Bonn, Germany
;
3
TU Darmstadt and Fraunhofer IGD, Germany
Keyword(s):
Visual Comparison, Human Motion Capture Data, Motion Capture Analysis, Human-Computer Interaction, Information Visualization, Visual Analytics, Information Retrieval, Data Mining, Machine Learning.
Related
Ontology
Subjects/Areas/Topics:
Abstract Data Visualization
;
Biomedical Visualization and Applications
;
Computer Vision, Visualization and Computer Graphics
;
General Data Visualization
;
High-Dimensional Data and Dimensionality Reduction
;
Spatial Data Visualization
;
Time-Dependent Visualization
;
Visual Representation and Interaction
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.