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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

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