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Motion Volume: Visualization of Human Motion Manifolds

Published: 14 November 2019 Publication History

Abstract

The understanding of human motion is important in many areas such as sports, dance, and animation. In this paper, we propose a method for visualizing the manifold of human motions. A motion manifold is defined by a set of motions in a specific motion form. Our method visualizes the ranges of time-varying positions and orientations of a body part by generating volumetric shapes for representing them. It selects representative keyposes from the keyposes of all input motions to visualize the range of keyposes at each key timing. A geometrical volume that contains the trajectories from all input motions is generated for each body part. In addition, a geometrical volume that contains the orientations from all input motions is generated for a sample point on the trajectory. The user can understand the motion manifold by visualizing these motion volumes. In this paper, we present some experimental examples for a tennis shot form.

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References

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Cited By

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  • (2023)GestureExplorer: Immersive Visualisation and Exploration of Gesture DataProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580678(1-16)Online publication date: 19-Apr-2023

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cover image ACM Conferences
VRCAI '19: Proceedings of the 17th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and its Applications in Industry
November 2019
354 pages
ISBN:9781450370028
DOI:10.1145/3359997
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 14 November 2019

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Author Tags

  1. Computational Geometry
  2. Human Motion
  3. Motion Manifolds
  4. Visualization

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Overall Acceptance Rate 51 of 107 submissions, 48%

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Cited By

View all
  • (2023)GestureExplorer: Immersive Visualisation and Exploration of Gesture DataProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580678(1-16)Online publication date: 19-Apr-2023

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