Keyframe Extraction from Motion Capture Data for Visualization

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review

3 Scopus Citations
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Author(s)

Related Research Unit(s)

Detail(s)

Original languageEnglish
Title of host publicationProceedings - 2016 International Conference on Virtual Reality and Visualization, ICVRV 2016
EditorsJian Chen, Dangxiao Wang, Dandan Ding, Xun Luo
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages154-157
ISBN (Print)9781509051885
Publication statusPublished - Sep 2016

Conference

Title6th International Conference on Virtual Reality and Visualization (ICVRV 2016)
PlaceChina
CityHangzhou, Zhejiang
Period24 - 26 September 2016

Abstract

In this paper, we propose a novel method to extract keyframes from motion capture data for people to better visualize and understand the content of the motion. It first applies a Butterworth filter to remove the noise in the motion capture data, then carries out principal component analysis (PCA) to reduce the dimension. By detecting the zero-crossing points of the velocity in the principal components, the initial set of keyframes can be derived. The initial set of keyframes are further pruned to group similar postures together to remove redundancies. An experiment based on the CMU motion capture database is carried out, and the experiment result suggests that the keyframes extracted with our method could better support visualization and understanding of motion capture data.

Research Area(s)

  • Keyframe extraction, Motion capture, Principal component analysis, Visualization, Zero-crossing point

Citation Format(s)

Keyframe Extraction from Motion Capture Data for Visualization. / Yang, Yang; Zeng, Lanling; Leung, Howard.

Proceedings - 2016 International Conference on Virtual Reality and Visualization, ICVRV 2016. ed. / Jian Chen; Dangxiao Wang; Dandan Ding; Xun Luo. Institute of Electrical and Electronics Engineers Inc., 2016. p. 154-157 7938188.

Research output: Chapters, Conference Papers, Creative and Literary Works (RGC: 12, 32, 41, 45)32_Refereed conference paper (with ISBN/ISSN)peer-review