IEICE TRANSACTIONS on Information
Motion Belts: Visualization of Human Motion Data on a Timeline
Summary :
Because motion capture system enabled us to capture a number of human motions, the demand for a method to easily browse the captured motion database has been increasing. In this paper, we propose a method to generate simple visual outlines of motion clips, for the purpose of efficient motion data browsing. Our method unfolds a motion clip into a 2D stripe of keyframes along a timeline that is based on semantic keyframe extraction and the best view point selection for each keyframes. With our visualization, timing and order of actions in the motions are clearly visible and the contents of multiple motions are easily comparable. In addition, because our method is applicable for a wide variety of motions, it can generate outlines for a large amount of motions fully automatically.
- Publication
- IEICE TRANSACTIONS on Information Vol.E91-D No.4 pp.1159-1167
- Publication Date
- 2008/04/01
- Publicized
- Online ISSN
- 1745-1361
- DOI
- 10.1093/ietisy/e91-d.4.1159
- Type of Manuscript
- PAPER
- Category
- Computer Graphics
Authors
Keyword
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Hiroshi YASUDA, Ryota KAIHARA, Suguru SAITO, Masayuki NAKAJIMA, "Motion Belts: Visualization of Human Motion Data on a Timeline" in IEICE TRANSACTIONS on Information,
vol. E91-D, no. 4, pp. 1159-1167, April 2008, doi: 10.1093/ietisy/e91-d.4.1159.
Abstract: Because motion capture system enabled us to capture a number of human motions, the demand for a method to easily browse the captured motion database has been increasing. In this paper, we propose a method to generate simple visual outlines of motion clips, for the purpose of efficient motion data browsing. Our method unfolds a motion clip into a 2D stripe of keyframes along a timeline that is based on semantic keyframe extraction and the best view point selection for each keyframes. With our visualization, timing and order of actions in the motions are clearly visible and the contents of multiple motions are easily comparable. In addition, because our method is applicable for a wide variety of motions, it can generate outlines for a large amount of motions fully automatically.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e91-d.4.1159/_p
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@ARTICLE{e91-d_4_1159,
author={Hiroshi YASUDA, Ryota KAIHARA, Suguru SAITO, Masayuki NAKAJIMA, },
journal={IEICE TRANSACTIONS on Information},
title={Motion Belts: Visualization of Human Motion Data on a Timeline},
year={2008},
volume={E91-D},
number={4},
pages={1159-1167},
abstract={Because motion capture system enabled us to capture a number of human motions, the demand for a method to easily browse the captured motion database has been increasing. In this paper, we propose a method to generate simple visual outlines of motion clips, for the purpose of efficient motion data browsing. Our method unfolds a motion clip into a 2D stripe of keyframes along a timeline that is based on semantic keyframe extraction and the best view point selection for each keyframes. With our visualization, timing and order of actions in the motions are clearly visible and the contents of multiple motions are easily comparable. In addition, because our method is applicable for a wide variety of motions, it can generate outlines for a large amount of motions fully automatically.},
keywords={},
doi={10.1093/ietisy/e91-d.4.1159},
ISSN={1745-1361},
month={April},}
Copy
TY - JOUR
TI - Motion Belts: Visualization of Human Motion Data on a Timeline
T2 - IEICE TRANSACTIONS on Information
SP - 1159
EP - 1167
AU - Hiroshi YASUDA
AU - Ryota KAIHARA
AU - Suguru SAITO
AU - Masayuki NAKAJIMA
PY - 2008
DO - 10.1093/ietisy/e91-d.4.1159
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E91-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2008
AB - Because motion capture system enabled us to capture a number of human motions, the demand for a method to easily browse the captured motion database has been increasing. In this paper, we propose a method to generate simple visual outlines of motion clips, for the purpose of efficient motion data browsing. Our method unfolds a motion clip into a 2D stripe of keyframes along a timeline that is based on semantic keyframe extraction and the best view point selection for each keyframes. With our visualization, timing and order of actions in the motions are clearly visible and the contents of multiple motions are easily comparable. In addition, because our method is applicable for a wide variety of motions, it can generate outlines for a large amount of motions fully automatically.
ER -
English
