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Generalizing wave gestures from sparse examples for real-time character control

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Generalizing wave gestures from sparse examples for real-time character control. / Rhodin, Helge; Tompkin, James; Kim, Kwang In et al.
In: ACM Transactions on Graphics (Proc. SIGGRAPH Asia), Vol. 34, No. 6, 181, 11.2015.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Rhodin, H, Tompkin, J, Kim, KI, de Aguiar, E, Pfister, H, Seidel, H-P & Theobalt, C 2015, 'Generalizing wave gestures from sparse examples for real-time character control', ACM Transactions on Graphics (Proc. SIGGRAPH Asia), vol. 34, no. 6, 181. https://doi.org/10.1145/2816795.2818082

APA

Rhodin, H., Tompkin, J., Kim, K. I., de Aguiar, E., Pfister, H., Seidel, H-P., & Theobalt, C. (2015). Generalizing wave gestures from sparse examples for real-time character control. ACM Transactions on Graphics (Proc. SIGGRAPH Asia), 34(6), Article 181. https://doi.org/10.1145/2816795.2818082

Vancouver

Rhodin H, Tompkin J, Kim KI, de Aguiar E, Pfister H, Seidel H-P et al. Generalizing wave gestures from sparse examples for real-time character control. ACM Transactions on Graphics (Proc. SIGGRAPH Asia). 2015 Nov;34(6):181. doi: 10.1145/2816795.2818082

Author

Rhodin, Helge ; Tompkin, James ; Kim, Kwang In et al. / Generalizing wave gestures from sparse examples for real-time character control. In: ACM Transactions on Graphics (Proc. SIGGRAPH Asia). 2015 ; Vol. 34, No. 6.

Bibtex

@article{2d473490a37b43329750ec81f532b67c,
title = "Generalizing wave gestures from sparse examples for real-time character control",
abstract = "Motion-tracked real-time character control is important for games and VR, but current solutions are limited: retargeting is hard for non-human characters, with locomotion bound to the sensing volume; and pose mappings are ambiguous and not robust with consumer trackers, with dynamic motion properties unwieldy. We robustly estimate wave properties — amplitude, frequency, and phase — for a set of interactively-defined gestures, by mapping user motions to a low-dimensional independent representation. The mapping both separates simultaneous or intersecting gestures, and extrapolates gesture variations from single training examples. For animation control, e.g., locomotion, wave properties map naturally to stride length, step frequency, and progression, and allow smooth animation from standing, to walking, to running. Simultaneous gestures are disambiguated successfully. Interpolating out-of-phase locomotions is hard, e.g., quadruped legs between walks and runs, so we introduce a new time-interpolation scheme to reduce artifacts. These improvements to real-time motion-tracked character control are particularly important for common cyclic animations, which we validate in a user study, with versatility to apply to part and full body motions across a variety of sensors. ",
author = "Helge Rhodin and James Tompkin and Kim, {Kwang In} and {de Aguiar}, Edilson and Hanspeter Pfister and Hans-Peter Seidel and Christian Theobalt",
note = "Date of Acceptance: 31/08/2015 ",
year = "2015",
month = nov,
doi = "10.1145/2816795.2818082",
language = "English",
volume = "34",
journal = "ACM Transactions on Graphics (Proc. SIGGRAPH Asia)",
issn = "0730-0301",
publisher = "Association for Computing Machinery (ACM)",
number = "6",

}

RIS

TY - JOUR

T1 - Generalizing wave gestures from sparse examples for real-time character control

AU - Rhodin, Helge

AU - Tompkin, James

AU - Kim, Kwang In

AU - de Aguiar, Edilson

AU - Pfister, Hanspeter

AU - Seidel, Hans-Peter

AU - Theobalt, Christian

N1 - Date of Acceptance: 31/08/2015

PY - 2015/11

Y1 - 2015/11

N2 - Motion-tracked real-time character control is important for games and VR, but current solutions are limited: retargeting is hard for non-human characters, with locomotion bound to the sensing volume; and pose mappings are ambiguous and not robust with consumer trackers, with dynamic motion properties unwieldy. We robustly estimate wave properties — amplitude, frequency, and phase — for a set of interactively-defined gestures, by mapping user motions to a low-dimensional independent representation. The mapping both separates simultaneous or intersecting gestures, and extrapolates gesture variations from single training examples. For animation control, e.g., locomotion, wave properties map naturally to stride length, step frequency, and progression, and allow smooth animation from standing, to walking, to running. Simultaneous gestures are disambiguated successfully. Interpolating out-of-phase locomotions is hard, e.g., quadruped legs between walks and runs, so we introduce a new time-interpolation scheme to reduce artifacts. These improvements to real-time motion-tracked character control are particularly important for common cyclic animations, which we validate in a user study, with versatility to apply to part and full body motions across a variety of sensors.

AB - Motion-tracked real-time character control is important for games and VR, but current solutions are limited: retargeting is hard for non-human characters, with locomotion bound to the sensing volume; and pose mappings are ambiguous and not robust with consumer trackers, with dynamic motion properties unwieldy. We robustly estimate wave properties — amplitude, frequency, and phase — for a set of interactively-defined gestures, by mapping user motions to a low-dimensional independent representation. The mapping both separates simultaneous or intersecting gestures, and extrapolates gesture variations from single training examples. For animation control, e.g., locomotion, wave properties map naturally to stride length, step frequency, and progression, and allow smooth animation from standing, to walking, to running. Simultaneous gestures are disambiguated successfully. Interpolating out-of-phase locomotions is hard, e.g., quadruped legs between walks and runs, so we introduce a new time-interpolation scheme to reduce artifacts. These improvements to real-time motion-tracked character control are particularly important for common cyclic animations, which we validate in a user study, with versatility to apply to part and full body motions across a variety of sensors.

U2 - 10.1145/2816795.2818082

DO - 10.1145/2816795.2818082

M3 - Journal article

VL - 34

JO - ACM Transactions on Graphics (Proc. SIGGRAPH Asia)

JF - ACM Transactions on Graphics (Proc. SIGGRAPH Asia)

SN - 0730-0301

IS - 6

M1 - 181

ER -