Browse > Article
http://dx.doi.org/10.9708/jksci.2021.26.11.051

Leap Motion Framework for Juggling Motion According to User Motion in Virtual Environment  

Kim, Jong-Hyun (School of Software Application, Kangnam University)
Abstract
In this paper, we propose a new framework that calculates the user's hand motions using a Leap Motion device, and uses this to practice and analyze arm muscles as well as juggling motions. The proposed method can map the movement of the ball in a virtual environment according to the user's hand motions in real time, and analyze the amount of exercise by visualizing the relaxation and contraction of the muscles. The proposed framework consists of three main parts : 1) It tracks the user's hand position with the Leap Motion device. 2) As with juggling, the action pattern of the user throwing the ball is defined as an event. 3) We propose a parabola-based particle method to map the movement of a juggling shape to a ball based on the user's hand position. As a result, using the our framework, it is possible to play a juggling game in real-time.
Keywords
Leap Motion device; Hand motion; Arm muscles; Virtual environment; Juggling motion;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Y. Fan, J. Litven, and D. K. Pai, "Active volumetric musculoskeletal systems," ACM Transactions on Graphics (TOG), vol. 33, no. 4, pp. 1-9, 2014.
2 W. Si, S.-H. Lee, E. Sifakis, and D. Terzopoulos, "Realistic biomechanical simulation and control of human swimming," ACM Transactions on Graphics (TOG), vol. 34, no. 1, pp. 1-15, 2014.
3 D. Holden, J. Saito, and T. Komura, "A deep learning framework for character motion synthesis and editing," ACM Transactions on Graphics (TOG), vol. 35, no. 4, pp. 1-11, 2016.
4 M. Da Silva, Y. Abe, and J. Popovi'c, "Simulation of human motion data using short-horizon model-predictive control," in Computer Graphics Forum, vol. 27, no. 2, pp. 371-380, 2008.   DOI
5 S. Barrett, K. Genter, T. Hester, M. Quinlan, and P. Stone, "Controlled kicking under uncertainty," in The Fifth Workshop on Humanoid Soccer Robots at Humanoids, 2010.
6 J.-I. Choi, S.-J. Kang, C.-H. Kim, and J. Lee, "Virtual ball player," The Visual Computer, vol. 31, no. 6-8, pp. 905-914, 2015.   DOI
7 O. Arikan and D. A. Forsyth, "Interactive motion generation from examples," ACM Transactions on Graphics (TOG), vol. 21, no. 3, pp. 483-490, 2002.   DOI
8 D. Holden, T. Komura, and J. Saito, "Phase-functioned neural networks for character control," ACM Transactions on Graphics (TOG), vol. 36, no. 4, pp. 1-13, 2017.
9 S. Clavet, "Motion matching and the road to next-gen animation," in Proc. of GDC, 2016.
10 D. Han, H. Eom, J. Noh, and J. S. Shin (formerly Sung Yong Shin), "Data-guided model predictive control based on smoothed contact dynamics," Computer Graphics Forum, vol. 35, no. 2, pp. 533-543, 2016.   DOI
11 M. Romeo, C. Monteagudo, and D. S'anchez-Quir'os, "Muscle and fascia simulation with extended position based dynamics," in Computer Graphics Forum, vol. 39, no. 1, pp. 134-146, 2020.   DOI
12 L. E. Potter, J. Araullo, and L. Carter, "The leap motion controller: a view on sign language," in Proceedings of the 25th Australian computer-human interaction conference: augmentation, application, innovation, collaboration, pp. 175-178, 2013.
13 S. I. Park and J. K. Hodgins, "Data-driven modeling of skin and muscle deformation," in ACM SIGGRAPH 2008 papers, pp. 1-6, 2008.
14 S. Lee, M. Park, K. Lee, and J. Lee, "Scalable muscleactuated human simulation and control," ACM Transactions on Graphics (TOG), vol. 38, no. 4, pp. 1-13, 2019.
15 R. Yu, H. Park, and J. Lee, "Figure skating simulation from video," in Computer graphics forum, vol. 38, no. 7, pp. 225-234, 2019.   DOI
16 P. Khungurn and D. Chou, "Pose estimation of anime/manga characters: a case for synthetic data," in Proceedings of the 1st International Workshop on coMics ANalysis, Processing and Understanding, pp. 1-6, 2016.
17 J. Chemin and J. Lee, "A physics-based juggling simulation using reinforcement learning," in Proceedings of the 11th Annual International Conference on Motion, Interaction, and Games, pp. 1-7, 2018.
18 M. Sra and C. Schmandt, "Metaspace ii: Object and full-body tracking for interaction and navigation in social vr," arXiv preprint arXiv:1512.02922, 2015.
19 L. Kumarapu and P. Mukherjee, "Animepose: Multiperson 3d pose estimation and animation," arXiv preprint arXiv:2002.02792, 2020.
20 J.Won and J. Lee, "Learning body shape variation in physicsbased characters," ACM Transactions on Graphics (TOG), vol. 38, no. 6, pp. 1-12, 2019.
21 J.-I. Choi, S.-J. Kim, C.-H. Kim, and J. Lee, "Let's be a virtual juggler," Computer Animation and Virtual Worlds, vol. 27, no. 3-4, pp. 443-450, 2016.   DOI
22 D. G. Thelen, "Adjustment of muscle mechanics model parameters to simulate dynamic contractions in older adults," J. Biomech. Eng., vol. 125, no. 1, pp. 70-77, 2003.   DOI
23 K. Ding, L. Liu, M. Van de Panne, and K. Yin, "Learning reduced-order feedback policies for motion skills," in Proceedings of the 14th ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 2015, pp. 83-92.
24 L. Liu, M. van de Panne, and K. Yin, "Guided learning of control graphs for physics-based characters," ACM Transactions on Graphics, vol. 35, no. 3, 2016.
25 T. Hester, M. Quinlan, and P. Stone, "Generalized model learning for reinforcement learning on a humanoid robot," in 2010 IEEE International Conference on Robotics and Automation, pp. 2369-2374, 2010.
26 S.-H. Lee, E. Sifakis, and D. Terzopoulos, "Comprehensive biomechanical modeling and simulation of the upper body," ACM Transactions on Graphics (TOG), vol. 28, no. 4, pp. 1-17, 2009.
27 S. Jain and C. K. Liu, "Interactive synthesis of humanobject interaction," in Proceedings of the 2009 ACM SIGGRAPH/Eurographics Symposium on Computer Animation, pp. 47-53, 2009.