Skip to main content

Advertisement

Log in

HandPuppet3D: Motion capture and analysis for character animation

  • Published:
Artificial Intelligence Review Aims and scope Submit manuscript

Abstract

Motion capture is a technique of digitally recording the movements of real entities, usually humans. It was originally developed as an analysis tool in biomechanics research, but has grown increasingly important as a source of motion data for computer animation. In this context it has been widely used for both cinema and video games. Hand motion capture and tracking in particular has received a lot of attention because of its critical role in the design of new Human Computer Interaction methods and gesture analysis. One of the main difficulties is the capture of human hand motion. This paper gives an overview of ongoing research “HandPuppet3D” being carried out in collaboration with an animation studio to employ computer vision techniques to develop a prototype desktop system and associated animation process that will allow an animator to control 3D character animation through the use of hand gestures. The eventual goal of the project is to support existing practice by providing a softer, more intuitive, user interface for the animator that improves the productivity of the animation workflow and the quality of the resulting animations. To help achieve this goal the focus has been placed on developing a prototype camera based desktop gesture capture system to capture hand gestures and interpret them in order to generate and control the animation of 3D character models. This will allow an animator to control 3D character animation through the capture and interpretation of hand gestures. Methods will be discussed for motion tracking and capture in 3D animation and in particular that of hand motion tracking and capture. HandPuppet3D aims to enable gesture capture with interpretation of the captured gestures and control of the target 3D animation software. This involves development and testing of a motion analysis system built from algorithms recently developed. We review current software and research methods available in this area and describe our current work.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • 3DConnexion (2008) Title of subordinate document. In: What is a 3D mouse? http://www.3dconnexion.com/3dmouse/what_is_3dmouse.php. Cited 25 Feb 2008

  • AAM Fitting Algorithms (2008) Title of subordinate document. In: Robotics institute: AAM fitting algorithms. http://www.ri.cmu.edu/projects/project_448.html. Cited 4 Feb 2008

  • Annosoft—Lypsync Tools for Professionals (2008) Title of subordinate document. In: Textless lypsync SDK. http://www.annosoft.com/. Cited 25 Feb 2008

  • Athitsos V, Sclaroff S (2003) Estimating 3D hand pose from a cluttered image. In: Proceedings of the international conference on computer vision and pattern recognition (CVPR), vol II. IEEE computer society, pp 432–439

  • Boujou 4 (2008) Title of subordinate document. In: Boujou 4 overview. http://www.2d3.com/html/products/boujou4_overview.html. Cited 4 Feb 2008

  • Benoit SM, Ferrie FP (1996) Monocular optical flow for real-time vision systems. In: Proceedings of the 13th international conference on pattern recognition (ICPR) vol 1, pp 864–868

  • Condell J et al (2005) Adaptive grid refinement procedures for efficient optical flow computation. International Journal of Computer Vision (IJCV), Kluwer Academic Publishers 61(1): 31–54

    Article  Google Scholar 

  • Condell J, et al (2006) Hand motion capture and tracking in animation. In: Lever L, McDerby M (eds) Eurographics UK chapter proceedings of fourth theory and practice of computer graphics conference (TPCG 2006), University of Teesside, Middlesbrough, June 2006, pp 105–109

  • Dewaele G, et al (2004) Hand motion from 3D point trajectories and a smooth surface model. In: Proceedings of the 8th european conference on computer vision, LNCS 3021, I:495–507

  • EyeToy® (2008) Title of subordinate document. In: EyeToy®. http://www.eyetoy.com/index.asp. Cited 4 Feb 2008

  • FaceLabTM (2008) Title of subordinate document. In: FaceLabTM version 4. http://www.seeingmachines.com/facelab.htm. Cited 4 Feb 2008

  • Heap T, Hogg D (1996) Towards 3D hand tracking using a deformable model. In: Proceedings of the 2nd international conference on automatic face and gesture recognition (FG ‘96), p 140

  • Henson Digital Performance Studio (2008) Title of subordinate document. In: http://www.5dt.com/index.html. Cited 25 Feb 2008

  • Image Metrics (2008) Title of subordinate document. In: Image metrics performance-driven facial animation solutions for the digital world. http://www.image-metrics.com/. Cited 4 Feb 2008

  • Koterba S, et al. (2005) Multi-view AAM fitting and camera calibration. In: Proceedings of the international conference on computer vision (ICCV), pp 511–518

  • Kolsch M, Turk M (2005) Hand tracking with flocks of features. In: IEEE computer society, Proceedings of the international conference on computer vision and pattern recognition (CVPR), vol 2, p 1187

  • Lee SU, Cohen I (2004) 3D Hands reconstruction from monocular view. In: Proceedings of the international conference on pattern recognition (ICPR), vol III, p 310

  • Lin J, et al (2002) Capturing human hand motion in image sequences. In: Proceedings of IEEE workshop on motion and video computing (WMVC02), pp 99–104

  • Lucas BD, Kanade T (1981) An iterative image registration technique with an application to stereo vision. In: Proceedings of the 7th international joint conference on artificial intelligence (IJCAI’81), pp 674–679

  • Matthews I, Baker S (2004) Active appearance models revisited. Int J Comput Vis 60(2):135–164

    Article  Google Scholar 

  • Metaxas D, et al (2003) Using multiple cues for hand tracking and model refinement. In: Proceedings of the international conference on computer vision and pattern recognition (CVPR), vol II. IEEE Computer Society, pp 443–450

  • PixelFarm PFTrack (2008) Title of subordinate document. In: The PixelFarm®). http://www.thepixelfarm.co.uk/. Cited 4 Feb 2008

  • RealViz Match Mover (2008) Title of subordinate document. In: Motion capture software, Mocap software and 3D tracking software—REALVIZ movimento. http://movimento.realviz.com/index.php?language=EN. Cited 4 Feb 2008

  • Rosenbluth S, et al. (2002) Controlling creatures with linux. Linux J, Vol 103

  • Sciene.D.Visions 3D-EqualizerTM V3 (2008) Title of subordinate document. In: Science-D-visions. http://www.3dequalizer.com. Cited 4 Feb 2008

  • Simi Reality Motion Systems (2008) Title of subordinate document. In: SIMI reality motion systems 2D/3D movement analysis software, kinematics, kinetics, motion capture, character animation. http://www.simi.com/en/. Cited 4 Feb 2008

  • Ssontech SynthEyes (2008) Title of subordinate document. In: SynthEyes—andersson technologies LLC. http://www.ssontech.com/. Cited 4 Feb 2008

  • Stenger B (2004) Model-based hand tracking using a hierarchical bayesian filter. PhD Thesis, Department of Engineering, University of Cambridge

  • Voodoo (2008) Title of subordinate document. In: Digilab homepage. http://www.digilab.uni-hannover.de/docs/manual.html. Cited 4 Feb 2008

  • Zhou H, Huang TS (2003) Tracking articulated hand motion with eigen dynamics analysis. In: Proceedings of the 9th international conference on computer vision (ICCV), vol 2, p 1102

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Joan Condell.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Condell, J., Moore, G. HandPuppet3D: Motion capture and analysis for character animation. Artif Intell Rev 31, 45 (2009). https://doi.org/10.1007/s10462-009-9126-5

Download citation

  • Published:

  • DOI: https://doi.org/10.1007/s10462-009-9126-5

Keywords

Navigation