skip to main content
research-article

Real-time hand-tracking with a color glove

Authors Info & Claims
Published:27 July 2009Publication History
Skip Abstract Section

Abstract

Articulated hand-tracking systems have been widely used in virtual reality but are rarely deployed in consumer applications due to their price and complexity. In this paper, we propose an easy-to-use and inexpensive system that facilitates 3-D articulated user-input using the hands. Our approach uses a single camera to track a hand wearing an ordinary cloth glove that is imprinted with a custom pattern. The pattern is designed to simplify the pose estimation problem, allowing us to employ a nearest-neighbor approach to track hands at interactive rates. We describe several proof-of-concept applications enabled by our system that we hope will provide a foundation for new interactions in modeling, animation control and augmented reality.

Skip Supplemental Material Section

Supplemental Material

tps039_09.mp4

mp4

54.1 MB

References

  1. Agrawala, M., Beers, A. C., Fröhlich, B., Hanrahan, P. M., McDowall, I., and Bolas, M. 1997. The two-user responsive workbench: Support for collaboration through independent views of a shared space. In Proceedings of SIGGRAPH 97, 327--332. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Athitsos, V., and Sclaroff, S. 2003. Estimating 3D hand pose from a cluttered image. In Computer Vision and Pattern Recognition (CVPR), vol. 2, 432--439.Google ScholarGoogle Scholar
  3. Athitsos, V., Alon, J., Sclaroff, S., and Kollios, G. 2004. BoostMap: A method for efficient approximate similarity rankings. In Computer Vision and Pattern Recognition (CVPR), vol. 2, 268--275. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Barnes, C., Jacobs, D. E., Sanders, J., Goldman, D. B., Rusinkiewicz, S., Finkelstein, A., and Agrawala, M. 2008. Video puppetry: a performative interface for cutout animation. ACM Transactions on Graphics 27, 5, 1--9. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Benko, H., Ishak, E., and Feiner, S. 2005. Cross-Dimensional Gestural Interaction Techniques for Hybrid Immersive Environments. In IEEE Virtual Reality Conference, 209--216. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Chong, H. Y., Gortler, S. J., and Zickler, T. 2008. A perception-based color space for illumination-invariant image processing. ACM Transactions on Graphics 27, 3, 1--7. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. de La Gorce, M., Paragios, N., and Fleet, D. 2008. Model-Based Hand Tracking with Texture, Shading and Self-occlusions. In Computer Vision and Pattern Recognition (CVPR), 1--8.Google ScholarGoogle Scholar
  8. Dewaele, G., Devernay, F., Horaud, R. P., and Forbes, F. 2006. The alignment between 3-d data and articulated shapes with bending surfaces. In European Conference on Computer Vision (ECCV), 578--591. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Dhawale, P., Masoodian, M., and Rogers, B. 2006. Barehand 3D gesture input to interactive systems. In New Zealand Chapter's International Conference on Computer-Human Interaction: Design Centered HCI (CHINZ), 25--32. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Dontcheva, M., Yngve, G., and Popović, Z. 2003. Layered acting for character animation. ACM Transactions on Graphics 22, 3, 409--416. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Dorner, B. 1994. Chasing the Colour Glove: Visual Hand Tracking. Master's thesis, Simon Fraser University.Google ScholarGoogle Scholar
  12. Grossman, T., Wigdor, D., and Balakrishnan, R. 2004. Multi-finger gestural interaction with 3d volumetric displays. In User Interface Software and Technology (UIST), 61--70. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Guskov, I., Klibanov, S., and Bryant, B. 2003. Trackable surfaces. In Symposium on Computer Animation (SCA), 251--257. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Keefe, D. F., Karelitz, D. B., Vote, E. L., and Laidlaw, D. H. 2005. Artistic collaboration in designing vr visualizations. IEEE Computer Graphics and Applications 25, 2, 18--23. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Kersten, D., Mamassian, P., and Knill, D. 1997. Moving cast shadows induce apparent motion in depth. Perception 26, 2, 171--192.Google ScholarGoogle ScholarCross RefCross Ref
  16. Kry, P., and Pai, D. 2006. Interaction capture and synthesis. ACM Transactions on Graphics 25, 3, 872--880. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Kry, P., Pihuit, A., Bernhardt, A., and Cani, M. 2008. HandNavigator: hands-on interaction for desktop virtual reality. In Virtual Reality Software and Technology (VRST), 53--60. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Lam, W., Zou, F., and Komura, T. 2004. Motion editing with data glove. In International Conference on Advances in Computer Entertainment Technology, 337--342. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Lee, C.-S., Ghyme, S.-W., Park, C.-J., and Wohn, K. 1998. The control of avatar motion using hand gesture. In Virtual Reality Software and Technology (VRST), 59--65. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Li, Y., Fu, J. L., and Pollard, N. S. 2007. Data-driven grasp synthesis using shape matching and task-based pruning. IEEE Transactions Visualization and Computer Graphics 13, 4, 732--747. Google ScholarGoogle ScholarDigital LibraryDigital Library
  21. Olwal, A., Benko, H., and Feiner, S. 2003. Senseshapes: Using statistical geometry for object selection in a multimodal augmented reality system. In International Symposium on Mixed and Augmented Reality (ISMAR), 300. Google ScholarGoogle ScholarDigital LibraryDigital Library
  22. Park, J., and Yoon, Y. 2006. LED-glove based interactions in multi-modal displays for teleconferencing. In International Conference on Artificial Reality and Telexistence-Workshops (ICAT), 395--399. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Pollard, N., and Zordan, V. 2005. Physically based grasping control from example. In Symposium on Computer Animation (SCA), 311--318. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. Ren, L., Shakhnarovich, G., Hodgins, J., Pfister, H., and Viola, P. 2005. Learning silhouette features for control of human motion. ACM Transactions on Graphics 24, 4, 1303--1331. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Schlattman, M., and Klein, R. 2007. Simultaneous 4 gestures 6 dof real-time two-hand tracking without any markers. In Virtual Reality Software and Technology (VRST), 39--42. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Scholz, V., Stich, T., Keckeisen, M., Wacker, M., and Magnor, M. A. 2005. Garment motion capture using color-coded patterns. Computer Graphics Forum 24, 3, 439--447.Google ScholarGoogle ScholarCross RefCross Ref
  27. Shakhnarovich, G., Viola, P., and Darrell, T. 2003. Fast pose estimation with parameter-sensitive hashing. In International Conference on Computer Vision (ICCV), 750--757. Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Sheng, J., Balakrishnan, R., and Singh, K. 2006. An interface for virtual 3d sculpting via physical proxy. In Computer Graphics and Interactive Techniques in Australasia and Southeast Asia (GRAPHITE), 213--220. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. Shiratori, T., and Hodgins, J. K. 2008. Accelerometer-based user interfaces for the control of a physically simulated character. ACM Transactions on Graphics 27, 5, 1--9. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Starner, T., Weaver, J., and Pentland, A. 1998. Real-time American sign language recognition using desk and wearable computer based video. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1371--1375. Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Stenger, B., Thayananthan, A., Torr, P., and Cipolla, R. 2006. Model-based hand tracking using a hierarchical bayesian filter. IEEE Transactions Pattern Analysis and Machine Intelligence 28, 9, 1372--1384. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Sturman, D. J., and Zeltzer, D. 1993. A design method for "whole-hand" human-computer interaction. ACM Transactions on Information Systems 11, 3, 219--238. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Sudderth, E. B., Mandel, M. I., Freeman, T., and Willsky, S. 2004. Distributed occlusion reasoning for tracking with nonparametric belief propagation. In Neural Information Processing Systems (NIPS), 1369--1376.Google ScholarGoogle Scholar
  34. Theobalt, C., Albrecht, I., Haber, J., Magnor, M., and Seidel, H.-P. 2004. Pitching a baseball -- tracking highspeed motion with multi-exposure images. ACM Transactions on Graphics 23, 3, 540--547. Google ScholarGoogle ScholarDigital LibraryDigital Library
  35. Torralba, A., Fergus, R., and Freeman, W. T. 2007. Tiny images. Tech. Rep. MIT-CSAIL-TR-2007-024, Computer Science and Artificial Intelligence Lab, MIT.Google ScholarGoogle Scholar
  36. Torralba, A., Fergus, R., and Weiss., Y. 2008. Small codes and large databases for recognition. In Computer Vision and Pattern Recognition (CVPR), vol. 2, 1--8.Google ScholarGoogle Scholar
  37. Wesche, G., and Seidel, H.-P. 2001. Freedrawer: a freeform sketching system on the responsive workbench. In Virtual Reality Software and Technology (VRST), 167--174. Google ScholarGoogle ScholarDigital LibraryDigital Library
  38. White, R., and Forsyth, D. 2005. Deforming objects provide better camera calibration. Tech. Rep. UCB/EECS-2005-3, EECS Department, University of California, Berkeley.Google ScholarGoogle Scholar
  39. White, R., Crane, K., and Forsyth, D. A. 2007. Capturing and animating occluded cloth. ACM Transactions on Graphics 26, 3, 34:1--34:8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. Wilson, A., Izadi, S., Hilliges, O., Garcia-Mendoza, A., and Kirk, D. 2008. Bringing physics to the surface. In User Interface Software and Technology (UIST), 67--76. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Real-time hand-tracking with a color glove

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in

      Full Access

      • Published in

        cover image ACM Transactions on Graphics
        ACM Transactions on Graphics  Volume 28, Issue 3
        August 2009
        750 pages
        ISSN:0730-0301
        EISSN:1557-7368
        DOI:10.1145/1531326
        Issue’s Table of Contents

        Copyright © 2009 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 27 July 2009
        Published in tog Volume 28, Issue 3

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader