Skip to main content
SpringerLink
Log in
Book cover

Man–Machine Interactions 4 pp 353–363Cite as

Towards the Automatic Definition of the Objective Function for Model-Based 3D Hand Tracking

  • Conference paper
  • First Online:

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 391))

Abstract

Recently, model-based approaches have produced very promising results to the problems of 3D hand tracking. The current state of the art method recovers the 3D position, orientation and 20 DOF articulation of a human hand from markerless visual observations obtained by an RGB-D sensor. Hand pose estimation is formulated as an optimization problem, seeking for the hand model parameters that minimize an objective function that quantifies the discrepancy between the appearance of hand hypotheses and the actual hand observation. The design of such a function is a complicated process that requires a lot of prior experience with the problem. In this paper we automate the definition of the objective function in such optimization problems. First, a set of relevant, candidate image features is computed. Then, given synthetic data sets with ground truth information, regression analysis is used to combine these features in an objective function that seeks to maximize optimization performance. Extensive experiments study the performance of the proposed approach based on various dataset generation strategies and feature selection techniques.

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Albrecht, I., Haber, J., Seidel, H.P.: Construction and animation of anatomically based human hand models. In: SIGGRAPH, pp. 98–109. San Diego, USA (2003)

    Google Scholar 

  2. Argyros, A.A., Lourakis, M.I.: Real-time tracking of multiple skin-colored objects with a possibly moving camera. In: Pajdla, T., Matas, J. (eds.) Computer Vision–ECCV 2004. LNCS, vol. 3023, pp. 368–379. Springer, Berlin (2004)

    Chapter  Google Scholar 

  3. Canny, J.: A computational approach to edge detection. IEEE Trans. PAMI-Pattern Anal. Mach. Intell. 8(6), 679–698 (1986)

    Google Scholar 

  4. Cao, C., Weng, Y., Lin, S., Zhou, K.: 3D shape regression for real-time facial animation. ACM Trans. Graphics 32(4), 41:1–41:10 (2013)

    Google Scholar 

  5. de La Gorce, M., Paragios, N., Fleet, D.J.: Model-based hand tracking with texture, shading and self-occlusions. In: CVPR, pp. 1–8. Anchorage, USA (2008)

    Google Scholar 

  6. Erol, A., Bebis, G., Nicolescu, M., Boyle, R.D., Twombly, X.: Vision-based hand pose estimation: a review. Comput. Vis. Image Underst. 108(1), 52–73 (2007)

    Article  Google Scholar 

  7. Felzenszwalb, P.F., Huttenlocher, D.P.: Efficient belief propagation for early vision. Int. J. Comput. Vision 70(1), 41–54 (2006)

    Article  Google Scholar 

  8. Hamer, H., Schindler, K., Koller-Meier, E., Van Gool, L.: Tracking a hand manipulating an object. In: ICCV, pp. 1475–1482. Kyoto, Japan (2009)

    Google Scholar 

  9. Kennedy, J., Eberhart, R.: Particle swarm optimization. In: ICNN, vol. 4, pp. 1942–1948. Perth, Australia (1995)

    Google Scholar 

  10. Kyriazis, N., Oikonomidis, I., Argyros, A.: A GPU-powered computational framework for efficient 3D model-based vision. Techincal report, ICS-FORTH (2011)

    Google Scholar 

  11. Moeslund, T.B., Hilton, A., Krüger, V.: A survey of advances in vision-based human motion capture and analysis. Comput. Vis. Image Underst. 104(2), 90–126 (2006)

    Article  Google Scholar 

  12. Oikonomidis, I., Kyriazis, N., Argyros, A.: Efficient model-based 3D tracking of hand articulations using Kinect. In: BMVC, pp. 101.1-101.11. Dundee, UK (2011)

    Google Scholar 

  13. Oikonomidis, I., Kyriazis, N., Argyros, A.A.: Markerless and efficient 26-DOF hand pose recovery. In: Kimmel, R., Klette, R., Sugimoto, A. (eds.) Computer Vision–ACCV 2010. LNCS, vol. 6494, pp. 744–757. Springer, Berlin (2011)

    Chapter  Google Scholar 

  14. Romero, J., Kjellstrom, H., Kragic, D.: Monocular real-time 3d articulated hand pose estimation. In: Humanoids, pp. 87–92. Paris, France (2009)

    Google Scholar 

  15. Shotton, J., Sharp, T., Kipman, A., Fitzgibbon, A., Finocchio, M., Blake, A., Cook, M., Moore, R.: Real-time human pose recognition in parts from single depth images. Commun. ACM 56(1), 116–124 (2013)

    Article  Google Scholar 

  16. Sobol, I.M.: On the distribution of points in a cube and the approximate evaluation of integrals. USSR Comput. Math. Mathematical Phys. 7(4), 86–112 (1967)

    Article  MathSciNet  Google Scholar 

  17. Wu, Y., Huang, T.S.: View-independent recognition of hand postures. In: CVPR, vol. 2, pp. 88–94. Hilton Head Island, USA (2000)

    Google Scholar 

  18. Xiong, X., De la Torre, F.: Supervised descent method and its applications to face alignment. In: CVPR, pp. 532–539. Portland, USA (2013)

    Google Scholar 

Download references

Acknowledgments

This work was partially supported by the EU project FP7-IP- 288533 Robohow. The contributions of Iason Oikonomidis and Nikolaos Kyriazis, members of FORTH/CVRL, are gratefully acknowledged.

Author information

Authors and Affiliations

  1. Institute of Computer Science, Foundation for Research and Technology, Heraklion, Greece

    Konstantinos Paliouras & Antonis A. Argyros

  2. Computer Science Department, University of Crete, Heraklion, Crete, Greece

    Konstantinos Paliouras & Antonis A. Argyros

Authors
  1. Konstantinos Paliouras
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Antonis A. Argyros
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Antonis A. Argyros .

Editor information

Editors and Affiliations

  1. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Aleksandra Gruca

  2. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Agnieszka Brachman

  3. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Stanisław Kozielski

  4. Institute of Informatics, Silesian University of Technology, Gliwice, Poland

    Tadeusz Czachórski

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Paliouras, K., Argyros, A.A. (2016). Towards the Automatic Definition of the Objective Function for Model-Based 3D Hand Tracking. In: Gruca, A., Brachman, A., Kozielski, S., Czachórski, T. (eds) Man–Machine Interactions 4. Advances in Intelligent Systems and Computing, vol 391. Springer, Cham. https://doi.org/10.1007/978-3-319-23437-3_30

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-23437-3_30

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23436-6

  • Online ISBN: 978-3-319-23437-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation