Real-Time Face Detection and Recognition on LEGO Mindstorms NXT Robot

  • Tae-Hoon Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4642)

Abstract

This paper addresses a real-time implementation of face recognition system with LEGO Mindstorms NXT robot and wireless camera. This system is organized to capture an image sequence, find the features of face in the images, and recognize and verify a person. Moreover, this system can collect the facial images of various poses due to movable robot, which enables this system to increase performance. The current implementation uses the LDA(Linear Discriminant Analysis) learning algorithm considering the number of training data. We have made several tests on video data, and measured the performance and the speed of the proposed system in real environment. Finally, the result has confirmed that the proposed system is better than conventional PC-based systems.

Keywords

LEGO Mindstorms NXT robot real-time face recognition 

References

  1. 1.
    Tan, X., Chen, S., Zhou, Z.-H., Zhang, F.: Face recognition from a single image per person: A survey. Pattern Recognition 39(9), 1725–1745 (2006)MATHCrossRefGoogle Scholar
  2. 2.
    Gilbert, J.M., Yang, W.: A Real-Time Face Recognition System Using Custom VLSI Hardware. In: Proc. of Computer Architectures for Machine Perceptron Workshop, New Orleans, USA, pp. 58–66 (1993)Google Scholar
  3. 3.
    Yang, F., Paindavoine, M., Abdi, H.: Parallel Implementation on DSPs of a Face Detection Algorithm. In: Proc. of International Conference on the Software Process, Chicago, USA (1998)Google Scholar
  4. 4.
    IBM ZISC036 Data Sheet: http://www.ibm.com
  5. 5.
    Zhou, S., Chellappa, R.: Rank constrained recognition under unknown illuminations. In: IEEE International Workshop on Analysis and Modeling of Faces and Gestures (2003)Google Scholar
  6. 6.
    Georghiades, A., Belhumeur, P., Kriegman, D.: From Few to Many: Illumination Cone Models for Face Recognition under Variable lighting and Pose. IEEE Transactions. on Pattern Analysis and Machine Intelligence 23(6), 643–660 (2001)CrossRefGoogle Scholar
  7. 7.
    Gross, R., Matthews, I., Baker, S.: Appearance-Based Face Recognition and Light-Fields. IEEE Transactions on Pattern Analysis and Machine Intelligence 26(4), 449–465 (2004)CrossRefGoogle Scholar
  8. 8.
    Blanz, V., Vetter, T.: Face Recognition Based on Fitting a 3D Morphable Model. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(9), 1063–1074 (2003)CrossRefGoogle Scholar
  9. 9.
    Sharad, S.: Introducing Embedded Design Concepts to Freshmen and Sophomore Engineering Students with LEGO MINDSTORMS NXT. In: IEEE International Conference on Microelectronic System Education, pp. 119–120. IEEE Computer Society Press, Los Alamitos (2007)CrossRefGoogle Scholar
  10. 10.
    LEGO Mindstorms NXT Hardware Developers Kit: http://mindstorms.lego.com/overview/nxtreme.aspx
  11. 11.
    Turk, M., Pentland, A.: Eigen faces for recognition. Journal of Cognitive Neuroscience 3, 71–86 (1991)CrossRefGoogle Scholar
  12. 12.
    Martinez, A.M., Kak, A.C.: PCA versus LDA. IEEE Transaction on Pattern Analysis and Machine Intelligence 23(2), 228–233 (2001)CrossRefGoogle Scholar
  13. 13.
    Viola, P., Jones, M.: Robust Real-time Face Detection. International Journal of Computer Vision 57(2) (2004)Google Scholar
  14. 14.
  15. 15.
  16. 16.

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Tae-Hoon Lee
    • 1
  1. 1.Center for Cognitive Robotics, Korea Institute of Science and Technology, 39-1 Hawolgok-dong, Seongbuk-gu, Seoul 136-791Republic of Korea

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