Skip to main content
SpringerLink
Log in
Book cover

Advanced Man-Machine Interaction pp 191–261Cite as

Person Recognition and Tracking

  • Chapter

Part of the book series: Signals and Communication Technology ((SCT))

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   169.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   299.00
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ahonen, T., Hadid, A., and Pietikäinen, M. Face Recognition with Local Binary Patterns. In Proceedings of the 8th European Conference on Computer Vision, pages 469–481. Springer, Prague, Czech Republic, May 11–14 2004.

    Google Scholar 

  2. Alvarado, P., Dörfler, P., and Wickel, J. AXON 2-A Visual Object Recognition System for Non-Rigid Objects. In Hamza, M. H., editor, IASTED International Conference-Signal Processing, Pattern Recognition and Applications (SPPRA), pages 235–240. Rhodes, Greece, July 3–6 2001.

    Google Scholar 

  3. Batista, J. Tracking Pedestrians Under Occlusion Using Multiple Cameras. In Int. Conference on Image Analysis and Recognition, volume Lecture Notes in Computer Science 3212, pages 552–562. 2004.

    Google Scholar 

  4. Belhumeur, P., Hespanha, J., and Kriegman, D. Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection. In IEEE Transactions on Pattern Analysis and Machine Intelligence, pages 711–720. 1997.

    Google Scholar 

  5. Bileschi, S. and Heisele, B. Advances in Component-based Face Detection. In 2003 IEEE International Workshop on Analysis and Modeling of Faces and Gestures, AMFG 2003, pages 149–156. IEEE, October 2003.

    Google Scholar 

  6. Bishop, C. Neural Networks for Pattern Recognition. Oxford University Press, 1995.

    Google Scholar 

  7. Bradski, G. Computer Vision Face Tracking for Use in a Perceptual User Interface. Intel Technology Journal, Q2, 1998.

    Google Scholar 

  8. Brunelli, R. and Poggio, T. Face Recognition: Features versus Templates. IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(10):1042–1052, 1993.

    Article  Google Scholar 

  9. Cheng, Y. Mean Shift, Mode Seeking and Clustering. IEEE PAMI, 17:790–799, 1995.

    Google Scholar 

  10. Chung, K., Kee, S., and Kim, S. Face Recognition Using Principal Component Analysis of Gabor Filter Responses. In International Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems. 1999.

    Google Scholar 

  11. Comaniciu, D. and Meer, P. Mean Shift: A Robust Approach toward Feature Space Analysis. IEEE PAMI, 24(5):603–619, 2002.

    Google Scholar 

  12. Cootes, T. and Taylor, C. Statistical Models of Appearance for Computer Vision. Technical report, University of Manchester, September 1999.

    Google Scholar 

  13. Cootes, T. and Taylor, C. Statistical Models of Appearance for Computer Vision. Technical report, Imaging Science and Biomedical Engineering, University of Manchester, March 2004.

    Google Scholar 

  14. Craw, I., Costen, N., Kato, T., and Akamatsu, S. How Should We Represent Faces for Automatic Recognition? IEEE Transactions on Pattern Recognition and Machine Intelligence, 21(8):725–736, 1999.

    Article  Google Scholar 

  15. Dempster, A., Laird, N., and Rubin, D. Maximum Likelihood from Incomplete Data Using the EM Algorithm. Journal of the Royal Statistical Society, Series B, 39(1):1–38, 1977.

    MathSciNet  MATH  Google Scholar 

  16. Duda, R. and Hart, P. Pattern Classification and Scene Analysis. John Wiley & Sons, 1973.

    Google Scholar 

  17. Elgammal, A. and Davis, L. Probabilistic Framework for Segmenting People Under Occlusion. In IEEE ICCV, volume 2, pages 145–152. 2001.

    Google Scholar 

  18. Fillbrandt, H. and Kraiss, K.-F. Tracking People on the Ground Plane of a Cluttered Scene with a Single Camera. WSEAS Transactions on Information Science and Applications, 9(2):1302–1311, 2005.

    Google Scholar 

  19. Gavrila, D. The Visual Analysis of Human Movement: A Survey. Computer Vision and Image Understanding, 73(1):82–98, 1999.

    Article  MATH  Google Scholar 

  20. Georghiades, A., Belhumeur, P., and 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.

    Article  Google Scholar 

  21. Gutta, S., Huang, J., Singh, D., Shah, I., Takács, B., and Wechsler, H. Benchmark Studies on Face Recognition. In Proceedings of the International Workshop on Automatic Face-and Gesture-Recognition (IWAFGR). Zürich, Switzerland, 1995.

    Google Scholar 

  22. Hähnel, M., Klünder, D., and Kraiss, K.-F. Color and Texture Features for Person Recognition. In International Joint Conference onf Neural Networks (IJCNN 2004). Budapest, Hungary, July 2004.

    Google Scholar 

  23. Haritaoglu, I., Harwood, D., and Davis, L. Hydra: Multiple People Detection and Tracking Using Silhouettes. In Proc. IEEE Workshop on Visual Surveillance, pages 6–13. 1999.

    Google Scholar 

  24. Haritaoglu, I., Harwood, D., and Davis, L. W4: Real-Time Surveillance of People and Their Activities. IEEE PAMI, 22(8):809–830, 2000.

    Google Scholar 

  25. Harville, M. and Li, D. Fast, Integrated Person Tracking and Activity Recognition with Plan-View Templates from a Single Stereo Camera. In IEEE CVPR, volume 2, pages 398–405. 2004.

    Google Scholar 

  26. Heisele, B., Ho, P., and Poggio, T. Face Recognition with Support Vector Machines: Global versus Component-based Approach. In ICCV01, volume 2, pages 688–694. 2001.

    Google Scholar 

  27. Kanade, T. Computer Recognition of Human Faces. Birkhauser, Basel, Switzerland, 1973.

    Google Scholar 

  28. Lades, M., Vorbrüggen, J., Buhmann, J., Lange, J., von der Malsburg, C., Würtz, R. P., and Konen, W. Distortion Invariant Object Recognition in the Dynamic Link Architecture. IEEE Transactions on Computers, 42(3):300–311, 1993.

    Article  Google Scholar 

  29. Manjunath, B., Salembier, P., and Sikora, T. Introduction to MPEG-7. John Wiley and Sons, Ltd., 2002.

    Google Scholar 

  30. Martinez, A. Recognizing Imprecisely Localized, Partially Occluded, and Expression Variant Faces from a Single Sample per Class. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24(6):748–763, June 2002.

    Article  Google Scholar 

  31. Martinez, A. and Benavente, R. The AR face database. Technical Report 24, CVC, 1998.

    Google Scholar 

  32. McKenna, S., Jabri, S., Duric, Z., Wechsler, H., and Rosenfeld, A. Tracking Groups of People. CVIU, 80(1):42–56, 2000.

    MATH  Google Scholar 

  33. Melnik, O., Vardi, Y., and Zhang, C.-H. Mixed Group Ranks: Preference and Confidence in Classifier Combination. PAMI, 26(8):973–981, August 2004.

    Google Scholar 

  34. Mittal, A. and Davis, L. M2-Tracker: A Multi-View Approach to Segmenting and Tracking People in a Cluttered Scene. Int. Journal on Computer Vision, 51(3):189–203, 2003.

    Article  Google Scholar 

  35. Moeslund, T. Summaries of 107 Computer Vision-Based Human Motion Capture Papers. Technical Report LIA 99-01, University of Aalborg, March 1999.

    Google Scholar 

  36. Moeslund, T. and Granum, E. A Survey of Computer Vision-Based Human Motion Capture. Computer Vision and Image Understanding, 81(3):231–268, 2001.

    Article  MATH  Google Scholar 

  37. Nakajima, C., Pontil, M., Heisele, B., and Poggio, T. Full-body Person Recognition System. Pattern Recognition, 36:1997–2006, 2003.

    Article  MATH  Google Scholar 

  38. Ohm, J. R., Cieplinski, L., Kim, H. J., Krishnamachari, S., Manjunath, B. S., Messing, D. S., and Yamada, A. Color Descriptors. In Manjunath, B., Salembier, P., and Sikora, T., editors, Introduction to MPEG-7, chapter 13, pages 187–212. Wiley & Sons, Inc., 2002.

    Google Scholar 

  39. Penev, P. and Atick, J. Local Feature Analysis: A General Statistical Theory for Object Representation. Network: Computation in Neural Systems, 7(3):477–500, 1996.

    Article  MATH  Google Scholar 

  40. Pentland, A., Moghaddam, B., and Starner, T. View-based and Modular Eigenspaces for Face Recognition. In IEEE Conference on Computer Vision and Pattern Recognition (CVPR’94). Seattle, WA, June 1994.

    Google Scholar 

  41. Phillips, P., Moon, H., Rizvi, S., and Rauss, P. The FERET Evaluation Methodology for Face-Recognition Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(10):1090–1104, October 2000.

    Article  Google Scholar 

  42. Ro, Y., Kim, M., Kang, H., Manjunath, B., and Kim, J. MPEG-7 Homogeneous Texture Descriptor. ETRI Journal, 23(2):41–51, June 2001.

    Google Scholar 

  43. Schwaninger, A., Mast, F., and Hecht, H. Mental Rotation of Facial Components and Configurations. In Proceedings of the Psychonomic Society 41st Annual Meeting. New Orleans, USA, 2000.

    Google Scholar 

  44. Sirovich, L. and Kirby, M. Low-Dimensional Procedure for the Characterization of Human Faces. Journal of the Optical Society of America, 4(3):519–524, 1987.

    Google Scholar 

  45. Sung, K. K. and Poggio, T. Example-Based Learning for View-Based Human Face Detection. IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(1):39–51, 1997.

    Article  Google Scholar 

  46. Swain, M. and Ballard, D. Color Indexing. Int. Journal on Computer Vision, 7(1):11–32, 1991.

    Article  Google Scholar 

  47. Turk, M. A Random Walk through Eigenspace. IEICE Transactions on Information and Systems, E84-D(12):1586–1595, 2001.

    Google Scholar 

  48. Turk, M. and Pentland, A. Eigenfaces for Recognition. Journal of Cognitive Neuroscience, 3(1):71–86, 1991.

    Article  Google Scholar 

  49. Vapnik, V. Statistical Learning Theory. Wiley & Sons, Inc., 1998.

    Google Scholar 

  50. Viola, P. and Jones, M. Robust Real-time Object Detection. In ICCV01, 2, page 747. 2001.

    Google Scholar 

  51. Wallraven, C. and Bülthoff, H. View-based Recognition under Illumination Changes Using Local Features. In Proceedings of the International Conference on Computer Vision and pattern Recognition (CVPR). Kauai, Hawaii, December, 8–14 2001.

    Google Scholar 

  52. Waring, C. A. and Liu, X. Face Detection Using Spectral Histograms and SVMs. IEEE Transactions on Systems, Man, and Cybernetics-Part B: Cybernetics, 35(3):467–476, June 2005.

    Article  Google Scholar 

  53. Welch, G. and Bishop, G. An Introduction to the Kalman Filter. Technical Report TR 95-041, Department of Computer Science, University of North Carolina at Chapel Hill, 2004.

    Google Scholar 

  54. Wickel, J., Alvarado, P., Dörfler, P., Krüger, T., and Kraiss, K.-F. Axiom-A Modular Visual Object Retrieval System. In Jarke, M., Koehler, J., and Lakemeyer, G., editors, Proceedings of 25th German Conference on Artificial Intelligence (KI 2002), Lecture Notes in Artificial Intelligence, pages 253–267. Springer, Aachen, September 2002.

    Google Scholar 

  55. Wiskott, L., Fellous, J., Krüger, N., and von der Malsburg, C. Face Recognition by Elastic Bunch Graph Matching. IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7):775–779, 1997.

    Article  Google Scholar 

  56. Wren, C., Azerbayejani, A., Darell, T., and Pentland, A. Pfinder: Real-Time Tracking of the Human Body. IEEE PAMI, 19(7):780–785, 1997.

    Google Scholar 

  57. Yang, J., Zhu, X., Gross, R., Kominek, J., Pan, Y., and Waibel, A. Multimodal People ID for a Multimedia Meeting Browser. In Proceedings of the Seventh ACM International Conference on Multimedia, pages 159–168. ACM, Orlando, Florida, United States, 1999.

    Google Scholar 

  58. Yang, M., Kriegman, D., and Ahuja, N. Detecting Faces in Images: A Survey. IEEE Transactions on Pattern Analysis and Machine Intelligence, 24:34–58, 2002.

    Article  Google Scholar 

  59. Zhao, T. and Nevatia, R. Tracking Multiple Humans in Complex Situations. IEEE PAMI, 26(9):1208–1221, 2004.

    Google Scholar 

  60. Zhao, W., Chellappa, R., Phillips, P. J., and Rosenfeld, A. Face recognition: A Literature Survey. ACM Computing Surveys, 35(4):399–458, 2003.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. RWTH Aachen University, Aachen, Germany

    Dipl.-Ing. Michael Hähnel (Chair of Technical Computer Science) & Dipl.-Ing. Holger Fillbrandt (Chair of Technical Computer Science)

Authors
  1. Dipl.-Ing. Michael Hähnel
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Dipl.-Ing. Holger Fillbrandt
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. RWTH Aachen University, Ahornstraße 55, 52074, Aachen, Germany

    Karl-Friedrich Kraiss (Chair of Technical Computer Science) (Chair of Technical Computer Science)

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Hähnel, M., Fillbrandt, H. (2006). Person Recognition and Tracking. In: Kraiss, KF. (eds) Advanced Man-Machine Interaction. Signals and Communication Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-30619-6_5

Download citation

  • DOI: https://doi.org/10.1007/3-540-30619-6_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30618-4

  • Online ISBN: 978-3-540-30619-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation