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Human Detection and Tracking

  • Reference work entry
  • First Online:
Encyclopedia of Biometrics
  • 229 Accesses

Synonyms

Association; Correspondence; Localization; Pedestrian detection; Target detection; Video surveillance

Definition

Human detection and tracking are tasks of computer vision systems for locating and following people in video imagery. Human detection is the task of locating all instances of human beings present in an image, and it has been most widely accomplished by searching all locations in the image, at all possible scales, and comparing a small area at each location with known templates or patterns of people. Human tracking is the process of temporally associating the human detections within a video sequence to generate persistent paths, or trajectories, of the people. Human detection and tracking are generally considered the first two processes in a video surveillance pipeline and can feed into higher-level reasoning modules such as action recognition and dynamic scene analysis.

Introduction

In relation to large-scale biometric and video surveillance systems, there is an...

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References

  1. M. Oren, C. Papageorgiou, P. Sinha, E. Osuma, T. Poggio, Pedestrian detection using wavelet templates, in Proceedings of Computer Vision and Pattern Recognition, San Juan, 1997

    Google Scholar 

  2. N. Dalal, B. Triggs, C. Schmid, Human detection using oriented histograms of flow and appearance, in Proceedings of European Conference on Computer Vision, Graz, 2006

    Google Scholar 

  3. O. Tuzel, F. Porikli, P. Meer, Human detection via classification on riemannian manifolds, in Proceedings of Computer Vision and Pattern Recognition, Minneapolis, 2007

    Google Scholar 

  4. P. Viola, M. Jones, D. Snow, Detecting pedestrians using patterns of motion and appearance, in Proceedings of International Conference Computer Vision, Nice, 2003

    Google Scholar 

  5. Y. Wu, T. Yu, A field model for human detection and tracking. IEEE Trans. Pattern Anal. Mach. Intell. 28(5), 753–765 (2006)

    Google Scholar 

  6. D. Ramanan, D. Forsyth, A. Zisserman, Strike a pose: tracking people by finding stylized poses. in Proceedings of Computer Vision and Pattern Recognition, San Diego, 2005

    Google Scholar 

  7. S. Lee, Y. Liu, R. Collins, Shape variation-based frieze pattern for robust gait recognition. in Proceedings of Computer Vision and Pattern Recognition, Minneapolis, 2007

    Google Scholar 

  8. V. Sharma, J. Davis, Integrating appearance and motion cues for simultaneous detection and segmentation of pedestrians, in Proceedings of International Conference Computer Vision, Rio de Janeiro, 2007

    Google Scholar 

  9. B. Leibe, E. Seemann, B. Schiele, Pedestrian detection in crowded scenes, in Proceedings of Computer Vision and Pattern Recognition, San Diego, 2005

    Google Scholar 

  10. A. Yilmaz, O. Javed, M. Shah, Object tracking: a survey. ACM Comput. Surv. 38(4), (2006)

    Google Scholar 

  11. K. Rangarajan, M. Shah, Establishing motion correspondence. Comput. Vis. Graph. Img. Proc. 54(1), 56–73 (1991)

    MATH  Google Scholar 

  12. R. Kalman, A new approach to linear filtering and prediction problems. Trans. ASME-J. Basic Eng. 82, 35–45 (1960)

    Google Scholar 

  13. S. Julier, J. Uhlmann, A new extension to the kalman filter to nonlinear systems, in SPIE AeroSense Symposium, Orlando, 1997

    Google Scholar 

  14. M. Isard, A. Blake, Condensation – conditional density propagation for visual tracking. Int. J. Comput. Vis. 29(1), 5–28 (1998)

    Google Scholar 

  15. D. Comaniciu, V. Ramesh, P. Meer, Kernel-based object tracking. IEEE Trans. Pattern Anal. Mach. Intell. 25(5), 564–577 (2003)

    Google Scholar 

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Davis, J.W., Sharma, V., Tyagi, A., Keck, M. (2015). Human Detection and Tracking. In: Li, S.Z., Jain, A.K. (eds) Encyclopedia of Biometrics. Springer, Boston, MA. https://doi.org/10.1007/978-1-4899-7488-4_35

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