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Camera cooperation for achieving visual attention

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Abstract

In this paper we address the problem of establishing a computational model for visual attention using cooperation between two cameras. More specifically we wish to maintain a visual event within the field of view of a rotating and zooming camera through the understanding and modeling of the geometric and kinematic coupling between a static camera and an active camera. The static camera has a wide field of view thus allowing panoramic surveillance at low resolution. High-resolution details may be captured by a second camera, provided that it looks in the right direction. We derive an algebraic formulation for the coupling between the two cameras and we specify the practical conditions yielding a unique solution. We describe a method for separating a foreground event (such as a moving object) from its background while the camera rotates. A set of outdoor experiments shows the two-camera system in operation.

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References

  1. Murray, D., Basu, A.: Motion tracking with an active camera. IEEE Trans. Pattern Anal. Machine Inttel. 16(5), 449–459 (1994)

    Article  Google Scholar 

  2. Fayman, J.A., Sudarsky, O., Rivlin, E., Rudzsky, M.: Zoom tracking and its applications. Machine Vision Appl. 13(1), 25–37 (2001)

    Article  Google Scholar 

  3. Daniilidis, K., Krauss, C., Hansen, M., Sommer, G.: Real time tracking of moving objects with an active camera. Real Time Imag. 4(1), 3–20 (1998)

    Article  Google Scholar 

  4. Murray, D.W., Bradshaw, K.J., McLauchlan, P.F., Reid, I.D., Sharkey, P.M.: Driving saccade to pursuit using image motion. Int. J. Comput. Vision 16(3), 205–228 (1995)

    Article  Google Scholar 

  5. Coombs, D., Brown, C.: Real-time binocular smooth pursuit. Int. J. Comput. Vision 11(2), 147–164 (1993)

    Article  Google Scholar 

  6. Batista, J., Peixoto, P., Araujo, H.: Real-time active visual surveillance by integrating peripheral motion detection with foveated tracking. In: IEEE Workshop on Visual Surveillance. Mumbai, India (1998)

  7. Martin, F., Horaud, R.: Multiple camera tracking of rigid objects. Int. J. Robot. Res. 21(2), 97–113 (2002)

    Article  Google Scholar 

  8. Hartley, R., Zisserman, A.: Multiple View Geometry in Computer Vision. Cambridge University Press, Cambridge, UK (2000)

  9. Peixoto, P., Batista, J., Araujo, H.: Integration of information from several vision systems for a common task of surveillance. In: 6th International Workshop on Intelligent Robotics Systems. Edinburgh, UK (1998)

  10. Crétual, A., Chaumette, F.: Application of motion-based visual servoing to target tracking. Int. J. Robot. Res. 20(11), 878–890 (2001)

    Article  Google Scholar 

  11. McCarthy, J.M.: Introduction to Theoretical Kinematics. MIT Press, Cambridge (1990)

  12. Murray, R.M., Li, Z., Sastry, S.S.: A Mathematical Introduction to Robotic Manipulation. CRC Press, Ann Arbor (1994)

    MATH  Google Scholar 

  13. Mooring, B.W., Roth, Z.S., Driels, M.R.: Fundamentals of Manipulator Calibration. Wiley, New York (1991)

    Google Scholar 

  14. Cox, D., Little, J., O'Shea, D.: Using Algebraic Geometry. Springer, Berlin Heidelberg, New York (1998)

    MATH  Google Scholar 

  15. Hartley, R.I.: Self-calibration from multiple views with a rotating camera. In: Proceedings of the Third European Conference on Computer Vision, pp. 471–478. Stockholm, Sweden (May 1994)

  16. Irani, M., Anandan, P.: About direct methods. In: Triggs, B., Zisserman, A., Szeliski, R. (eds.) Vision Algorithms: Theory and Practice, Corfu, Greece, July 1999. LNCS 1883, pp. 267–277. Springer-Verlag, Berlin Heidelberg New York (1999)

  17. Shum, H.-Y., Szeliski, R.: Systems and experiment paper: construction of panoramic mosaics with global and local alignment. Int. J. Comput. Vision 36(2), 101–130 (2000)

    Article  Google Scholar 

  18. Bartoli, A., Dalal, N., Horaud, R.: Motion panoramas. Comput. Animation Virtual Worlds 15(6), 501–517 (2004)

    Article  Google Scholar 

  19. Dufaux, F., Moscheni, F.: Background mosaicking for low bit rate video coding. In: Proceedings IEEE International Conference on Image Processing, vol. 1, pp. 673–676. Lausanne, Switzerland (1996)

  20. Personnaz, M., Horaud, R.: Camera calibration: estimation, validation and software. Technical Report RT-0258. INRIA Rhone Alpes, Grenoble (2002)

  21. Personnaz, M., Sturm, P.: Calibration of a stereo-vision system by the non-linear optimization of the motion of a calibration object. Technical Report RT-0269, INRIA (2002)

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Authors and Affiliations

  1. INRIA Rhône-Alpes, 655, Avenue de l'Europe, Montbonnot Saint-Martin, France, 38330

    Radu Horaud, David Knossow & Markus Michaelis

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  1. Radu Horaud
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  2. David Knossow
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  3. Markus Michaelis
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Correspondence to Radu Horaud.

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Horaud, R., Knossow, D. & Michaelis, M. Camera cooperation for achieving visual attention. Machine Vision and Applications 16, 1–2 (2006). https://doi.org/10.1007/s00138-005-0182-9

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  • DOI: https://doi.org/10.1007/s00138-005-0182-9

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