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An information theoretic approach to camera control for crowded scenes

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Abstract

Navigation and monitoring of large and crowded virtual environments is a challenging task and requires intuitive camera control techniques to assist users. In this paper, we present a novel automatic camera control technique providing a scene analysis framework based on information theory. The developed framework contains a probabilistic model of the scene to build entropy and expectancy maps. These maps are utilized to find interest points which represent either characteristic behaviors of the crowd or novel events occurring in the scene. After an interest point is chosen, the camera is updated accordingly to display this point. We tested our model in a crowd simulation environment and it performed successfully. Our method can be integrated into existent camera control modules in computer games, crowd simulations and movie pre-visualization applications.

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Authors and Affiliations

  1. Computer Graphics Laboratory, Sabanci University, Istanbul, Turkey

    Cagatay Turkay, Emre Koc & Selim Balcisoy

Authors
  1. Cagatay Turkay
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  2. Emre Koc
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  3. Selim Balcisoy
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Corresponding author

Correspondence to Cagatay Turkay.

Additional information

This research is partially supported by Sabanci University Internal Grant IACF06-00423 and Istanbul Metropolitan Municipality Research Grant.

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Turkay, C., Koc, E. & Balcisoy, S. An information theoretic approach to camera control for crowded scenes. Vis Comput 25, 451–459 (2009). https://doi.org/10.1007/s00371-009-0337-1

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