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Optimal camera selection in vision networks for shape approximation

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Abstract
Within a camera network, the contribution of a camera to the observation of a scene depends on its viewpoint and on the scene configuration. This is a dynamic property, as the scene content is subject to change over time. An automatic selection of a subset of cameras that significantly contributes to the desired observation of a scene can be of great value for the reduction of the amount of transmitted or stored image data. In this work, we propose low data rate schemes to select from a vision network a subset of cameras that provides a good frontal observation of the persons in the scene and allows for the best approximation of their 3D shape. We also investigate to what degree low data rates trade off quality of reconstructed 3D shapes.

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MLA
Morbée, Marleen, et al. “Optimal Camera Selection in Vision Networks for Shape Approximation.” 2008 IEEE 10TH WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING, VOLS 1 AND 2, IEEE, 2008, pp. 46–51.
APA
Morbée, M., Tessens, L., Lee, H., Philips, W., & Aghajan, H. (2008). Optimal camera selection in vision networks for shape approximation. 2008 IEEE 10TH WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING, VOLS 1 AND 2, 46–51. New York, NY, USA: IEEE.
Chicago author-date
Morbée, Marleen, Linda Tessens, Huang Lee, Wilfried Philips, and Hamid Aghajan. 2008. “Optimal Camera Selection in Vision Networks for Shape Approximation.” In 2008 IEEE 10TH WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING, VOLS 1 AND 2, 46–51. New York, NY, USA: IEEE.
Chicago author-date (all authors)
Morbée, Marleen, Linda Tessens, Huang Lee, Wilfried Philips, and Hamid Aghajan. 2008. “Optimal Camera Selection in Vision Networks for Shape Approximation.” In 2008 IEEE 10TH WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING, VOLS 1 AND 2, 46–51. New York, NY, USA: IEEE.
Vancouver
1.
Morbée M, Tessens L, Lee H, Philips W, Aghajan H. Optimal camera selection in vision networks for shape approximation. In: 2008 IEEE 10TH WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING, VOLS 1 AND 2. New York, NY, USA: IEEE; 2008. p. 46–51.
IEEE
[1]
M. Morbée, L. Tessens, H. Lee, W. Philips, and H. Aghajan, “Optimal camera selection in vision networks for shape approximation,” in 2008 IEEE 10TH WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING, VOLS 1 AND 2, Cairns, Australia, 2008, pp. 46–51.
@inproceedings{517755,
  abstract     = {{Within a camera network, the contribution of a camera to the observation of a scene depends on its viewpoint and on the scene configuration. This is a dynamic property, as the scene content is subject to change over time. An automatic selection of a subset of cameras that significantly contributes to the desired observation of a scene can be of great value for the reduction of the amount of transmitted or stored image data. In this work, we propose low data rate schemes to select from a vision network a subset of cameras that provides a good frontal observation of the persons in the scene and allows for the best approximation of their 3D shape. We also investigate to what degree low data rates trade off quality of reconstructed 3D shapes.}},
  author       = {{Morbée, Marleen and Tessens, Linda and Lee, Huang and Philips, Wilfried and Aghajan, Hamid}},
  booktitle    = {{2008 IEEE 10TH WORKSHOP ON MULTIMEDIA SIGNAL PROCESSING, VOLS 1 AND 2}},
  isbn         = {{978-1-4244-2294-4}},
  language     = {{eng}},
  location     = {{Cairns, Australia}},
  pages        = {{46--51}},
  publisher    = {{IEEE}},
  title        = {{Optimal camera selection in vision networks for shape approximation}},
  year         = {{2008}},
}

Web of Science
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