NDLI: Optimal camera selection in vision networks for shape approximation

Content Provider	IEEE Xplore Digital Library
Author	Morbee, M. Tessens, L. Huang Lee Philips, W. Aghajan, H.
Copyright Year	2008
Description	Author affiliation: Dept. of Electr. Eng., Stanford Univ., Stanford, CA (Huang Lee; Aghajan, H.) \|\| TELIN-IPI-IBBT, Ghent Univ., Ghent (Morbee, M.; Tessens, L.; Philips, W.)
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.
Starting Page	46
Ending Page	51
File Size	640713
Page Count	6
File Format	PDF
ISBN	9781424422944
DOI	10.1109/MMSP.2008.4665047
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-08
Publisher Place	Australia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cameras Visualization Approximation methods Shape Base stations Image reconstruction Three dimensional displays
Content Type	Text
Resource Type	Article

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