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ICCV
1999
IEEE

Control in a 3D Reconstruction System using Selective Perception

10 years 11 months ago
Control in a 3D Reconstruction System using Selective Perception
This paper presents a control structure for general purpose image understanding that addresses both the high level of uncertainty in local hypotheses and the computational complexity of image interpretation. The control of vision algorithms is performed by an independent subsystem that uses Bayesian networks and utility theory to compute the marginal value of information provided by alternative operators and selects the ones with the highest value. We have implemented and tested this control structure with several aerial image datasets. The results show that the knowledge base used by the system can be acquired using standard learning techniques and that the value-driven approach to the selection of vision algorithms leads to performance gains. Moreover, the modular system architecture simpli es the addition of both control knowledge and new vision algorithms.
Maurício Marengoni, Allen R. Hanson, Shlomo
Added 15 Oct 2009
Updated 15 Oct 2009
Type Conference
Year 1999
Where ICCV
Authors Maurício Marengoni, Allen R. Hanson, Shlomo Zilberstein, Edward M. Riseman
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