Entropy functional based adaptive decision fusion framework
Töreyin, B. U.
Çetin, A. E.
2012 20th Signal Processing and Communications Applications Conference, SIU 2012, Proceedings
1 - 4
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In this paper, an entropy functional based online adaptive decision fusion framework is developed for image analysis and computer vision applications. In this framework, it is assumed that the compound algorithm consists of several sub-algorithms, each of which yields its own decision as a real number centered around zero, representing the confidence level of that particular sub-algorithm. Decision values are linearly combined with weights which are updated online according to an active fusion method based on performing entropic projections onto convex sets describing sub-algorithms. It is assumed that there is an oracle, who is usually a human operator, providing feedback to the decision fusion method. A video based wildfire detection system was developed to evaluate the performance of the decision fusion algorithm.
Computer vision applications
Decision fusion methods
Projections onto convex sets
Permalink (Please cite this version)http://hdl.handle.net/11693/28193
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