Özet:
t. In this paper, an 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 that are
updated online according to an active fusion method based on performing orthogonal 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 is developed to evaluate the performance of the algorithm in handling the problems where data arrives sequentially. In this
case, the oracle is the security guard of the forest lookout tower verifying
the decision of the combined algorithm. Simulation results are presented.