|Adaptive scene-dependent filters in online learning environments
|Year of Publication
|Götting M, Steil JJ, Wersing H, Körner E, Ritter H
|New issues in neurocomputing. 13th European Symposium on Artificial Neural Networks 2005
In this paper we propose the Adaptive Scene Dependent Filters (ASDF) to enhance the online learning capabilities of an object recognition system in real-world scenes. The ASDF method proposed extends the idea of unsupervised segmentation to a flexible, highly dynamic image segmentation architecture. We combine unsupervised segmentation to define coherent groups of pixels with a recombination step using top-down information to determine which segments belong together to the object. We show the successful application of this approach to online learning in cluttered environments.