We present a biologically inspired vision system able to incrementally learn multiple visual categories by interactively presenting several hand-held objects. The overall system is composed of a foreground-background separation part, several feature extraction methods and a life-long learning approach combining incremental learning with category specific feature selection. In contrast to most visual categorization approaches where typically each view is assigned to a single category we allow labeling with an arbitrary number of shape and color categories and also impose no restrictions to the viewing angle of presented objects. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Kirstein, S., Wersing, H., Gross, H. M., & Körner, E. (2009). An integrated system for incremental learning of multiple visual categories. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5506 LNCS, pp. 813–820). https://doi.org/10.1007/978-3-642-02490-0_99
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