Stephan Kirstein, Alexander Denecke, Stephan Hasler, Heiko Wersing, Horst-Michael Groß, Edgar Körner, "A Vision Architecture for Unconstrained and Incremental Learning of Multiple Categories", Memetic Computing, vol. 1, no. 4, pp. 291–304, 2009.

We present an integrated vision architecture capable of incrementally learning several visual categories based on natural hand-held objects. Ad- ditionally we focus on interactive learning, which requires real-time image processing methods and a fast learning algorithm. The overall system is composed of a figure-ground segregation part, several feature extraction methods and a life-long learning approach combining incremental learn- ing with category-specific feature selection. In contrast to most visual categorization approaches, where typically each view is assigned to a sin- gle category, we allow labeling with an arbitrary number of shape and color categories. We also impose no restrictions on the viewing angle of presented objects, relaxing the common constraint on canonical views.