Concurrent learning of visual codebooks and object categories in open-ended domains

Abstract

In open-ended domains, robots must continuously learn new object categories. When the training sets are created offline, it is not possible to ensure their representativeness with respect to the object categories and features the system will find when operating online. In the Bag of Words model, visual codebooks are usually constructed from training sets… (More)
DOI: 10.1109/IROS.2015.7353715

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