We present a self-valuing learning technique which is capable of learning how to grasp unfamiliar objects and generalize the learned abilities. The learning system consists of two...
This contribution proposes a compositionality architecture for visual object categorization, i.e., learning and recognizing multiple visual object classes in unsegmented, cluttered...
Recently the "bag of words" model becomes popular in the approaches to object recognition. These approaches model an image as a collection of local patches called "...
Visual search is a common daily human activity and a prerequisite to the interaction with objects encountered in cluttered environments. Humanoid robots that are supposed to take p...
Common objects such as people and cars comprise many visual parts and attributes, yet image-based tracking algorithms are often keyed to only one of a target's identifying ch...