A Framework for Continuous Learning of Simple Visual Concepts

We present a continuous learning framework for learning simple visual concepts and its implementation in an artificial cognitive system. The main goal is to learn as- sociations between automatically extracted visual features and words that describe the scene in an open-ended, contin- uous manner. In particular, we address the problem of cross- modal learning of elementary visual properties and spatial relations; we show that the same learning mechanism can be used to learn both types of concepts. We introduce and analyse several learning modes requiring different levels of tutor supervision, ranging from a completely tutor driven to a completely autonomous exploratory approach.