Affordances, as for example grasping possibilities, are known to play a role in the guidance of human attention but have not been considered in artificial attention systems so far. Extending our earlier work, we investigate the combination of affordance estimation and visual saliency in an artificial visual attention model. Different models based on saliency, affordance estimation, or their com...

Affordances (unit utility, functional and topological relationships) and semantic scene understanding are key to building a generic, scalable and cognitive architecture for visual perception. ‘Affordance based object recognition’ or recognition based on affordance features is an important step in this regard. In this paper, we extend the scope of affordance features to define ‘Conceptual Equiva...

The growing interest of IS researchers in using the theory of Affordances for studying the uses and consequences of the IT artefact calls for an integrative view on the subject. The originating literature is dispersed and the definition of the concept of affordance varies in these studies. With this paper we offer a framework for organizing the existing interdisciplinary literature modeling aff...

Complex cognitive processes corresponding to human control behaviors cannot be easily inferred using (1) a logical rule-based model, (2) a statistical model, or (3) an analytical predictive model. Predicting human behaviors in complex and uncertain environments like emergency evacuation is considered almost impossible (at least NP hard) in systems theory. In this paper, we explore simulating hu...

We present a novel method for learning and predicting the affordances of an object based on its physical and visual attributes. Affordance prediction is a key task in autonomous robot learning, as it allows a robot to reason about the actions it can perform in order to accomplish its goals. Previous approaches to affordance prediction have either learned direct mappings from visual features to ...

Affordance learning has, in recent years, been generating heightened interest in both the cognitive vision and developmental robotics communities. In this paper we describe the development of a system that uses a robotic arm to interact with household objects on a table surface while observing the interactions using camera systems. Various computer vision methods are used to derive, firstly, ob...

Imitation is not only a powerful means to drastically downsize the exploration space when learning behavior. It also helps to align the learning efforts of a robot group towards a common goal. However, one prerequisite in imitation, the decision of which robot to imitate, is often factored out in current research. In our work we address this question by providing a means to measure the similari...