Despite the growing body of Human-Robot Interaction (HRI) research focused on domestic
robots, surprisingly little is known about the demographic profile of robot owners and their …

This paper presents foundations, original research and trends in the field of object
categorization by computer vision methods. The research goals in object categorization are …

We propose a framework that learns functional object-categories from spatio-temporal data
sets such as those abstracted from video. The data is represented as one activity graph that …

As AI moves into the second half of its first century, we certainly have much to cheer about.
For AI to become truly robust, we must further our understanding of similarity-driven …

A robot's ability to assist humans in a variety of tasks, eg in search and rescue or in a
household, heavily depends on the robot's reliable recognition of the objects in the …

Humans have abstract models for object classes which helps recognize previously unseen
instances, despite large intra-class variations. Also objects are grouped into classes based …

It is generally agreed that learning, either supervised or unsupervised, can provide the best
possible specification of known classes and offer inference for outlier detection by a …

In ambient intelligence object recognition is an important step towards behaviour analysis
and the understanding interactions between people and the environment. Existing methods …

We present a method for unsupervised learning of event classes from videos in which
multiple activities may occur simultaneously. Unsupervised discovery of event classes …

Spatial scaffolding is a naturally occurring human teaching behavior, in which teachers use
their bodies to spatially structure the learning environment to direct the attention of the …