Eye Tracking Applications
Detecting where the user is looking at is extremely useful in several contexts, from interface design to usability studies. We apply eye tracking as an alternative input method in gaze-based (pure or partial) interaction, as a source of information in e-learning systems, and as a help in the evaluation of interfaces and information presentation modes.
Vision-based Perceptive Interfaces
Perceptive interfaces, able to acquire information about users and the environment in which they operate, can be very useful for human-computer interaction. In our research, we focus on exploiting vision to implement interfaces based on gesture recognition, head tracking, and general scene understanding.
Visual Browsing of Large Collections of Images
Within the field of Information Visualization, the subclass of the so-called Information Presentation has received relatively limited attention to date. We are especially interested in browsing large collections of images in effective and fast ways, starting from the assumption that it is often necessary to examine image databases to search for something, but without knowing what exactly.
Exploiting the two- or three-dimensional space, visual languages represent an interesting alternative to textual languages in many situations. Our works are mainly aimed at implementing effective languages for non-expert users, to accomplish tasks such as programming, plan specification, and database querying.
E-learning can provide many benefits. However, to be really useful, an e-learning system must rely on proper user models and interaction paradigms, which are the object of our research.
User-centered Interface Design
In a world where Information Technology is gaining an ever greater share of everyday life, the need for usable user interfaces, effective while simple to use, becomes more and more evident. Our efforts are focused on the development of new interaction paradigms for visual interfaces (with special attention to the Web), as well as on the identification of usability criteria for their design.
The aim of computer vision is to process images acquired with cameras to produce proper representations of objects in the world. Our works are targeted at developing methods for both basic feature extraction and high-level exploitation of vision information.