TeV's research contributes to the mission of the Digital Industry Center, in that it carries out projects in various digital industry fields, investigating specific areas to achieve scientific results and developing new competencies. Basic research in computer vision helps expand existing knowledge and creates a foundation for solving future problems. Cutting-edge topics of Computer Vision have various names, but the ultimate goal is the description of visual inputs.
In 1966, Prof. Marvin Minsky hired a first-year undergraduate student, Gerald Sussman, and assigned him a problem to solve over the summer: “Connect a camera to a computer and get the machine to describe what it sees.” That summer, for our scientific community, is still going on. Relaxing more and more the assumptions about the knowledge of the world and the constrains on devices, leads us and the whole Computer Vision community in the study of algorithms to solve the task set by Minsky, to describe a (dynamic) scene geometrically starting from images or videos freely acquired by several cameras, possible moving in space, and depicting many objects in motion.
Fortunately, some specific problems attached with Computer Vision do not require the global description of a scene, but their solution benefits from the development and application of specific techniques and technologies.
We are currently actively working on the following research topics.
What about machine learning in our unit? Not a new topic to us. The partial renunciation of complicated elaborations in favour of the constitution of large databases, acquired through experience and associated with appropriate commands, seems to be the best way to simulate and realise what we commonly consider an intelligent activity. (Luigi Stringa, director, 1993)