Hand detection and gesture recognition are two of the most studied topics in human–computer interaction (HCI). The increasing availability of sensors able to provide real‐time depth measurements, such as time‐of‐flight cameras or the more recent Kinect, has helped researchers to find more and more efficient solutions for these issues. With the main aim to implement effective gesture‐based interaction systems, this study presents an approach to hand detection and tracking that exploits two different video streams: the depth one and the colour one. Both hand and gesture recognition are based only on geometrical and colour constraints, and no learning phase is needed. The use of a Kalman filter to track hands guarantees system robustness also in presence of many persons in the scene. The entire procedure is designed to maintain a low computational cost and is optimised to efficiently execute HCI tasks. As use cases two common applications are described: a virtual keyboard and a three‐dimensional object manipulation virtual environment. These applications have been tested with a representative sample of non‐trained users to assess the usability and flexibility of the system.

Teaching computer graphics in an effective way is a challenging task. Different approaches are proposed in the literature, some focusing on traditional teacher-led lectures, others on interactive teaching methods. This paper describes an experiential learning approach applied in a university-level course in computer engineering. Students were involved in the realization of a digital humanities project, the 3-D modeling of the city of Pavia, Italy, as it was in the 16th century. Traditional lectures introduced key theoretical elements, but students were subsequently given specific assignments and retrieved additional content when completing the tasks assigned to them under the overall guidance of their supervisors.