Gianluca Fadda

TL;DR: This competition is to compare the performance of different state-of-the-art algorithms on the same database using a unique evaluation method and the results suggest the investigation of more complex attacks.

TL;DR: Both video and static analysis are performed in order to employ complementary information about motion, texture and liveness and consequently to obtain a more robust classification of 2-D face spoofing attacks.

TL;DR: Two different state/parameter decoupling procedures are proposed, the single and multi-channel schemes, designed for overcoming the loss of observability due to the large number of states and parameters to be estimated.

TL;DR: The most promising approaches involving the integration of power, control, and communication systems are presented and discussed in this chapter, which presents the related models and technologies able to manage heterogeneous DERs for the purposes of enhancing the integration and coordination of small-scale power generation for self-consumption.

TL;DR: A novel method based on a geometrical model of the head, in which basic features for estimating the pose consist in eyes and nose coordinates only, which shows a competitive performance although its simplicity and its low computational complexity.