Faces play a central role in human communication. When interacting with someone, we use their face to identify them, to determine their gender, their emotional state and even their health. Automatic facial image interpretation involves developing algorithms, which can estimate such information from digital images and video. Such technology has a wide range of applications, including use in human-computer interfaces, assistive systems for human-human interaction, healthcare, entertainment, smart environments, and security. Considering the shift to the paradigm of human-centered computing for natural interfaces, convenient healthcare applications for daily monitoring, and advanced security needs of the society, the interest in face processing is expected to continue with increasing pace.
There are two main objectives of this proposal. The first one is building a unified framework to derive information from face images and the second one is joint maximization of information extraction performance. In addition, the project will address the task of benchmarking face processing under ambient conditions and involve collection of a multi-sensor face database.
Fields of science
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