Datensatz

Zusammenfassung

Compared to other species, humans have developed highly sophisticated communication systems for social interaction. One of the most important communication systems is based on
facial expressions, which are both used for expressing emotions and conveying intentions. Starting already at birth, humans are trained to process faces and facial expressions, resulting in a high degree of perceptual expertise for face perception and social communication.
To date, research has mostly focused on the emotional aspect of facial expression processing, using only a very limited set of „generic“ or „universal“ expressions, such as happiness or sadness. The important communicative aspect of facial expressions, however, has so far been largely neglected. Furthermore, the processing of facial expressions is influenced by dynamic information (e. g. Fox et al., 2009). However, almost all studies so far have used static expressions and thus were studying facial expressions in an ecologically less valid context (O’Toole
et al., 2004). In order to enable a deeper understanding of facial expression processing it therefore seems crucial to investigate the emotional and communicative aspects of facial expressions in a dynamic context. For these investigations it is essential to first construct a database that contains such material using a well-controlled setup. In this talk, we will present the novel MPI facial expression database, which to our knowledge is the most extensive database of this kind up to date. Furthermore, we will briefly present psychophysical experiments with which we investigated the validity of our database, as well as the recognizability of a large set of facial expressions.