Recent studies have deciphered the nature of the neural code for facial identification in the primate inferotemporal cortex. The neural code is believed to consist in a linear projection of the facial image onto principal axes of variation, preceded by a disentanglement of the facial coordinates of shape (Cartesian positions of facial elements) and texture (image variation at fixed shape coordinates). We present an estimation of the efficiency, on information-theoretical grounds, of such a probabilistic representation of facial images (known as Active Appearance Model), comparing it with the simpler representation in terms of Eigenfaces. The seminar focus will be on the methods: we will review the relation between information theory and Bayesian statistics, the notion of description length, and the multivariate normal distribution.
Ponente: Miguel Ibáñez Berganza. Università di Roma, «La Sapienza».
Fecha y hora: miércoles, 29 de junio de 2022 a las 12:00.
Lugar: Seminario de Física Computacional, planta baja del edificio de Física (junto a las pantallas). Facultad de Ciencias.
