Implicit face prototype learning from geometric information

Implicit face prototype learning from geometric information

There is evidence that humans implicitly learn an average or prototype of previously studied faces, as the unseen face prototype is falsely recognized as having been learned (Solso & McCarthy, 1981). Here we investigated the extent and nature of face prototype formation where observers' memory was tested after they studied synthetic faces defined purely in geometric terms in a multidimensional ...

Implicit learning of geometric eigenfaces

The human visual system can implicitly extract a prototype of encountered visual objects (Posner & Keele, 1968). While learning a prototype provides an efficient way of encoding objects at the category level, discrimination among individual objects requires encoding of variations among them as well. Here we show that in addition to the prototype, human adults also implicitly learn the feature c...

Prototype Based Classification Using Information Theoretic Learning

In this article we extend the (recently published) unsupervised information theoretic vector quantization approach based on the Cauchy–Schwarz-divergence for matching data and prototype densities to supervised learning and classification. In particular, first we generalize the unsupervised method to more general metrics instead of the Euclidean, as it was used in the original algorithm. Thereaf...

Prototype Discriminative Learning for Face Image Set Classification

Learning Hidden Markov Models with Geometric Information

Hidden Markov models (hmms) and partially observable Markov decision processes (pomdps) provide a useful tool for modeling dynamical systems. They are particularly useful for representing environments such as road networks and ooce buildings, which are typical for robot navigation and planning. In a previous paper SK97] we have empirically shown that by taking advantage of readily available odo...