Facial Memory Is Kernel Density Estimation (Almost)

We compare the ability of three exemplar-based memory models, each using three different face stimulus representations, to account for the probability a human subject responded "old" in an old/new facial memory experiment. The models are 1) the Generalized Context Model, 2) SimSample, a probabilistic sampling model, and 3) DBM, a novel model related to kernel density estimation that explicitly encodes stimulus distinctiveness. The representations are 1) positions of stimuli in MDS "face space," 2) projections of test faces onto the eigenfaces of the study set, and 3) a representation based on response to a grid of Gabor filter jets. Of the 9 model/representation combinations, only the distinctiveness model in MDS space predicts the observed "morph familiarity inversion" effect, in which the subjects' false alarm rate for morphs between similar faces is higher than their hit rate for many of the studied faces. This evidence is consistent with the hypo...

• Type: Conference
• Year: 1998
• Where: NIPS
• Authors: Matthew N. Dailey, Garrison W. Cottrell, Thomas A. Busey
• Keywords: Face Stimulus Representations, Faces Affect Subjects, Kernel Density Estimation, NIPS 1998, NIPS 2007