Aleix M. Mart́ınez

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Researchers in computer vision, machine learning and cognitive science have long sought a way to describe faces of different people as disjoint subsets in a feature space of some sort. In recent years, the modelling of such subsets has played an increasingly important role within our community. In this chapter, we address the three important challenges(More)
The classical way of attempting to solve the face (or object) recognition problem is by using large and representative datasets. In many applications though, only one sample per class is available to the system. In this contribution, we describe a probabilistic approach that is able to compensate for imprecisely localized, partially oc-cluded and expression(More)
Several models have been proposed that attempt to explain how the brain identifies people by looking at their faces. However, to date, it is still not clear by which mechanism the brain successfully accomplishes the matching of two or more face images when differences in facial expression make the (local and global) appearance of these images different from(More)
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