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ICCV
2009
IEEE

Is that you? Metric Learning Approaches for Face Identification

13 years 1 months ago
Is that you? Metric Learning Approaches for Face Identification
Face identification is the problem of determining whether two face images depict the same person or not. This is difficult due to variations in scale, pose, lighting, background, expression, hairstyle, and glasses. In this paper we present two methods for learning robust distance measures: (a) a logistic discriminant approach which learns the metric from a set of labelled image pairs (LDML) and (b) a nearest neighbour approach which computes the probability for two images to belong to the same class (MkNN). We evaluate our approaches on the Labeled Faces in the Wild data set, a large and very challenging data set of faces from Yahoo! News. The evaluation protocol for this data set defines a restricted setting, where a fixed set of positive and negative image pairs is given, as well as an unrestricted one, where faces are labelled by their identity. We are the first to present results for the unrestricted setting, and show that our methods benefit from this richer traini...
Matthieu Guillaumin, Jakob Verbeek, Cordelia Schmi
Added 13 Jul 2009
Updated 09 Jul 2010
Type Conference
Year 2009
Where ICCV
Authors Matthieu Guillaumin, Jakob Verbeek, Cordelia Schmid
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