title: Multi-PIE.
abstract: A close relationship exists between the advancement of face recognition algorithms and the availability of face databases varying factors that affect facial appearance in a controlled manner. The CMU PIE database has been very influential in advancing research in face recognition across pose and illumination. Despite its success the PIE database has several shortcomings: a limited number of subjects, single recording session and only few expressions captured. To address these issues we collected the CMU Multi-PIE database. It contains 337 subjects, imaged under 15 view points and 19 illumination conditions in up to four recording sessions. In this paper we introduce the database and describe the recording procedure. We furthermore present results from baseline experiments using PCA and LDA classifiers to highlight similarities and differences between PIE and Multi-PIE.
authors.affiliation: Robotics Institute, Carnegie Mellon University.
authors.forename: Ralph
authors.initials: R
authors.lastname: Gross
authors.forename: Iain
authors.initials: I
authors.lastname: Matthews
authors.forename: Jeff
authors.initials: J
authors.lastname: Cohn
authors.forename: Takeo
authors.initials: T
authors.lastname: Kanade
authors.forename: Simon
authors.initials: S
authors.lastname: Baker