Ralph Gross, Iain Matthews, Jeffrey Cohn, Takeo Kanade, and Simon Baker
Advancement of face recognition algorithms is tied to the availability of face databases which vary factors influencing 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 a number of shortcomings related to the limited number of subjects, recording sessions and expressions captured. To address these issues we recorded the 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.
|Published in||Image and Vision Computing|
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