Multi-PIE |
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Authors: | Ralph Gross Iain Matthews Jeffrey Cohn Takeo Kanade Simon Baker |
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Affiliation: | 1. Robotics Institute, Carnegie Mellon University, Pittsburgh, PA 15213, United States;2. Department of Psychology, University of Pittsburgh, United States;3. Microsoft Research, Microsoft Corporation, One Microsoft way, Redmond, WA 98052, United States |
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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, a 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. |
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Keywords: | Face database Face recognition across pose Face recognition across illumination Face recognition across expression |
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