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Multi-PIE

delete2010-05-01
delete1.5K
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OA
AI
R
Ralph Gross *
I
Iain Matthews
J
Jeffrey F. Cohn
T
Takeo Kanade
S
Simon Baker
DOI:10.1016/j.imavis.2009.08.002delete
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Abstract

Abstract

En 中文
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. (C) 2009 Elsevier B.V. All rights reserved.
Keywords:
Face database
Face recognition across pose
Face recognition across illumination
Face recognition across expression
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Image and Vision Computing cover
Image and Vision Computing
IF:
4.2
Papers:
4.1K
Citations:
6.7K

Organization

C
Carnegie Mellon University
Scholars:
1.4W
Papers: 1.4W
Citations: 2.7W
U
University of Pittsburgh
Scholars:
4.5W
Papers: 3.6W
Citations: 7.1W
P
pennsylvania commonwealth system of higher education (pcshe)
Scholars:
12.9W
Papers: 11.7W
Citations: 177
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