Multi-PIE

Author

Gross, Ralph ; Matthews, Iain ; Cohn, Jeffrey ; Kanade, Takeo ; Baker, Simon

Author_Institution

Robot. Inst., Carnegie Mellon Univ., Pittsburgh, PA

fYear

2008

fDate

17-19 Sept. 2008

Firstpage

1

Lastpage

8

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.

Keywords

face recognition; lighting; pose estimation; visual databases; face recognition algorithm; illumination recognition; multi PIE face database; pose recognition; Face recognition; Image databases; Lighting; Linear discriminant analysis; Principal component analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Automatic Face & Gesture Recognition, 2008. FG '08. 8th IEEE International Conference on

Conference_Location

Amsterdam

Print_ISBN

978-1-4244-2153-4

Electronic_ISBN

978-1-4244-2154-1

Type

conf

DOI

10.1109/AFGR.2008.4813399

Filename

4813399