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, 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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3-D Generic Elastic Models for Fast and Texture Preserving 2-D Novel Pose Synthesis
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An Overview of Recent Advances in Assessing and Mitigating the Face Morphing Attack
Makrushin, A., & Wolf, A. (2018) · European Signal Processing Conference (EUSIPCO) · doi:10.23919/eusipco.2018.8553599 · Cited by 34 · see citing works
Face photo-sketch recognition using local and global texture descriptors
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Self-citationMitigating Dataset Harms Requires Stewardship: Lessons from 1000 Papers
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- Authors
- Gross, R., Matthews, I., Cohn, J., Kanade, T., & Baker, S.
- Affiliations
- Carnegie Mellon University (US)
- University of Pittsburgh (US)
- Microsoft (United States) (US)
- Venue
- 2008 8th IEEE International Conference on Automatic Face & Gesture Recognition
- Publisher
- IEEE
- Published
- 2008-09
- Pages
- 1-8
- ISSN
- 1541-5058 (ISSN-L)
- OpenAlex
- W2296659146
- Cited by
- 373
- References
- 14
- Citations by year
- 2026: 6 · 2025: 11 · 2024: 11 · 2023: 13 · 2022: 20 · 2021: 29 · 2020: 22 · 2019: 26 · 2018: 20 · 2017: 17 · 2016: 31 · 2015: 25 · 2014: 30 · 2013: 27 · 2012: 28
- FWCI
- 14.95
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- International Conference on Automatic Face and Gesture Recognition (publishedVersion)
- Funders
- Yale University
- Sandia National Laboratories
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face recognition and analysis
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Face and Expression Recognition
- Life Sciences › Neuroscience › Cognitive Neuroscience › Face Recognition and Perception
- Keywords
- CMU-PIE, face recognition, face database, pose variation, illumination variation, facial expressions, PCA, LDA
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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