The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Multi-PIE
Open accessAbstract
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, 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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Cites
Turk, M., & Pentland, A. (1991) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.1991.3.1.71 · Cited by 13,733
Cootes, T. F., Edwards, G. J., & Taylor, C. J. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.927467 · Cited by 5,409
Martinez, A. M., & Kak, A. C. (2001) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.908974 · Cited by 3,249
Cited by
AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild
Mollahosseini, A., Hasani, B., & Mahoor, M. H. (2019) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2017.2740923 · Cited by 2,338
Face detection, pose estimation, and landmark localization in the wild
Zhu, X., & Ramanan, D. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6248014 · Cited by 2,120
Openface 2.0: facial behavior analysis toolkit
Baltrusaitis, T., Zadeh, A., Lim, Y. C., & Morency, L.-P. (2018) · 2018 13th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2018) · doi:10.1109/fg.2018.00019 · Cited by 1,861
Bulat, A., & Tzimiropoulos, G. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.116 · Cited by 1,464
Face recognition in unconstrained videos with matched background similarity
Wolf, L., Hassner, T., & Maoz, I. (2011) · CVPR 2011 · doi:10.1109/cvpr.2011.5995566 · Cited by 1,382
Metadata
- Authors
- Gross, R., Matthews, I., Cohn, J., Kanade, T., & Baker, S.
- Venue
- Image and Vision Computing
- Publisher
- Elsevier BV
- Published
- 2010-05
- Volume
- 28
- Issue
- 5
- Pages
- 807-813
- ISSN
- 0262-8856 (ISSN-L)
- OpenAlex
- W2912990735
- Cited by
- 1,621
- References
- 3
- FWCI
- 36.65
- Type
- journal article
- Language
- en
- Open access
- green
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