Eigenfeature Regularization and Extraction in Face Recognition
By Xudong Jiang, Bappaditya Mandal, Alex ChiChung Kot. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2008
328 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Signal Processing
View Paper: https://www.semanticscholar.org/paper/1819d9a9099dafc987dd236c2174945e7922be13
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Mohammed Bennamoun
- Imran Naseem
- Roberto B. Togneri
- Weishi Zheng
- Yulan Guo
- Ran He
- Senjian An
- Munawar Hayat
In Signal Processing
- Mohammed Bennamoun
- Imran Naseem
- Roberto B. Togneri
- Ran He
- Weishi Zheng
- Arnout Devos
- Matthias Grossglauser
Citations in the corpus
- Linear discriminant analysis for the small sample size problem: an overview (2014, unknown): “…et al., 1997), regularized LDA (RLDA) (Friedman, 1989; Lu et al., 2003b, 2005; Zhao et al., 1998, 1999, 2003), eigenfeature regularization (EFR) (Jiang et al., 2008), extrapolation of scatter matrices (ELDA) (Sharma and Paliwal, 2010), maximum uncertainty LDA (MLDA) (Thomaz et al., 2005),…”
- Linear Regression for Face Recognition (2010, methodology): “We follow two evaluation protocols as proposed in the literature quite often [24], [25], [26], [27].”