ORL face

Our Database of Faces, (formerly ’The ORL Database of Faces’), contains a set of face images taken between April 1992 and April 1994 at the lab. The database was used in the context of a face recognition project carried out in collaboration with the Speech, Vision and Robotics Group of the Cambridge University Engineering Department. There are ten different images of each of 40 distinct subjects. For some subjects, the images were taken at different times, varying the lighting, facial expressions (open / closed eyes, smiling / not smiling) and facial details (glasses / no glasses). All the images were taken against a dark homogeneous background with the subjects in an upright, frontal position (with tolerance for some side movement). A preview image of the Database of Faces is available. The files are in PGM format, and can conveniently be viewed on UNIX (TM) systems using the ’xv’ program. The size of each image is 92x112 pixels, with 256 grey levels per pixel. The images are organised in 40 directories (one for each subject), which have names of the form sX, where X indicates the subject number (between 1 and 40). In each of these directories, there are ten different images of that subject, which have names of the form Y.pgm, where Y is the image number for that subject (between 1 and 10).

References in zbMATH (referenced in 106 articles )

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  1. Kühnel, Line; Sommer, Stefan; Pai, Akshay; Raket, Lars Lau: Most likely separation of intensity and warping effects in image registration (2017)
  2. Cui, Jiantao; Fan, Naimei; Deng, Lujuan: Face recognition based on bag-of-visual word model (2015) ioport
  3. Ghouzali, Sanaa: Watermarking based multi-biometric fusion approach (2015)
  4. Wu, Gang; Feng, Ting-Ting: A theoretical contribution to the fast implementation of null linear discriminant analysis with random matrix multiplication. (2015)
  5. Chen, Yu; Xu, Xiao-Hong: Supervised orthogonal discriminant subspace projects learning for face recognition (2014)
  6. Du, Shiqiang; Shi, Yuqing; Ma, Ming; Wang, Weilan: $L_3/2$ regularized graph non-negative matrix factorization (2014)
  7. Gaidhane, Vilas H.; Hote, Yogesh V.; Singh, Vijander: An efficient approach for face recognition based on common eigenvalues (2014) ioport
  8. Gao, Zhirong; Ding, Lixin; Xiong, Chengyi; Huang, Bo: A robust face recognition method using multiple features fusion and linear regression (2014)
  9. Khaji, Rokan; Li, Hong; Li, Hongfeng; Haruna, Rabiu; Alsaidi, Ramadhan Abdo Musleh: Improved combination of RPCA and MEL for sparse representation-based face recognition (2014)
  10. Ma, Xiaohu; Tan, Yanqi: Face recognition based on discriminant sparsity preserving embedding (2014)
  11. Chen, Yu; Zheng, Wei-Shi; Xu, Xiao-Hong; Lai, Jian-Huang: Discriminant subspace learning constrained by locally statistical uncorrelation for face recognition (2013)
  12. Du, Shiqiang; Shi, Yuqing; Wang, Weilan; Ma, Ming: Manifold regularized-based discriminant concept factorization (2013)
  13. Gao, Jian-Qiang; Fan, Li-Ya; Xu, Li-Zhong: Median null($S_w$)-based method for face feature recognition (2013)
  14. Huang, Yunjuan; Li, Fanzhang: Isospectral manifold learning algorithm (2013)
  15. Wan, Jianwu; Yang, Ming: Pairwise costs in subclass discriminant analysis (2013)
  16. Xu, Yong; Zhu, Qi; Fan, Zizhu; Zhang, David; Mi, Jianxun; Lai, Zhihui: Using the idea of the sparse representation to perform coarse-to-fine face recognition (2013) ioport
  17. Yang, Zhangjing; Liu, Chuancai; Huang, Pu; Qian, Jianjun: Membership-degree preserving discriminant analysis with applications to face recognition (2013)
  18. Zhu, Changshui; Cao, Honggen; Yuan, Baohua; Yuan, Hongxing: Face recognition based on combination of scale-invariant feature transform and local phase quantization (2013)
  19. Chen, Wen-Sheng; Wang, Wei; Yang, Jian-Wei; Tang, Yuan Yan: Supervised regularization locality-preserving projection method for face recognition (2012)
  20. Rani, J.Sheeba; Devaraj, D.: Face recognition using Krawtchouk moment (2012)

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