FERET

The FERET database and evaluation procedure for face-recognition algorithms. The Face Recognition Technology (FERET) program database is a large database of facial images, divided into development and sequestered portions. The development portion is made available to researchers, and the sequestered portion is reserved for testing facerecognition algorithms. The FERET evaluation procedure is an independently administered test of face-recognition algorithms. The test was designed to: (1) allow a direct comparison between different algorithms, (2) identify the most promising approaches, (3) assess the state of the art in face recognition, (4) identify future directions of research, and (5) advance the state of the art in face recognition.


References in zbMATH (referenced in 198 articles )

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  1. Harandi, Mehrtash; Basirat, Mina; Lovell, Brian C.: Coordinate coding on the Riemannian manifold of symmetric positive-definite matrices for image classification (2016)
  2. Li, Zhi-Ming; Huang, Zheng-Hai; Zhang, Ting: Gabor-scale binary pattern for face recognition (2016)
  3. Chen, Wen-Sheng; Dai, Xiuli; Pan, Binbin; Tang, Yuan Yan: Semi-supervised discriminant analysis method for face recognition (2015)
  4. Kamaruzaman, Fadhlan; Shafie, Amir Akramin; Mustafah, Yasir M.: Coincidence detection using spiking neurons with application to face recognition (2015)
  5. Cament, Leonardo A.; Castillo, Luis E.; Perez, Juan P.; Galdames, Francisco J.; Perez, Claudio A.: Fusion of local normalization and Gabor entropy weighted features for face identification (2014)
  6. Cheng, Miao; Pun, Chi-Man; Tang, Yuan Yan: Nonnegative class-specific entropy component analysis with adaptive step search criterion (2014)
  7. Chen, Yu; Xu, Xiao-Hong: Supervised orthogonal discriminant subspace projects learning for face recognition (2014)
  8. Gaidhane, Vilas H.; Hote, Yogesh V.; Singh, Vijander: An efficient approach for face recognition based on common eigenvalues (2014)
  9. Kang, Jeonil; Nyang, DaeHun; Lee, KyungHee: Two-factor face authentication using matrix permutation transformation and a user password (2014)
  10. Karczmarek, Paweł; Pedrycz, Witold; Reformat, Marek; Akhoundi, Elaheh: A study in facial regions saliency: a fuzzy measure approach (2014)
  11. Li, Yongchao; Cai, Cheng; Qiu, Guoping; Lam, Kin-Man: Face hallucination based on sparse local-pixel structure (2014)
  12. Li, Yuelong; Feng, Jufu; Meng, Li; Wu, Jigang: Sparse representation shape models (2014)
  13. Ma, Andy J.; Yuen, Pong C.: Reduced analytic dependency modeling: robust fusion for visual recognition (2014)
  14. Mehta, Rakesh; Yuan, Jirui; Egiazarian, Karen: Face recognition using scale-adaptive directional and textural features (2014)
  15. Mohamad AL-Shiha, Abeer A.; Woo, W.L.; Dlay, S.S.: Multi-linear neighborhood preserving projection for face recognition (2014)
  16. Tang, Y.Y.; Xia, Tian; Wei, Yantao; Li, Hong; Li, Luoqing: Hierarchical kernel-based rotation and scale invariant similarity (2014)
  17. Uddin, Md.Zia: An efficient local feature-based facial expression recognition system (2014)
  18. Wang, Nannan; Tao, Dacheng; Gao, Xinbo; Li, Xuelong; Li, Jie: A comprehensive survey to face hallucination (2014)
  19. Zhao, Haitao; Wong, W.K.: Regularized discriminant entropy analysis (2014)
  20. Chen, Wen-Sheng; Zhang, Chu; Chen, Shengyong: Geometric distribution weight information modeled using radial basis function with fractional order for linear discriminant analysis method (2013)

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