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 234 articles )

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  1. Tan, Xiaoyang; Chen, Songcan; Zhou, Zhi-Hua; Zhang, Fuyan: Face recognition from a single image per person: a survey (2006)
  2. Vogel, Julia; Schiele, Bernt: Performance evaluation and optimization for content-based image retrieval (2006)
  3. Wang, Jie; Plataniotis, K. N.; Lu, Juwei; Venetsanopoulos, A. N.: On solving the face recognition problem with one training sample per subject (2006)
  4. Wang, Liwei; Wang, Xiao; Feng, Jufu: Subspace distance analysis with application to adaptive Bayesian algorithm for face recognition (2006)
  5. Wang, Xiaogang; Tang, Xiaoou: Random sampling for subspace face recognition (2006) ioport
  6. Zhao, Haitao; Sun, Shaoyuan; Jing, Zhongliang; Yang, Jingyu: Local structure based supervised feature extraction (2006)
  7. Beveridge, J. Ross; Bolme, David; Draper, Bruce A.; Teixeira, Marcio: The CSU face identification evaluation system (2005) ioport
  8. Cesar, Roberto M.; Jr.; Bengoetxea, Endika; Bloch, Isabelle; Larrañaga, Pedro: Inexact graph matching for model-based recognition: evaluation and comparison of optimization algorithms (2005) ioport
  9. Cheng, Jian; Wang, Kongqiao; Chen, Yenwei: A cascaded ensemble learning for independent component analysis (2005)
  10. Lee, Jianguo; Wang, Jingdong; Zhang, Changshui; Bian, Zhaoqi: Visual object recognition using probabilistic kernel subspace similarity (2005) ioport
  11. Liang, Yixiong; Gong, Weiguo; Pan, Yingjun; Li, Weihong: Generalizing relevance weighted LDA (2005)
  12. Liu, Dang-Hui; Lam, Kin-Man; Shen, Lan-Sun: Illumination invariant face recognition (2005) ioport
  13. Rao, K. Srinivasa; Rajagopalan, A. N.: A probabilistic fusion methodology for face recognition (2005)
  14. Rukhin, Andrew L.; Osmoukhina, Anna: Nonparametric measures of dependence for biometric data studies (2005)
  15. Su, Congyong; Zhuang, Yueting; Huang, Li; Wu, Fei: Steerable pyramid-based face hallucination (2005) ioport
  16. Tu, Zhuowen; Chen, Xiangrong; Yuille, Alan L.; Zhu, Song-Chun: Image parsing: unifying segmentation, detection, and recognition (2005) ioport
  17. Yang, Jian; Gao, Xiumei; Zhang, David; Yang, Jing-yu: Kernel ICA: An alternative formulation and its application to face recognition (2005)
  18. Zhang, Daoqiang; Chen, Songcan; Zhou, Zhi-Hua: A new face recognition method based on SVD perturbation for single example image per person (2005)
  19. Ahonen, Timo; Hadid, Abdenour; Pietikäinen, Matti: Face recognition with local binary patterns (2004)
  20. Chen, Songcan; Liu, Jun; Zhou, Zhi-Hua: Making FLDA applicable to face recognition with one sample per person (2004) ioport

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