CMU PIE

The CMU Pose, Illumination, and Expression (PIE) database. Between October 2000 and December 2000, we collected a database of over 40,000 facial images of 68 people. Using the CMU (Carnegie Mellon University) 3D Room, we imaged each person across 13 different poses, under 43 different illumination conditions, and with four different expressions. We call this database the CMU Pose, Illumination and Expression (PIE) database. In this paper, we describe the imaging hardware, the collection procedure, the organization of the database, several potential uses of the database, and how to obtain the database.


References in zbMATH (referenced in 156 articles )

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  1. Diaz-Chito, Katerine; Martínez del Rincón, Jesús; Rusiñol, Marçal; Hernández-Sabaté, Aura: Feature extraction by using dual-generalized discriminative common vectors (2019)
  2. Mi, Jian-Xun; Zhang, Ya-Nan; Lai, Zhihui; Li, Weisheng; Zhou, Lifang; Zhong, Fujin: Principal component analysis based on nuclear norm minimization (2019)
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  5. Choi, Jae Young: Color compensation via color-flow representation and eigenspace manifold learning for robust color-invariant face recognition (2018)
  6. Liu, Xiao-Zhang; Li, Yu-Wei: Face pose estimation based on kernelized maximum separability (2018)
  7. Min, Xiaoping; Chen, Youbing; Ge, Shengxiang: Nonnegative matrix factorization with Hessian regularizer (2018)
  8. Shang, Kun; Huang, Zheng-Hai; Liu, Wanquan; Li, Zhi-Ming: A single gallery-based face recognition using extended joint sparse representation (2018)
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  10. Li, Huaxiong; Zhang, Libo; Zhou, Xianzhong; Huang, Bing: Cost-sensitive sequential three-way decision modeling using a deep neural network (2017)
  11. Zhang, Zhao; Zhang, Yan; Li, Fanzhang; Zhao, Mingbo; Zhang, Li; Yan, Shuicheng: Discriminative sparse flexible manifold embedding with novel graph for robust visual representation and label propagation (2017)
  12. Hou, Xuan; Yao, Guangjun; Wang, Jun: Semi-supervised classification based on low rank representation (2016)
  13. Lu, Yuwu; Lai, Zhihui; Xu, Yong; You, Jane; Li, Xuelong; Yuan, Chun: Projective robust nonnegative factorization (2016)
  14. Niu, Guo; Ma, Zhengming; Liu, Shuyu: A multikernel-like learning algorithm based on data probability distribution (2016)
  15. Ren, Yingchun; Wang, Zhicheng; Chen, Yufei; Zhao, Weidong: Sparsity preserving discriminant projections with applications to face recognition (2016)
  16. Ye, Lei; Wang, Can; Xu, Xin; Qian, Hui: Customized dictionary learning for subdatasets with fine granularity (2016)
  17. Feng, Lei; Yu, Guoxian: Semi-supervised classification based on mixture graph (2015)
  18. Huang, Sheng; Yang, Dan; Yongxin, Ge; Zhang, Xiaohong: Combined supervised information with PCA via discriminative component selection (2015)
  19. Kuang, Da; Yun, Sangwoon; Park, Haesun: SymNMF: nonnegative low-rank approximation of a similarity matrix for graph clustering (2015)
  20. Piao, Yongjun; Piao, Minghao; Jin, Cheng Hao; Shon, Ho Sun; Chung, Ji-Moon; Hwang, Buhyun; Ryu, Keun Ho: A new ensemble method with feature space partitioning for high-dimensional data classification (2015)

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