The CAS-PEAL face database has been constructed under the sponsors of National Hi-Tech Program and ISVISION by the Face Recognition Group of JDL, ICT, CAS. The goals to create the PEAL face database include: providing the worldwide researchers of FR community a large-scale Chinese face database for training and evaluating their algorithms; facilitating the development of FR by providing large-scale face images with different sources of variations, especially Pose, Expression, Accessories, and Lighting (PEAL); advancing the state-of-the-art face recognition technologies aiming at practical applications especially for the oriental. Currently, the CAS-PEAL face database contains 99,594 images of 1040 individuals (595 males and 445 females) with varying Pose, Expression, Accessory, and Lighting (PEAL). For each subject, 9 cameras spaced equally in a horizontal semicircular shelf are setup to simultaneously capture images across different poses in one shot. Each subject is also asked to look up and down to capture 18 images in another two shots. We also considered 5 kinds of expressions, 6 kinds accessories (3 glasses, and 3 caps), and 15 lighting directions. This face database is now partly made available (a subset named by CAS-PEAL-R1, contain 30,900 images of 1040 subjects) for research purpose only on a case-by-case basis only. JDL is serving as the technical agent for distribution of the database and reserves the copyright of all the images in the database.

References in zbMATH (referenced in 20 articles )

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  1. He, Ran; Hu, Baogang; Yuan, Xiaotong; Wang, Liang: Robust recognition via information theoretic learning (2014)
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  3. Song, Fengyi; Tan, Xiaoyang; Liu, Xue; Chen, Songcan: Eyes closeness detection from still images with multi-scale histograms of principal oriented gradients (2014) ioport
  4. Wang, Nannan; Tao, Dacheng; Gao, Xinbo; Li, Xuelong; Li, Jie: A comprehensive survey to face hallucination (2014) ioport
  5. Escalante-B., Alberto N.; Wiskott, Laurenz: How to solve classification and regression problems on high-dimensional data with a supervised extension of slow feature analysis (2013)
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  8. Wang, Jing; Su, Guangda; Xiong, Ying; Chen, Jiansheng; Shang, Yan; Liu, Jiongxin; Ren, Xiaolong: Sparse representation for face recognition based on constraint sampling and face alignment (2013)
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  10. Suhr, Jae Kyu; Eum, Sungmin; Jung, Ho Gi; Li, Gen; Kim, Gahyun; Kim, Jaihie: Recognizability assessment of facial images for automated teller machine applications (2012) ioport
  11. Tunç, Birkan; Dağlı, Volkan; Gökmen, Muhittin: Class dependent factor analysis and its application to face recognition (2012)
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  15. Huang, Hua; He, Huiting; Fan, Xin; Zhang, Junping: Super-resolution of human face image using canonical correlation analysis (2010)
  16. Ma, Xiang; Zhang, Junping; Qi, Chun: Hallucinating face by position-patch (2010) ioport
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  19. Xie, Shufu; Shan, Shiguang; Chen, Xilin; Meng, Xin; Gao, Wen: Learned local Gabor patterns for face representation and recognition (2009)
  20. Zhang, Baochang; Wang, Zongli; Zhong, Bineng: Kernel learning of histogram of local Gabor phase patterns for face recognition (2008)