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2008 | Vol. 13, no 3-4 | 59-64
Tytuł artykułu

The put face database

Wybrane pełne teksty z tego czasopisma
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In this paper we present a new database of color, high resolution face images. The database contains almost 10000 images of 100 people acquired in partially controlled conditions and stored in 2048 x 1536 pixels images. The base is publicly available for research purposes and can be used as a training and testing material in developing various algorithms related to the face detection, recognition and analysis.
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Wydawca

Rocznik
Strony
59-64
Opis fizyczny
Bibliogr. 16 poz., rys.
Twórcy
autor
autor
  • Poznan University of Technology, Poznan, Poland
Bibliografia
  • [1] Open computer vision library. http://www.intel.com/technology/computing/ /opencv/.
  • [2] P. J. Phillips, H. Wechsler, P. Rauss, The Feret database and evaluation procedure for face-recognition algorithms, Image and Vision Computing, 16(5), pp. 295-306, 1998.
  • [3] A. R. Martinez, R. Benavente, The AR face database, Technical report 24, ComputerVision Center(CVC) Barcelona, 1998.
  • [4] V. Blanz, T. Vetter, A morphable model for the synthesis of 3d faces, In Computer Graphics Proceedings, Annual Conference Series (SIGGRAPH), 1999.
  • [5] P. J. Phillips, H. Moon, S. Rizvi, P. J. Rauss, The Feret evaluation methodology for face-recognition algorithms, IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(10), pp. 1090-1104, 2000.
  • [6] A. Georghiades, D. Kriegman, P. Belhumeur, From few to many: generative models for recognition under variable pose and illumination, IEEE Transactions on Pattern Analysis and Machine Intelligence, 23(6), pp. 643-660, 2001.
  • [7] Socolinsky, D., Wolff, L., Neuheisel, J., Eveland, C., Illumination invariant face recognition using thermal infrared imagery, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2001.
  • [8] L. Denes, P. Metes, Y. Liu, Hyperspectral face database, Technical report, Robotics Institute, Carnegie Mellon University, 2002.
  • [9] P. Flynn, K. Bowyer, P.J. Phillips, Assesment of time dependency in face recognition: an initial study, In Audio- and Video-Based Biometric Person Authentication (AVBPA), pp. 44-51, 2003.
  • [10] E. Bailly-Bailliere, S. Bengio, F. Bimbot, M. Hamouz, J. Kittler, J. Mariethoz, J. Matas, K. Messer, V. Popovici, F. Poree, B. Ruiz, J.-P. Thiran, The Banca database and evaluation protocol, In Audio- and Video-Based Biometric Person Authentication (AVBPA), pp. 625638, 2003.
  • [11] B.-W. Hwang, M.-C. R. H. Byun, S.-W. Lee, Performance evaluation of face recognition algorithms on the Asian face database, KFDB, In Audio- and Video-Based Biometric Person Authentication (AVBPA), pp. 557565, 2003.
  • [12] T. Sim, S. Baker, M. Bsat, The CMu Pose, Illumination, and Expression database, IEEE Transactions on Pattern Analysis and Machine Intelligence, 25(12), pp. 16151618, 2003.
  • [13] Y. Zhou, L. Gu, H. Zhang, Bayesian tangent shape model: Estimating shape and pose parameters via bayesian inference, In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2003.
  • [14] T. Cootes, C.J. Taylor, Statistical models of appearance for computer vision, Technical report, Imaging Science and Biomedical Engineering, University of Manchester, 2004.
  • [15] W. Gao, B. Cao, S. Shan, D. Zhou, X. Zhang, D. Zhao, Cas-peal large-scale chinese face database and evaluation protocols, Technical report jdl-tr-04-fr-001, Technical report, Joint Research and DevelopmentLaboratory, 2004.
  • [16] R. Gross, Handbook of face recognition, chapter Face Databases, Springer-Verlag, 2005.
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT5-0037-0007
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