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Cited by 778

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MORPH: A Longitudinal Image Database of Normal Adult Age-Progression

Ricanek, K., Tesafaye, T.·2006·7th International Conference on Automatic Face and Gesture Recognition (FGR06)
DOI 10.1109/fgr.2006.78
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Abstract

This paper details MORPH a longitudinal face database developed for researchers investigating all facets of adult age-progression, e.g. face modeling, photo-realistic animation, face recognition, etc. This database contributes to several active research areas, most notably face recognition, by providing: the largest set of publicly available longitudinal images; longitudinal spans from a few months to over twenty years; and, the inclusion of key physical parameters that affect aging appearance. The direct contribution of this data corpus for face recognition is highlighted in the evaluation of a standard face recognition algorithm, which illustrates the impact that age-progression, has on recognition rates. Assessment of the efficacy of this algorithm is evaluated against the variables of gender and racial origin. This work further concludes that the problem of age-progression on face recognition (FR) is not unique to the algorithm used in this work.

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  • Identification accuracy of face recognition can be quite poor when image capture conditions are not optimal and when images of a face are captured several years apart.

    “Identification accuracy can be quite poor in cases where image capture conditions are not optimal [7] and where images of a face are captured several years apart [8].”

    From Error Rates in Users of Automatic Face Recognition Software (2015) · cites this paper as [8]

Citations

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No references could be resolved yet.

Research works printed but not linked: 13

  1. 2002, FG-Net Aging Database
  2. 10.1109/34.993553 · DOI
  3. ricanek, 2004, Age-related morphological changes: Effects on facial recognition technologies, UNC Technical Report
  4. 10.1016/S0379-0738(00)00433-3 · DOI
  5. 10.1109/AFGR.2000.840647 · DOI
  6. farkas, 1994, Photogrammetry of the face, Anthropometry Ofthe Head and Face 2nd Edition, 79
  7. jain, 2004, Soft biometric traits for personal recognition systems, LNCS, 3072, 731
  8. 10.1109/AFGR.2002.1004130 · DOI
  9. 10.1109/CVPR.1997.609311 · DOI
  10. phillips, 2003, FRVT2002 Evaluation Report
  11. 10.1109/CVPR.2005.268 · DOI
  12. cootes, 2001, Statistical models of appearance for medical image analysis and computer vision, Proceedings of SPIE Medical Imaging, 10.1117/12.431093 · DOI
  13. zimbler, 2002, Anatomy and pathophysiology of facial aging, Facial Plastic Surgery Clinics of North Anerica, 9, 179

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Metadata

Authors
Ricanek, K., & Tesafaye, T.
Venue
7th International Conference on Automatic Face and Gesture Recognition (FGR06)
Publisher
IEEE
Published
2006
Pages
341-345
DOI
10.1109/fgr.2006.78
Cited by
778
References
0

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