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Abstrakty
In the last two decades numerous methods of biometric data extraction were invented and new systems of face analysis were proposed. People can easily read the information from the human face and use it during social interaction for identification, emotion interpretation or categorisation of other by demographic features. In the article a system for an automatic description of face images based on individual facial features is presented. Access to such a data may allow fast and automatic person filtration in large scale databases or video material.
Czasopismo
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Tom
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129--136
Opis fizyczny
Bibliogr. 13 poz., rys.
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autor
autor
- Zachodniopomorski Uniwersytet Technologiczny w Szczecinie, Wydział Informatyki
Bibliografia
- [1] P. J. Phillips, H. Moon, S. A. Rizvi, P. J. Rauss. The FERET Evaluation Methodology for Face Recognition Algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence 22(10), 2000, s. 1090-1104
- [2] G. Kukharev, A. Kuźmiński Techniki Biometryczne. Część 1. Metody Rozpoznawania Twarzy. Pracownia Poligraficzna WI PS, 2003, 310 s.
- [3] W. Zhao, R. Chellappa, P. J. Phillips, A. Rosenfeld. Face Recognition: A Literature Survey. ACM Computing Surveys 35(4), 2003, s. 399-458
- [4] S. G. Kong, J. Heo, B. R. Abidi, J. Paik, A. M. Abidi. Recent advances in visual and infrared face recognition - a review. Computer Vision and Image Understanding 97(1), 2005, s. 103-135
- [5] K. W. Bowyer, K. Chang, P. Flynn. A survey of approaches and challenges in 3D and multi-modal 3D + 2D face recognition. Computer Vision and Image Understanding 101(1), 2006, s. 1–15
- [6] T. Fabry, D. Smeets, D. Vandermeulen. Surface representations for 3D face recognition. Face Recognition, InTech, 2010, s. 273-294
- [7] Kong S. G., Heo J., Boughorbel F., Zheng Y., Abidi B. R., Koschan A., Yi M., Abidi M. A., Multiscale Fusion of Visible and Thermal IR Images for Illumination-Invariant Face Recognition, International Journal of Computer Vision 71(2), 2007, s. 215-233
- [8] Sang-W. Lee, J. Park, Seong-W. Lee. Low resolution face recognition based on support vector data description. Pattern Recognition 39(9), 2006, s. 1809-1812
- [9] J. Wang, K.N. Plataniotis, J. Lu, A.N. Venetsanopoulos. On solving the face recognition problem with one training sample per subject. Pattern Recognition 39(9), 2006, s. 1746-1762
- [10] C. Li. An Integrative Approach to Face and Expression Recognition from 3D Scans. Face Recognition, InTech, 2010, s. 295-313
- [11] P. M. Pallett, S. Link, K. Lee. New “golden” ratios for facial beauty. Vision Research, Vol. 50(2), 2010, s. 149-154
- [12] M. Komori, S. Kawamura, S. Ishihara. Averageness or symmetry: Which is more important for facial attractiveness? Acta Psychologica, Vol. 131(2), 2009, s. 136-142
- [13] S. Asteriadis, N. Nikolaidis, I. Pitas. Facial feature detection using distance vector fields. Pattern Recognition 42(7), 2009, s. 1388-1398
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPS3-0022-0068