1 November 1990 Self-organizing system for analysis and identification of human faces
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Abstract
A system is proposed for a fully automatized analysis and identification of a human face appearing in a picture. The system learns a face by analyzing it and storing the extracted features in a database. This analysis starts from a very robust detection of a face and its position scale and orientation based on the position of the eyes. The. four transformation parameters define the face-specific coordinates which are used during the entire analysis. In these coordinates some face features are detected and stored which belong roughly to three categories: geometrical proportions surface properties and iconic features. The identification of a person using a different picture of a known person also starts from a face analysis. Using the features the presented face is correlated with all faces present in the database. The correlation of the extracted features contains two steps: individual measures (correlating iconic features computing differences in geometrical proportions or surface properties) give the similarity between two faces for one feature while a global measure (a Euclidean norm for instance) combines these similarity values. The system is therefore able to identify a known person by finding the best match. The results of the system on real images are presented. It is shown that the identification is quite selective.
© (1990) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Herwig Mannaert, Andre J. Oosterlinck, "Self-organizing system for analysis and identification of human faces", Proc. SPIE 1349, Applications of Digital Image Processing XIII, (1 November 1990); doi: 10.1117/12.23533; https://doi.org/10.1117/12.23533
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