Abstract
Caricature is affected strongly by the attribute relationship between input face and mean face. This paper proposes a method of facial attribute classification by means of the statistics of many mean faces and an input face. These processes are made up by the estimation function of the input face and the attribute matrix which is defined by the distances of all feature points of the face and its variances. There should be many attribute matrices characterized by the different age and different gender sets of faces. This proposal delivered the expected results enough for the automation of the mean face selection and clarification as the new caricature generation principle.
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© 2003 Springer-Verlag Berlin Heidelberg
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Fujiwara, T., Koshimizu, H. (2003). Age and Gender Estimations by Modeling Statistical Relationship among Faces. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2774. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45226-3_119
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DOI: https://doi.org/10.1007/978-3-540-45226-3_119
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-40804-8
Online ISBN: 978-3-540-45226-3
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