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Multi-stream gaussian mixture model based facial feature localization

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5 Author(s)
Kumatani, K. ; Institut fÿr Theoretische Informatik, Universitÿt Karlsruhe (TH), Germany ; Ekenel, H.K. ; Hua Gao ; Stiefelhagen, R.
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This paper presents a new facial feature localization system which estimates positions of eyes, nose and mouth corners simultaneously. In contrast to conventional systems, we use the multi-stream Gaussian mixture model (GMM) framework in order to represent structural and appearance information of facial features. We construct a GMM for the region of each facial feature, where the principal component analysis is used to extract each facial feature. We also build a GMM which represents the structural information of a face, relative positions of facial features. Those models are combined based on the multi-stream framework. It can reduce the computation time to search region of interest (ROI). We demonstrate the effectiveness of our algorithm through experiments on the BioID Face Database.

Published in:

Signal Processing, Communication and Applications Conference, 2008. SIU 2008. IEEE 16th

Date of Conference:

20-22 April 2008