A COMPARATIVE STUDY OF HMMS AND DBNS APPLIED TO FACIAL ACTION UNITS RECOGNITION by ProQuest

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									        A COMPARATIVE STUDY OF HMMS
   AND DBNS APPLIED TO FACIAL ACTION
                     UNITS RECOGNITION
 M. C. Popa∗ L. J. M. Rothkrantz∗† D. Datcu∗†, P. Wiggers∗, R. Braspenning‡
           ,                     ,                                        ,
                                   C. Shan‡



Abstract: From a theoretical point of view, Hidden Markov Models (HMMs) and
Dynamic Bayesian Networks (DBNs) are similar, still in practice they pose dif-
ferent challenges and perform in a different manner. In this study we present a
comparative analysis of the two spatial-temporal classification methods: HMMs
and DBNs applied to the Facial Action Units (AUs) recognition problem. The Fa-
cial Action Coding Syste
								
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