DocumentCode :
2421936
Title :
Differentiating Duchenne from non-Duchenne smiles using active appearance models
Author :
Vandeventer, Jason ; Patterson, Eric
Author_Institution :
Univ. of North Carolina Wilmington, Wilmington, NC, USA
fYear :
2012
fDate :
23-27 Sept. 2012
Firstpage :
319
Lastpage :
324
Abstract :
Face-related biometrics research in recent years has moved from attempting merely to recognize faces, and even doing so under varying conditions, to considering a wide variety of aspects such as dynamics, gesture, aging, and expression. The state of an individual´s face is a revealing indicator that may be used for soft biometrics, active authentication, deception detection, response feedback, and other areas of interface. One related psychological indicator is the Duchenne smile that usually indicates a genuine, spontaneous, or enjoyed emotional state rather than a forced or posed state, as likely expressed by a non-Duchenne smile. Differentiating between these is a useful task to automate for a variety of reasons. This paper discusses a classification technique that achieves higher recognition rates than previously published for similar comparisons.
Keywords :
biometrics (access control); face recognition; active appearance models; active authentication; deception detection; face-related biometrics; nonDuchenne smile; psychological indicator; response feedback; soft biometrics; Active appearance model; Databases; Feature extraction; Gold; Support vector machines; Tracking; Training;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Biometrics: Theory, Applications and Systems (BTAS), 2012 IEEE Fifth International Conference on
Conference_Location :
Arlington, VA
Print_ISBN :
978-1-4673-1384-1
Electronic_ISBN :
978-1-4673-1383-4
Type :
conf
DOI :
10.1109/BTAS.2012.6374595
Filename :
6374595
Link To Document :
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