Title :
Person-independent facial expression detection using Constrained Local Models
Author :
Chew, Sien W. ; Lucey, Patrick ; Lucey, Simon ; Saragih, Jason ; Cohn, Jeffrey F. ; Sridharan, Sridha
Author_Institution :
Speech, Audio, Image & Video Technol. Lab., Queensland Univ. of Technol., Brisbane, QLD, Australia
Abstract :
In automatic facial expression detection, very accurate registration is desired which can be achieved via a deformable model approach where a dense mesh of 60-70 points on the face is used, such as an active appearance model (AAM). However, for applications where manually labeling frames is prohibitive, AAMs do not work well as they do not generalize well to unseen subjects. As such, a more coarse approach is taken for person-independent facial expression detection, where just a couple of key features (such as face and eyes) are tracked using a Viola-Jones type approach. The tracked image is normally post-processed to encode for shift and illumination invariance using a linear bank of filters. Recently, it was shown that this preprocessing step is of no benefit when close to ideal registration has been obtained. In this paper, we present a system based on the Constrained Local Model (CLM) method which is a generic or person-independent face alignment algorithm which gains high accuracy. We show these results against the LBP feature extraction on the CK+ and GEMEP-FERA datasets.
Keywords :
channel bank filters; emotion recognition; face recognition; feature extraction; image coding; image registration; GEMEP-FERA datasets; LBP feature extraction; Viola-Jones type approach; active appearance model; automatic facial expression detection; coarse approach; constrained local model; constrained local model method; deformable model approach; illumination invariance; image coding; image tracking; linear bank of filters; person-independent face alignment algorithm; person-independent facial expression detection; Face; Feature extraction; Gold; Pixel; Shape; Support vector machines; Training;
Conference_Titel :
Automatic Face & Gesture Recognition and Workshops (FG 2011), 2011 IEEE International Conference on
Conference_Location :
Santa Barbara, CA
Print_ISBN :
978-1-4244-9140-7
DOI :
10.1109/FG.2011.5771373