@conference {73,
	title = {The computer expression recognition toolbox (CERT)},
	booktitle = {2011 IEEE International Conference on Automatic Face Gesture Recognition and Workshops (FG 2011)},
	year = {2011},
	month = {03/2011},
	publisher = {IEEE},
	organization = {IEEE},
	address = {Santa Barbara, CA},
	abstract = {<p class="p1">We present the Computer Expression Recognition Toolbox (CERT), a software tool for fully automatic real-time facial expression recognition, and officially release it for free academic use. CERT can automatically code the intensity of 19 different facial actions from the Facial Action Unit Coding System (FACS) and 6 different prototypical facial expressions. It also estimates the locations of 10 facial features as well as the 3-D orientation (yaw, pitch, roll) of the head. On a database of posed facial expressions, Extended Cohn-Kanade (CK+[1]), CERT achieves an average recognition performance (probability of correctness on a two-alternative forced choice (2AFC) task between one positive and one negative example) of 90.1\% when analyzing facial actions. On a spontaneous facial expression dataset, CERT achieves an accuracy of nearly 80\%. In a standard dual core laptop, CERT can process 320 {\texttimes} 240 video images in real time at approximately 10 frames per second.</p>
},
	keywords = {3D orientation, Accuracy, automatic real-time facial expression recognition, CERT, computer expression recognition toolbox, Detectors, dual core laptop, Emotion recognition, Encoding, extended Cohn-Kanade, Face, face recognition, facial action unit coding system, facial expression dataset, Facial features, FACS, Gold, Image coding, software tool, software tools, two-alternative forced choice task},
	isbn = {978-1-4244-9140-7},
	author = {Littlewort, G. and Whitehill, J. and Wu, T. and Fasel, I. and Frank, M. and Movellan, J. and Bartlett, M.}
}