ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
LIBSVM: A library for support vector machines
ACM Transactions on Intelligent Systems and Technology (TIST)
AVEC 2011-the first international audio/visual emotion challenge
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part II
IEEE Transactions on Affective Computing
Face detection, pose estimation, and landmark localization in the wild
CVPR '12 Proceedings of the 2012 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
AVEC 2012: the continuous audio/visual emotion challenge
Proceedings of the 14th ACM international conference on Multimodal interaction
Selective Transfer Machine for Personalized Facial Action Unit Detection
CVPR '13 Proceedings of the 2013 IEEE Conference on Computer Vision and Pattern Recognition
Emotion recognition in the wild challenge 2013
Proceedings of the 15th ACM on International conference on multimodal interaction
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Automatic facial expression analysis promises to be a game-changer in many application areas. But before this promise can be fulfilled, it has to move from the laboratory into the wild. The Emotion Recognition in the Wild challenge provides an opportunity to develop approaches in this direction. We propose a novel Distribution-based Pairwise Iterative Classification scheme, which outperforms standard multi-class classification on this challenge data. We also verify that the recently proposed dynamic appearance descriptor, Local Gabor Patterns on Three Orthogonal Planes, performs well on this real-world data, indicating that it is robust to the type of facial misalignments that can be expected in such scenarios. Finally, we provide details of ACTC, our affective computing tools on the cloud, which is a new resource for researchers in the field of affective computing.