Context-Sensitive Conditional Ordinal Random Fields for Facial Action Intensity Estimation
暂无分享,去创建一个
[1] P. McCullagh. Regression Models for Ordinal Data , 1980 .
[2] K. Prkachin,et al. The structure, reliability and validity of pain expression: Evidence from patients with shoulder pain , 2008, PAIN.
[3] Shih-Fu Chang,et al. Context-Based Concept Fusion with Boosted Conditional Random Fields , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.
[4] Vladimir Pavlovic,et al. Structured Output Ordinal Regression for Dynamic Facial Emotion Intensity Prediction , 2010, ECCV.
[5] Fei-Fei Li,et al. Recognizing Human-Object Interactions in Still Images by Modeling the Mutual Context of Objects and Human Poses , 2012, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6] John McDonald,et al. Investigating the Dynamics of Facial Expression , 2006, ISVC.
[7] Jeffrey F. Cohn,et al. Painful data: The UNBC-McMaster shoulder pain expression archive database , 2011, Face and Gesture 2011.
[8] Maja Pantic,et al. Continuous Pain Intensity Estimation from Facial Expressions , 2012, ISVC.
[9] Jiawei Han,et al. Spectral Regression for Efficient Regularized Subspace Learning , 2007, 2007 IEEE 11th International Conference on Computer Vision.
[10] Jaime S. Cardoso,et al. Measuring the Performance of Ordinal Classification , 2011, Int. J. Pattern Recognit. Artif. Intell..
[11] Arman Savran,et al. Regression-based intensity estimation of facial action units , 2012, Image Vis. Comput..
[12] Chih-Jen Lin,et al. LIBSVM: A library for support vector machines , 2011, TIST.
[13] Cristian Sminchisescu,et al. Conditional Random Fields for Contextual Human Motion Recognition , 2005, ICCV.
[14] Andrea Esuli,et al. Evaluation Measures for Ordinal Regression , 2009, 2009 Ninth International Conference on Intelligent Systems Design and Applications.
[15] Thorsten Joachims,et al. Cutting-plane training of structural SVMs , 2009, Machine Learning.
[16] Vladimir Pavlovic,et al. Multi-output Laplacian dynamic ordinal regression for facial expression recognition and intensity estimation , 2012, 2012 IEEE Conference on Computer Vision and Pattern Recognition.
[17] B. Welch. The structure , 1992 .
[18] R. Fildes. Journal of the Royal Statistical Society (B): Gary K. Grunwald, Adrian E. Raftery and Peter Guttorp, 1993, “Time series of continuous proportions”, 55, 103–116.☆ , 1993 .
[19] Thomas Hofmann,et al. Large Margin Methods for Structured and Interdependent Output Variables , 2005, J. Mach. Learn. Res..
[20] Fernando De la Torre,et al. Continuous AU intensity estimation using localized, sparse facial feature space , 2013, 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG).
[21] Jeffrey F. Cohn,et al. Automatic detection of pain intensity , 2012, ICMI '12.
[22] Wei Chu,et al. New approaches to support vector ordinal regression , 2005, ICML.
[23] Lawrence K. Saul,et al. Large Margin Hidden Markov Models for Automatic Speech Recognition , 2006, NIPS.
[24] Rainer Winkelmann,et al. Analysis of Microdata , 2006 .
[25] Mohammad H. Mahoor,et al. DISFA: A Spontaneous Facial Action Intensity Database , 2013, IEEE Transactions on Affective Computing.
[26] Janez Demsar,et al. Statistical Comparisons of Classifiers over Multiple Data Sets , 2006, J. Mach. Learn. Res..
[27] Maja Pantic,et al. Machine analysis of facial behaviour: naturalistic and dynamic behaviour , 2009, Philosophical Transactions of the Royal Society B: Biological Sciences.
[28] Wei Chu,et al. Gaussian Processes for Ordinal Regression , 2005, J. Mach. Learn. Res..
[29] Alex Pentland,et al. Human computing and machine understanding of human behavior: a survey , 2006, ICMI '06.
[30] Chong-Wah Ngo,et al. Semantic context modeling with maximal margin Conditional Random Fields for automatic image annotation , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[31] Andrew McCallum,et al. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data , 2001, ICML.
[32] Daniel S. Messinger,et al. A framework for automated measurement of the intensity of non-posed Facial Action Units , 2009, 2009 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops.