Journal Article10.1016/J.IMAVIS.2005.12.021
Authentic facial expression analysis
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TL;DR: This paper presents the effort in creating an authentic facial expression database based on spontaneous emotions derived from the environment, and test and compare a wide range of classifiers from the machine learning literature that can be used for facial expression classification.
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About: This article is published in Image and Vision Computing. The article was published on 01 Dec 2007. The article focuses on the topics: Facial expression & Emotional intelligence.
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Citations
Local Binary Patterns and Its Application to Facial Image Analysis: A Survey
Di Huang,Caifeng Shan,Mohsen Ardabilian,Yunhong Wang,Liming Chen +4 more
- 01 Nov 2011
TL;DR: As a typical application of the LBP approach, LBP-based facial image analysis is extensively reviewed, while its successful extensions, which deal with various tasks of facial imageAnalysis, are also highlighted.
A high-resolution 3D dynamic facial expression database
Lijun Yin,Xiaochen Chen,Yi Sun,T. Worm,Michael Reale +4 more
- 01 Sep 2008
TL;DR: This paper presents a newly created high-resolution 3D dynamic facial expression database, which is made available to the scientific research community and has been validated through the authors' facial expression recognition experiment using an HMM based 3D spatio-temporal facial descriptor.
609
Survey on RGB, 3D, Thermal, and Multimodal Approaches for Facial Expression Recognition: History, Trends, and Affect-Related Applications
TL;DR: A new taxonomy of automatic RGB, 3D, thermal and multimodal facial expression analysis is defined, encompassing all steps from face detection to facial expression recognition, and described and classify the state of the art methods accordingly.
488
Extended deep neural network for facial emotion recognition
TL;DR: The aim of this work is to classify each image into one of six facial emotion classes, based on single Deep Convolutional Neural Networks (DNNs), which contain convolution layers and deep residual blocks.
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DECAF: MEG-Based Multimodal Database for Decoding Affective Physiological Responses
Mojtaba Khomami Abadi,Ramanathan Subramanian,Seyed Mostafa Kia,Paolo Avesani,Ioannis Patras,Nicu Sebe +5 more
TL;DR: DECAF is presented, a detailed analysis of the correlations between participants' self-assessments and their physiological responses and single-trial classification results for valence, arousal and dominance are presented, with performance evaluation against existing data sets.
366
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