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Facial Expression Recognition from Video Sequences: Temporal and Static Modelling

by Ira Cohen, Nicu Sebe, Larry Chen, Ashutosh Garg, Thomas S. Huang - Computer Vision and Image Understanding , 2003
"... Human-computer intelligent interaction (HCII) is an emerging field of science aimed at providing natural ways for humans to use computers as aids. It is argued that for the computer to be able to interact with humans, it needs to have the communication skills of humans. One of these skills is the ab ..."
Abstract - Cited by 195 (18 self) - Add to MetaCart
is the ability to understand the emotional state of the person. The most expressive way humans display emotions is through facial expressions. In this work we report on several advances we have made in building a system for classification of facial expressions from continuous video input. We introduce and test

Dynamics of Facial Expression: Recognition of Facial Actions and Their Temporal Segments from Face Profile Image Sequences

by Maja Pantic, Ioannis Patras - IEEE Trans. Systems, Man, and Cybernetics, Part B , 2006
"... Abstract—Automatic analysis of human facial expression is a challenging problem with many applications. Most of the existing automated systems for facial expression analysis attempt to recognize a few prototypic emotional expressions, such as anger and happiness. Instead of representing another appr ..."
Abstract - Cited by 111 (19 self) - Add to MetaCart
Abstract—Automatic analysis of human facial expression is a challenging problem with many applications. Most of the existing automated systems for facial expression analysis attempt to recognize a few prototypic emotional expressions, such as anger and happiness. Instead of representing another

Emotion Recognition from Facial Expressions using Multilevel HMM

by Ira Cohen, Ashutosh Garg, Thomas S. Huang - in In Neural Information Processing Systems , 2000
"... Human-computer intelligent interaction (HCII) is an emerging field of science aimed at providing natural ways for humans to use computers as aids. It is argued that for the computer to be able to interact with humans, it needs to have the communication skills of humans. One of these skills is the ab ..."
Abstract - Cited by 23 (0 self) - Add to MetaCart
explored for speech recognition applications. Among these methods are template matching using dynamic programming methods and hidden Markov models (HMM). This work exploits existing methods and proposes a new architecture of HMMs for automatically segmenting and recognizing human facial expression from

Geometric Approach for Human Emotion Recognition using Facial Expression

by S. S. Bavkar, Vpcoe Baramati, U. Deshmukh, Vpcoe Baramati
"... Paper contains emotion recognition system based on facial expression using Geometric approach. A human emotion recognition system consists of three steps: face detection, facial feature extraction and facial expression classification. In this paper, we used an anthropometric model to detect facial f ..."
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Paper contains emotion recognition system based on facial expression using Geometric approach. A human emotion recognition system consists of three steps: face detection, facial feature extraction and facial expression classification. In this paper, we used an anthropometric model to detect facial

Modeling Naturalistic Affective States Via Facial, Vocal, and Bodily Expressions Recognition

by Kostas Karpouzis, George Caridakis, Loic Kessous, Noam Amir, Amaryllis Raouzaiou, Lori Malatesta, Stefanos Kollias
"... Abstract. Affective and human-centered computing have attracted a lot of attention during the past years, mainly due to the abundance of devices and environments able to exploit multimodal input from the part of the users and adapt their functionality to their preferences or individual habits. In th ..."
Abstract - Cited by 14 (5 self) - Add to MetaCart
Recurrent Network’ which lends itself well to modeling dynamic events in both user’s facial expressions and speech. Moreover this approach differs from existing work in that it models user expressivity using a dimensional representation of activation and valence, instead of detecting discrete ‘universal

Related Work in Facial Recognition

by unknown authors
"... With its ability to create more than 10,000 expressions, the face has greater variability than any other channel of nonverbal expression. Thus, automated facial-feature tracking lets researchers tap into a rich resource of behavioral cues. In the past, researchers have shown great interest in using ..."
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micro-momentary facial expressions to predict human emotion and mental states. 1–4 In a recent study, Rana El Kaliouby and Peter Robinson developed a general computational model to recognize six classes of complex emotions and implemented this model as a real-time system. 5 Their approach used dynamic

Simultaneous Facial Feature Tracking and Facial Expression Recognition

by Yongqiang Li, Yongping Zhao, Shangfei Wang, Qiang Ji
"... The tracking and recognition of facial activities from images or videos attracted great attention in computer vision field. Facial activities are characterized by three levels: First, in the bottom level, facial feature points around each facial component, i.e., eyebrow, mouth, etc, capture the deta ..."
Abstract - Cited by 1 (0 self) - Add to MetaCart
the global facial muscle movement and are commonly used to describe the human emotion state. In contrast to the mainstream approaches, which usually only focus on one or two levels of facial activities, and track (or recognize) them separately, this paper introduces a unified probabilistic framework based

Deeply Learning Deformable Facial Action Parts Model for Dynamic Expression Analysis

by Ruiping Wang, Xilin Chen
"... Abstract. Expressions are facial activities invoked by sets of muscle motions, which would give rise to large variations in appearance mainly around facial parts. Therefore, for visual-based expression analysis, local-izing the action parts and encoding them effectively become two essential but chal ..."
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but challenging problems. To take them into account jointly for expres-sion analysis, in this paper, we propose to adapt 3D Convolutional Neural Networks (3D CNN) with deformable action parts constraints. Specifi-cally, we incorporate a deformable parts learning component into the 3D CNN framework, which can

Dynamic Facial Emotion Recognition Oriented to HCI Applications

by Samuel Marcos Pablos, Jaime Gómez García-bermejo, Eduardo Zalama Casanova, Joaquín López , 2013
"... As part of a multimodal animated avatar previously presented in Marcos-Pablos et al. ((2010) A realistic, virtual head for human-computer interaction. Interact. Comput., 22, 176–192, ISSN 0953-5438), in this paper we describe a method for dynamic recognition of displayed facial emotions on low-resol ..."
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As part of a multimodal animated avatar previously presented in Marcos-Pablos et al. ((2010) A realistic, virtual head for human-computer interaction. Interact. Comput., 22, 176–192, ISSN 0953-5438), in this paper we describe a method for dynamic recognition of displayed facial emotions on low

The integration of optical flow and deformable models with applications to human face shape and motion estimation

by Douglas Decarlo, Dimitris Metaxas , 1996
"... We present a formal methodology for the integration of optical flow and deformable models. The optical flow constraint equation provides a non-holonomic constraint on the motion of the deformable model. In this augmented system, forces computed from edges and optical flow are used simultaneously. Wh ..."
Abstract - Cited by 123 (6 self) - Add to MetaCart
for treating visual cues as constraints on deformable models. We apply this framework to human face shape and motion estimation. Our 3-D deformable face model uses a small number of parameters to describe a rich variety of face shapes and facial expressions. We present experiments in extracting the shape
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