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Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction

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Cover of 'Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction'

Table of Contents

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    Book Overview
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    Chapter 1 Active Shape Model vs. Deep Learning for Facial Emotion Recognition in Security
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    Chapter 2 Bimodal Recognition of Cognitive Load Based on Speech and Physiological Changes
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    Chapter 3 Human Mobility-Pattern Discovery and Next-Place Prediction from GPS Data
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    Chapter 4 Fusion Architectures for Multimodal Cognitive Load Recognition
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    Chapter 5 Face Recognition in Home Security System Using Tensor Decomposition Based on Radix-(2 × 2) Hierarchical SVD
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    Chapter 6 Performance Analysis of Gesture Recognition Classifiers for Building a Human Robot Interface
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    Chapter 7 On Automatic Question Answering Using Efficient Primal-Dual Models
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    Chapter 8 Hierarchical Bayesian Multiple Kernel Learning Based Feature Fusion for Action Recognition
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    Chapter 9 Audio Visual Speech Recognition Using Deep Recurrent Neural Networks
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    Chapter 10 Audio-Visual Recognition of Pain Intensity
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    Chapter 11 The SenseEmotion Database: A Multimodal Database for the Development and Systematic Validation of an Automatic Pain- and Emotion-Recognition System
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    Chapter 12 Photometric Stereo for 3D Face Reconstruction Using Non Linear Illumination Models
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    Chapter 13 Recursively Measured Action Units
Attention for Chapter 12: Photometric Stereo for 3D Face Reconstruction Using Non Linear Illumination Models
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Citations

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Chapter title
Photometric Stereo for 3D Face Reconstruction Using Non Linear Illumination Models
Chapter number 12
Book title
Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction
Published by
Springer, Cham, December 2016
DOI 10.1007/978-3-319-59259-6_12
Book ISBNs
978-3-31-959258-9, 978-3-31-959259-6
Authors

Barbara Villarini, Athanasios Gkelias, Vasilios Argyriou, Villarini, Barbara, Gkelias, Athanasios, Argyriou, Vasilios

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 50%
Unknown 1 50%
Readers by discipline Count As %
Computer Science 1 50%
Unknown 1 50%

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