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Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction [electronic resource] : 4th IAPR TC 9 Workshop, MPRSS 2016, Cancun, Mexico, December 4, 2016, Revised Selected Papers / edited by Friedhelm Schwenker, Stefan Scherer.

Contributor(s): Schwenker, Friedhelm [editor.] | Scherer, Stefan [editor.] | SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: Lecture Notes in Artificial Intelligence: 10183Publisher: Cham : Springer International Publishing : Imprint: Springer, 2017Edition: 1st ed. 2017.Description: VIII, 161 p. 61 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319592596.Subject(s): Artificial intelligence | User interfaces (Computer systems) | Human-computer interaction | Pattern recognition systems | Data mining | Artificial Intelligence | User Interfaces and Human Computer Interaction | Automated Pattern Recognition | Data Mining and Knowledge DiscoveryAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Active Shape Model Vs. Deep Learning for Facial Emotion Recognition in Security -- Bimodal Recognition of Cognitive Load Based on Speech and Physiological Changes -- Human Mobility-Pattern Discovery and Next-Place Prediction from GPS data -- Fusion Architectures for Multimodal Cognitive Load Recognition -- Face Recognition in Home Security System Using Tensor Decomposition Based on Radix Hierarchical SVD -- Performance analysis of gesture recognition classifiers for building a human robot interface -- On Automatic Question Answering Using Efficient Primal-dual Models -- Hierarchical Bayesian Multiple Kernel Learning Based Feature Fusion for Action Recognition -- Audio Visual Speech Recognition Using Deep Recurrent Neural Networks -- Audio-Visual Recognition of Pain Intensity -- The Sense Emotion Database: A Multimodal Database for the Development and Systematic Validation of an Automatic Pain- and Emotion-Recognition System -- Photometric Stereo for 3D face reconstruction using non linear illumination models -- Recursively Measured Action Units.
In: Springer Nature eBookSummary: This book constitutes the thoroughly refereed post-workshop proceedings of the Fourth IAPR TC9 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2016, held in Cancun, Mexico, in December 2016. The 13 revised papers presented focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition, user identification, and recognition of human activities.
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Active Shape Model Vs. Deep Learning for Facial Emotion Recognition in Security -- Bimodal Recognition of Cognitive Load Based on Speech and Physiological Changes -- Human Mobility-Pattern Discovery and Next-Place Prediction from GPS data -- Fusion Architectures for Multimodal Cognitive Load Recognition -- Face Recognition in Home Security System Using Tensor Decomposition Based on Radix Hierarchical SVD -- Performance analysis of gesture recognition classifiers for building a human robot interface -- On Automatic Question Answering Using Efficient Primal-dual Models -- Hierarchical Bayesian Multiple Kernel Learning Based Feature Fusion for Action Recognition -- Audio Visual Speech Recognition Using Deep Recurrent Neural Networks -- Audio-Visual Recognition of Pain Intensity -- The Sense Emotion Database: A Multimodal Database for the Development and Systematic Validation of an Automatic Pain- and Emotion-Recognition System -- Photometric Stereo for 3D face reconstruction using non linear illumination models -- Recursively Measured Action Units.

This book constitutes the thoroughly refereed post-workshop proceedings of the Fourth IAPR TC9 Workshop on Pattern Recognition of Social Signals in Human-Computer-Interaction, MPRSS 2016, held in Cancun, Mexico, in December 2016. The 13 revised papers presented focus on pattern recognition, machine learning and information fusion methods with applications in social signal processing, including multimodal emotion recognition, user identification, and recognition of human activities.

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