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Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction: 4th IAPR TC 9 Workshop, MPRSS 2016, Cancun, Mexico, December 4, 2016, Revised Selected Papers de Friedhelm Schwenker

Multimodal Pattern Recognition of Social Signals in Human-Computer-Interaction: 4th IAPR TC 9 Workshop, MPRSS 2016, Cancun, Mexico, December 4, 2016, Revised Selected Papers: Lecture Notes in Computer Science, cartea 10183

Editat de Friedhelm Schwenker, Stefan Scherer
en Limba Engleză Paperback – 31 mai 2017
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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Specificații

ISBN-13: 9783319592589
ISBN-10: 3319592580
Pagini: 161
Ilustrații: VIII, 161 p. 61 illus.
Dimensiuni: 155 x 235 mm
Greutate: 0.25 kg
Ediția:1st ed. 2017
Editura: Springer International Publishing
Colecția Springer
Seriile Lecture Notes in Computer Science, Lecture Notes in Artificial Intelligence

Locul publicării:Cham, Switzerland

Cuprins

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.

Caracteristici

Includes supplementary material: sn.pub/extras