Machine Learning Systems for Multimodal Affect Recognition

Markus Kächele

ISBN 10: 3658286733 / ISBN 13: 9783658286736

Published by Springer Gabler, 2019

About this Item

Druck auf Anfrage Neuware - Printed after ordering - Markus Kächele offers a detailed view on the different steps in the affective computing pipeline, ranging from corpus design and recording over annotation and feature extraction to post-processing, classification of individual modalities and fusion in the context of ensemble classifiers. He focuses on multimodal recognition of discrete and continuous emotional and medical states. As such, specifically the peculiarities that arise during annotation and processing of continuous signals are highlighted. Furthermore, methods are presented that allow personalization of datasets and adaptation of classifiers to new situations and persons.

Seller Inventory # 9783658286736

Bibliographic Details

• Title: Machine Learning Systems for Multimodal Affect Recognition
• Publisher: Springer Gabler
• Publication Date: 2019
• Language: English
• ISBN 10: 3658286733
• ISBN 13: 9783658286736
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 210W x 148H x 12D millimeters 210 millimeters width by 148 millimeters height by 12 millimeters depth
• Weight: 276 grams

About this title

Synopsis

Markus Kächele offers a detailed view on the different steps in the affective computing pipeline, ranging from corpus design and recording over annotation and feature extraction to post-processing, classification of individual modalities and fusion in the context of ensemble classifiers. He focuses on multimodal recognition of discrete and continuous emotional and medical states. As such, specifically the peculiarities that arise during annotation and processing of continuous signals are highlighted. Furthermore, methods are presented that allow personalization of datasets and adaptation of classifiers to new situations and persons. 

About the Author

Dr. Markus Kächele is managing partner of Ikara Vision Systems, a spin-off of the German Research Center for Artificial Intelligence (DFKI). He focuses on bridging the gap between research and industrial applications in the fields of deep learning and computer vision.