Machine Learning Systems for Multimodal Affect Recognition

by Markus Kachele

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Book cover for Machine Learning Systems for Multimodal Affect Recognition

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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. 

  • ISBN13 9783658286736
  • Publish Date 3 December 2019
  • Publish Status Active
  • Publish Country DE
  • Imprint Springer Vieweg
  • Edition 1st ed. 2020
  • Format Paperback
  • Pages 188
  • Language English