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Statistical Machine Learning for Human Behaviour Analysis - Sergio Escalera - Bog

Bag om Statistical Machine Learning for Human Behaviour Analysis

This Special Issue focused on novel vision-based approaches, mainly related to computer vision and machine learning, for the automatic analysis of human behaviour. We solicited submissions on the following topics: information theory-based pattern classification, biometric recognition, multimodal human analysis, low resolution human activity analysis, face analysis, abnormal behaviour analysis, unsupervised human analysis scenarios, 3D/4D human pose and shape estimation, human analysis in virtual/augmented reality, affective computing, social signal processing, personality computing, activity recognition, human tracking in the wild, and application of information-theoretic concepts for human behaviour analysis. In the end, 15 papers were accepted for this special issue. These papers, that are reviewed in this editorial, analyse human behaviour from the aforementioned perspectives, defining in most of the cases the state of the art in their corresponding field.

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  • Sprog:
  • Engelsk
  • ISBN:
  • 9783039362288
  • Indbinding:
  • Hardback
  • Sideantal:
  • 300
  • Udgivet:
  • 17. juni 2020
  • Størrelse:
  • 170x244x24 mm.
  • Vægt:
  • 844 g.
  • 2-3 uger.
  • 18. januar 2025
Forlænget returret til d. 31. januar 2025
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Beskrivelse af Statistical Machine Learning for Human Behaviour Analysis

This Special Issue focused on novel vision-based approaches, mainly related to computer vision and machine learning, for the automatic analysis of human behaviour. We solicited submissions on the following topics: information theory-based pattern classification, biometric recognition, multimodal human analysis, low resolution human activity analysis, face analysis, abnormal behaviour analysis, unsupervised human analysis scenarios, 3D/4D human pose and shape estimation, human analysis in virtual/augmented reality, affective computing, social signal processing, personality computing, activity recognition, human tracking in the wild, and application of information-theoretic concepts for human behaviour analysis. In the end, 15 papers were accepted for this special issue. These papers, that are reviewed in this editorial, analyse human behaviour from the aforementioned perspectives, defining in most of the cases the state of the art in their corresponding field.

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