Statistical Machine Learning for Human Behaviour Analysis

ISBN 10: 3039362283 / ISBN 13: 9783039362288

Published by MDPI AG, 2020

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - 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.

Seller Inventory # 9783039362288

Bibliographic Details

• Title: Statistical Machine Learning for Human Behaviour Analysis
• Publisher: MDPI AG
• Publication Date: 2020
• Language: English
• ISBN 10: 3039362283
• ISBN 13: 9783039362288
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 24D millimeters 250 millimeters width by 175 millimeters height by 24 millimeters depth
• Weight: 950 grams

About this title

Synopsis

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.