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 hum...

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Bibliographic Details
Other Authors:	Moeslund, Thomas (Editor), Escalera, Sergio (Editor), Anbarjafari, Gholamreza (Editor), Nasrollahi, Kamal (Editor), Wan, Jun (Editor)
Format:	Book Chapter
Published:	Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020
Subjects:	History of engineering & technology multi-objective evolutionary algorithms rule-based classifiers interpretable machine learning categorical data hand sign language deep learning restricted Boltzmann machine (RBM) multi-modal profoundly deaf noisy image ensemble methods adaptive classifiers recurrent concepts concept drift stock price direction prediction toe-off detection gait event silhouettes difference convolutional neural network saliency detection foggy image spatial domain frequency domain object contour detection discrete stationary wavelet transform attention allocation attention behavior hybrid entropy information entropy single pixel single photon image acquisition time-of-flight action recognition fibromyalgia Learning Using Concave and Convex Kernels Empatica E4 self-reported survey speech emotion recognition 3D convolutional neural networks k-means clustering spectrograms context-aware framework accuracy false negative rate individual behavior estimation statistical-based time-frequency domain and crowd condition emotion recognition gestures body movements Kinect sensor neural networks face analysis face segmentation head pose estimation age classification gender classification singular point detection boundary segmentation blurring detection fingerprint image enhancement fingerprint quality speech committee of classifiers biometric recognition multimodal-based human identification privacy privacy-aware
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Summary:	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.
Physical Description:	1 electronic resource (300 p.)
ISBN:	books978-3-03936-229-5 9783039362288 9783039362295
Access:	Open Access

Statistical Machine Learning for Human Behaviour Analysis

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