Ubiquitous Technologies for Emotion Recognition

Emotions play a very important role in how we think and behave. As such, the emotions we feel every day can compel us to act and influence the decisions and plans we make about our lives. Being able to measure, analyze, and better comprehend how or why our emotions may change is thus of much relevan...

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Other Authors: Banos, Oresti (Editor), Castro, Luis A. (Editor), Villalonga, Claudia (Editor)
Format: Book Chapter
Published: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021
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Online Access:Get Fullteks
DOAB: description of the publication
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100 1 |a Banos, Oresti  |4 edt 
700 1 |a Castro, Luis A.  |4 edt 
700 1 |a Villalonga, Claudia  |4 edt 
700 1 |a Banos, Oresti  |4 oth 
700 1 |a Castro, Luis A.  |4 oth 
700 1 |a Villalonga, Claudia  |4 oth 
245 1 0 |a Ubiquitous Technologies for Emotion Recognition 
260 |a Basel, Switzerland  |b MDPI - Multidisciplinary Digital Publishing Institute  |c 2021 
300 |a 1 electronic resource (174 p.) 
506 0 |a Open Access  |2 star  |f Unrestricted online access 
520 |a Emotions play a very important role in how we think and behave. As such, the emotions we feel every day can compel us to act and influence the decisions and plans we make about our lives. Being able to measure, analyze, and better comprehend how or why our emotions may change is thus of much relevance to understand human behavior and its consequences. Despite the great efforts made in the past in the study of human emotions, it is only now, with the advent of wearable, mobile, and ubiquitous technologies, that we can aim to sense and recognize emotions, continuously and in real time. This book brings together the latest experiences, findings, and developments regarding ubiquitous sensing, modeling, and the recognition of human emotions. 
540 |a Creative Commons  |f https://creativecommons.org/licenses/by/4.0/  |2 cc  |4 https://creativecommons.org/licenses/by/4.0/ 
546 |a English 
650 7 |a Information technology industries  |2 bicssc 
653 |a self-management interview application 
653 |a emotion analysis 
653 |a facial recognition 
653 |a image-mining 
653 |a deep convolutional neural network 
653 |a emotion recognition 
653 |a pattern recognition 
653 |a texture descriptors 
653 |a mobile tool 
653 |a neuromarketing 
653 |a brain computer interface (BCI) 
653 |a consumer preferences 
653 |a EEG signal 
653 |a deep learning 
653 |a deep neural network (DNN) 
653 |a electroencephalogram (EEG) 
653 |a logistic regression 
653 |a Gaussian kernel 
653 |a Laplacian prior 
653 |a affective computing 
653 |a human-robot interaction 
653 |a thermal IR imaging 
653 |a social robots 
653 |a facial expression analysis 
653 |a line segment feature analysis 
653 |a dimensionality reduction 
653 |a convolutional recurrent neural network 
653 |a driver health risk 
653 |a intelligent speech signal processing 
653 |a human computer interaction 
653 |a supervised learning 
653 |a computer vision 
653 |a optical flow 
653 |a micro facial expressions 
653 |a real-time processing 
653 |a driver stress state 
653 |a IR imaging 
653 |a machine learning 
653 |a support vector machine (SVR) 
653 |a advanced driver-assistance systems (ADAS) 
653 |a artificial intelligence 
653 |a image processing 
653 |a video processing 
856 4 0 |a www.oapen.org  |u https://mdpi.com/books/pdfview/book/4136  |7 0  |z Get Fullteks 
856 4 0 |a www.oapen.org  |u https://directory.doabooks.org/handle/20.500.12854/76689  |7 0  |z DOAB: description of the publication