Statistical Machine Learning For Human Behaviour Analysis

Author : Thomas Moeslund,Sergio Escalera,Gholamreza Anbarjafari,Kamal Nasrollahi,Jun Wan
Publisher : MDPI
Page : 300 pages
File Size : 52,7 Mb
Release : 2020-06-17
Category : Technology & Engineering
ISBN : 9783039362288

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Statistical Machine Learning for Human Behaviour Analysis by Thomas Moeslund,Sergio Escalera,Gholamreza Anbarjafari,Kamal Nasrollahi,Jun Wan Pdf

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.

Author : Thomas Moeslund,Sergio Escalera,Gholamreza Anbarjafari,Kamal Nasrollahi,Jun Wan
Publisher : Unknown
Page : 300 pages
File Size : 46,7 Mb
Release : 2020
Category : Electronic
ISBN : 3039362291

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Statistical Machine Learning for Human Behaviour Analysis by Thomas Moeslund,Sergio Escalera,Gholamreza Anbarjafari,Kamal Nasrollahi,Jun Wan Pdf

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.

Author : Enrique Garcia Ceja
Publisher : CRC Press
Page : 434 pages
File Size : 53,6 Mb
Release : 2021-11-26
Category : Psychology
ISBN : 9781000484236

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Behavior Analysis with Machine Learning Using R by Enrique Garcia Ceja Pdf

Behavior Analysis with Machine Learning Using R introduces machine learning and deep learning concepts and algorithms applied to a diverse set of behavior analysis problems. It focuses on the practical aspects of solving such problems based on data collected from sensors or stored in electronic records. The included examples demonstrate how to perform common data analysis tasks such as: data exploration, visualization, preprocessing, data representation, model training and evaluation. All of this, using the R programming language and real-life behavioral data. Even though the examples focus on behavior analysis tasks, the covered underlying concepts and methods can be applied in any other domain. No prior knowledge in machine learning is assumed. Basic experience with R and basic knowledge in statistics and high school level mathematics are beneficial. Features: Build supervised machine learning models to predict indoor locations based on WiFi signals, recognize physical activities from smartphone sensors and 3D skeleton data, detect hand gestures from accelerometer signals, and so on. Program your own ensemble learning methods and use Multi-View Stacking to fuse signals from heterogeneous data sources. Use unsupervised learning algorithms to discover criminal behavioral patterns. Build deep learning neural networks with TensorFlow and Keras to classify muscle activity from electromyography signals and Convolutional Neural Networks to detect smiles in images. Evaluate the performance of your models in traditional and multi-user settings. Build anomaly detection models such as Isolation Forests and autoencoders to detect abnormal fish behaviors. This book is intended for undergraduate/graduate students and researchers from ubiquitous computing, behavioral ecology, psychology, e-health, and other disciplines who want to learn the basics of machine learning and deep learning and for the more experienced individuals who want to apply machine learning to analyze behavioral data.

Author : D. Jude Hemanth
Publisher : Springer Nature
Page : 205 pages
File Size : 43,8 Mb
Release : 2019-11-20
Category : Technology & Engineering
ISBN : 9783030351397

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Human Behaviour Analysis Using Intelligent Systems by D. Jude Hemanth Pdf

Human–computer interaction (HCI) is one of the most significant areas of computational intelligence. This book focuses on the human emotion analysis aspects of HCI, highlighting innovative methodologies for emotion analysis by machines/computers and their application areas. The methodologies are presented with numerical results to enable researchers to replicate the work. This multidisciplinary book is useful to researchers and academicians, as well as students wanting to pursue a career in computational intelligence. It can also be used as a handbook, reference book, and a textbook for short courses.

Author : Yangsheng Xu,Ka Keung C. Lee
Publisher : CRC Press
Page : 360 pages
File Size : 50,9 Mb
Release : 2005-09-06
Category : Technology & Engineering
ISBN : 0849377838

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Human Behavior Learning and Transfer by Yangsheng Xu,Ka Keung C. Lee Pdf

Bridging the gap between human-computer engineering and control engineering, Human Behavior Learning and Transfer delineates how to abstract human action and reaction skills into computational models. The authors include methods for modeling a variety of human action and reaction behaviors and explore processes for evaluating, optimizing, and transferring human skills. They also cover modeling continuous and discontinuous human control strategy and discuss simulation studies and practical real-life situations. The book examines how to model two main aspects of human behavior: reaction skills and action skills. It begins with a discussion of the various topics involved in human reaction skills modeling. The authors apply machine learning techniques and statistical analysis to abstracting models of human reaction control strategy. They contend that such models can be learned sufficiently to emulate complex human control behaviors in the feedback loop. The second half of the book explores issues related to human action skills modeling. The methods presented are based on techniques for reducing the dimensionality of data sets, while preserving as much useful information as possible. The modeling approaches developed are applied in real-life applications including navigation of smart wheel chairs and intelligent surveillance. Written in a consistent, easily approachable style, the book includes in-depth discussions of a broad range of topics. It provides the tools required to formalize human behaviors into algorithmic, machine-coded strategies.

Author : Akinori Okada,Kazuo Shigemasu,Ryozo Yoshino,Satoru Yokoyama
Publisher : Springer Nature
Page : 335 pages
File Size : 45,5 Mb
Release : 2023-09-17
Category : Mathematics
ISBN : 9789819922406

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Facets of Behaviormetrics by Akinori Okada,Kazuo Shigemasu,Ryozo Yoshino,Satoru Yokoyama Pdf

This edited book is the first one written in English that deals comprehensively with behavior metrics. The term “behaviormetrics” comprehends the research including all sorts of quantitative approaches to disclose human behavior. Researchers in behavior metrics have developed, extended, and improved methods such as multivariate statistical analysis, survey methods, cluster analysis, machine learning, multidimensional scaling, corresponding analysis or quantification theory, network analysis, clustering, factor analysis, test theory, and related factors. In the spirit of behavior metrics, researchers applied these methods to data obtained by surveys, experiments, or websites from a diverse range of fields. The purpose of this book is twofold. One is to represent studies that display how the basic elements of behavior metrics have developed into present-day behavior metrics. The other is to represent studies performed mainly by those who would like to pioneer new fields of behavior metrics and studies that display elements of future behavior metrics. These studies consist of various characteristics such as those dealing with theoretical or conceptual subjects, the algorithm, the model, the method, and the application to a wide variety of fields. This book helps readers to understand the present and future of behavior metrics.

Author : Rong Chen,Tianyi Yan,Yiannis Ventikos
Publisher : Frontiers Media SA
Page : 290 pages
File Size : 55,9 Mb
Release : 2021-04-16
Category : Science
ISBN : 9782889666836

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Brain-inspired Machine Learning and Computation for Brain-Behavior Analysis by Rong Chen,Tianyi Yan,Yiannis Ventikos Pdf

Author : Ross Jacobucci,Kevin J. Grimm,Zhiyong Zhang
Publisher : Guilford Publications
Page : 434 pages
File Size : 54,7 Mb
Release : 2023-07-31
Category : Business & Economics
ISBN : 9781462552931

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Machine Learning for Social and Behavioral Research by Ross Jacobucci,Kevin J. Grimm,Zhiyong Zhang Pdf

"Over the past 20 years, there has been an incredible change in the size, structure, and types of data collected in the social and behavioral sciences. Thus, social and behavioral researchers have increasingly been asking the question: "What do I do with all of this data?" The goal of this book is to help answer that question. It is our viewpoint that in social and behavioral research, to answer the question "What do I do with all of this data?", one needs to know the latest advances in the algorithms and think deeply about the interplay of statistical algorithms, data, and theory. An important distinction between this book and most other books in the area of machine learning is our focus on theory"--

Author : Shaogang Gong,Tao Xiang
Publisher : Springer Science & Business Media
Page : 356 pages
File Size : 45,8 Mb
Release : 2011-05-26
Category : Computers
ISBN : 9780857296702

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Visual Analysis of Behaviour by Shaogang Gong,Tao Xiang Pdf

This book presents a comprehensive treatment of visual analysis of behaviour from computational-modelling and algorithm-design perspectives. Topics: covers learning-group activity models, unsupervised behaviour profiling, hierarchical behaviour discovery, learning behavioural context, modelling rare behaviours, and “man-in-the-loop” active learning; examines multi-camera behaviour correlation, person re-identification, and “connecting-the-dots” for abnormal behaviour detection; discusses Bayesian information criterion, Bayesian networks, “bag-of-words” representation, canonical correlation analysis, dynamic Bayesian networks, Gaussian mixtures, and Gibbs sampling; investigates hidden conditional random fields, hidden Markov models, human silhouette shapes, latent Dirichlet allocation, local binary patterns, locality preserving projection, and Markov processes; explores probabilistic graphical models, probabilistic topic models, space-time interest points, spectral clustering, and support vector machines.

Author : Albert Ali Salah,Theo Gevers
Publisher : Springer Science & Business Media
Page : 412 pages
File Size : 44,5 Mb
Release : 2011-10-07
Category : Computers
ISBN : 0857299948

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Computer Analysis of Human Behavior by Albert Ali Salah,Theo Gevers Pdf

This book provides a broad survey of advanced pattern recognition techniques for human behavior analysis. Clearly structured, the book begins with concise coverage of the major concepts, before introducing the most frequently used techniques and algorithms in detail, and then discussing examples of real applications. Features: contains contributions from an international selection of experts in the field; presents a thorough introduction to the fundamental topics of human behavior analysis; investigates methods for activity recognition, including gait and posture analysis, hand gesture analysis, and semantics of human behavior in image sequences; provides an accessible psychological treatise on social signals for the analysis of social behaviors; discusses voice and speech analysis, combined audiovisual cues, and social interactions and group dynamics; examines applications in different research fields; each chapter concludes with review questions, a summary of the topics covered, and a glossary.

Author : Chandril Ghosh
Publisher : Springer Nature
Page : 169 pages
File Size : 55,7 Mb
Release : 2022-10-17
Category : Psychology
ISBN : 9783031146343

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Data Analysis with Machine Learning for Psychologists by Chandril Ghosh Pdf

The power of data drives the digital economy of the 21st century. It has been argued that data is as vital a resource as oil was during the industrial revolution. An upward trend in the number of research publications using machine learning in some of the top journals in combination with an increasing number of academic recruiters within psychology asking for Python knowledge from applicants indicates a growing demand for these skills in the market. While there are plenty of books covering data science, rarely, if ever, books in the market address the need of social science students with no computer science background. They are typically written by engineers or computer scientists for people of their discipline. As a result, often such books are filled with technical jargon and examples irrelevant to psychological studies or projects. In contrast, this book was written by a psychologist in a simple, easy-to-understand way that is brief and accessible. The aim for this book was to make the learning experience on this topic as smooth as possible for psychology students/researchers with no background in programming or data science. Completing this book will also open up an enormous amount of possibilities for quantitative researchers in psychological science, as it will enable them to explore newer types of research questions.

Author : Hojjatollah Farahani,Marija Blagojević,Parviz Azadfallah,Peter Watson,Forough Esrafilian,Sara Saljoughi
Publisher : Springer Nature
Page : 262 pages
File Size : 44,8 Mb
Release : 2023-05-18
Category : Psychology
ISBN : 9783031311727

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An Introduction to Artificial Psychology by Hojjatollah Farahani,Marija Blagojević,Parviz Azadfallah,Peter Watson,Forough Esrafilian,Sara Saljoughi Pdf

Artificial Psychology (AP) is a highly multidisciplinary field of study in psychology. AP tries to solve problems which occur when psychologists do research and need a robust analysis method. Conventional statistical approaches have deep rooted limitations. These approaches are excellent on paper but often fail to model the real world. Mind researchers have been trying to overcome this by simplifying the models being studied. This stance has not received much practical attention recently. Promoting and improving artificial intelligence helps mind researchers to find a holistic model of mental models. This development achieves this goal by using multiple perspectives and multiple data sets together with interactive, and realistic models. In this book, the methodology of approximate inference in psychological research from a theoretical and practical perspective has been considered. Quantitative variable-oriented methodology and qualitative case-oriented methods are both used to explain the set-oriented methodology and this book combines the precision of quantitative methods with information from qualitative methods. This is a book that many researchers can use to expand and deepen their psychological research and is a book which can be useful to postgraduate students. The reader does not need an in-depth knowledge of mathematics or statistics because statistical and mathematical intuitions are key here and they will be learned through practice. What is important is to understand and use the new application of the methods for finding new, dynamic and realistic interpretations. This book incorporates theoretical fuzzy inference and deep machine learning algorithms in practice. This is the kind of book that we wished we had had when we were students. This book covers at least some of the most important issues in mind research including uncertainty, fuzziness, continuity, complexity and high dimensionality which are inherent to mind data. These are elements of artificial psychology. This book implements models using R software.

Author : Olga Isupova
Publisher : Springer
Page : 126 pages
File Size : 46,5 Mb
Release : 2018-02-24
Category : Technology & Engineering
ISBN : 9783319755083

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Machine Learning Methods for Behaviour Analysis and Anomaly Detection in Video by Olga Isupova Pdf

This thesis proposes machine learning methods for understanding scenes via behaviour analysis and online anomaly detection in video. The book introduces novel Bayesian topic models for detection of events that are different from typical activities and a novel framework for change point detection for identifying sudden behavioural changes. Behaviour analysis and anomaly detection are key components of intelligent vision systems. Anomaly detection can be considered from two perspectives: abnormal events can be defined as those that violate typical activities or as a sudden change in behaviour. Topic modelling and change-point detection methodologies, respectively, are employed to achieve these objectives. The thesis starts with the development of learning algorithms for a dynamic topic model, which extract topics that represent typical activities of a scene. These typical activities are used in a normality measure in anomaly detection decision-making. The book also proposes a novel anomaly localisation procedure. In the first topic model presented, a number of topics should be specified in advance. A novel dynamic nonparametric hierarchical Dirichlet process topic model is then developed where the number of topics is determined from data. Batch and online inference algorithms are developed. The latter part of the thesis considers behaviour analysis and anomaly detection within the change-point detection methodology. A novel general framework for change-point detection is introduced. Gaussian process time series data is considered. Statistical hypothesis tests are proposed for both offline and online data processing and multiple change point detection are proposed and theoretical properties of the tests are derived. The thesis is accompanied by open-source toolboxes that can be used by researchers and engineers.

Author : Chi-Chun Lee
Publisher : CRC Press
Page : 130 pages
File Size : 44,7 Mb
Release : 2022-09-01
Category : Science
ISBN : 9781000794182

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Modeling Human Behaviors in Psychology Using Engineering Methods by Chi-Chun Lee Pdf

The main purpose of the work is to showcase the interdisciplinary engineering approaches in modeling and understanding human behaviors during interpersonal interactions those that could be typical, distressed, or atypical. The ability to measure human behaviors quantitatively has been a core component and a major research direction in both fields of engineering and psychology – though often with distinct approaches designed for different targeted applications. Engineering methods often strive to achieve high predictive accuracies using behavioral informatics techniques; these techniques employ a combination of behavior measures derived using automated signal based descriptors, and of statistical frameworks modeled using machine learning techniques. These approaches are often distinct from the observational approaches the gold standard for the past three decades in the study of psychology, even in clinical settings. The observational approaches are largely based on human subjective judgments.

Author : Ariel Geib,Sarit Yang
Publisher : Springer Nature
Page : 134 pages
File Size : 48,5 Mb
Release : 2022-05-31
Category : Computers
ISBN : 9783031015786

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Predicting Human Decision-Making by Ariel Geib,Sarit Yang Pdf

Human decision-making often transcends our formal models of "rationality." Designing intelligent agents that interact proficiently with people necessitates the modeling of human behavior and the prediction of their decisions. In this book, we explore the task of automatically predicting human decision-making and its use in designing intelligent human-aware automated computer systems of varying natures—from purely conflicting interaction settings (e.g., security and games) to fully cooperative interaction settings (e.g., autonomous driving and personal robotic assistants). We explore the techniques, algorithms, and empirical methodologies for meeting the challenges that arise from the above tasks and illustrate major benefits from the use of these computational solutions in real-world application domains such as security, negotiations, argumentative interactions, voting systems, autonomous driving, and games. The book presents both the traditional and classical methods as well as the most recent and cutting edge advances, providing the reader with a panorama of the challenges and solutions in predicting human decision-making.