Human Activity Recognition And Prediction

Author : Yun Fu
Publisher : Springer
Page : 174 pages
File Size : 50,8 Mb
Release : 2015-12-23
Category : Technology & Engineering
ISBN : 9783319270043

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Human Activity Recognition and Prediction by Yun Fu Pdf

This book provides a unique view of human activity recognition, especially fine-grained human activity structure learning, human-interaction recognition, RGB-D data based action recognition, temporal decomposition, and causality learning in unconstrained human activity videos. The techniques discussed give readers tools that provide a significant improvement over existing methodologies of video content understanding by taking advantage of activity recognition. It links multiple popular research fields in computer vision, machine learning, human-centered computing, human-computer interaction, image classification, and pattern recognition. In addition, the book includes several key chapters covering multiple emerging topics in the field. Contributed by top experts and practitioners, the chapters present key topics from different angles and blend both methodology and application, composing a solid overview of the human activity recognition techniques.

Author : Miguel A. Labrador,Oscar D. Lara Yejas
Publisher : CRC Press
Page : 209 pages
File Size : 47,8 Mb
Release : 2013-12-05
Category : Computers
ISBN : 9781466588271

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Human Activity Recognition by Miguel A. Labrador,Oscar D. Lara Yejas Pdf

Learn How to Design and Implement HAR Systems The pervasiveness and range of capabilities of today’s mobile devices have enabled a wide spectrum of mobile applications that are transforming our daily lives, from smartphones equipped with GPS to integrated mobile sensors that acquire physiological data. Human Activity Recognition: Using Wearable Sensors and Smartphones focuses on the automatic identification of human activities from pervasive wearable sensors—a crucial component for health monitoring and also applicable to other areas, such as entertainment and tactical operations. Developed from the authors’ nearly four years of rigorous research in the field, the book covers the theory, fundamentals, and applications of human activity recognition (HAR). The authors examine how machine learning and pattern recognition tools help determine a user’s activity during a certain period of time. They propose two systems for performing HAR: Centinela, an offline server-oriented HAR system, and Vigilante, a completely mobile real-time activity recognition system. The book also provides a practical guide to the development of activity recognition applications in the Android framework.

Author : Zhongxu Hu,Chen Lv
Publisher : Springer Nature
Page : 130 pages
File Size : 48,8 Mb
Release : 2022-04-22
Category : Computers
ISBN : 9789811922909

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Vision-Based Human Activity Recognition by Zhongxu Hu,Chen Lv Pdf

This book offers a systematic, comprehensive, and timely review on V-HAR, and it covers the related tasks, cutting-edge technologies, and applications of V-HAR, especially the deep learning-based approaches. The field of Human Activity Recognition (HAR) has become one of the trendiest research topics due to the availability of various sensors, live streaming of data and the advancement in computer vision, machine learning, etc. HAR can be extensively used in many scenarios, for example, medical diagnosis, video surveillance, public governance, also in human–machine interaction applications. In HAR, various human activities such as walking, running, sitting, sleeping, standing, showering, cooking, driving, abnormal activities, etc., are recognized. The data can be collected from wearable sensors or accelerometer or through video frames or images; among all the sensors, vision-based sensors are now the most widely used sensors due to their low-cost, high-quality, and unintrusive characteristics. Therefore, vision-based human activity recognition (V-HAR) is the most important and commonly used category among all HAR technologies. The addressed topics include hand gestures, head pose, body activity, eye gaze, attention modeling, etc. The latest advancements and the commonly used benchmark are given. Furthermore, this book also discusses the future directions and recommendations for the new researchers.

Author : David Forsyth,Philip Torr,Andrew Zisserman
Publisher : Springer Science & Business Media
Page : 833 pages
File Size : 52,6 Mb
Release : 2008-10-07
Category : Computers
ISBN : 9783540886815

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Computer Vision - ECCV 2008 by David Forsyth,Philip Torr,Andrew Zisserman Pdf

The four-volume set comprising LNCS volumes 5302/5303/5304/5305 constitutes the refereed proceedings of the 10th European Conference on Computer Vision, ECCV 2008, held in Marseille, France, in October 2008. The 243 revised papers presented were carefully reviewed and selected from a total of 871 papers submitted. The four books cover the entire range of current issues in computer vision. The papers are organized in topical sections on recognition, stereo, people and face recognition, object tracking, matching, learning and features, MRFs, segmentation, computational photography and active reconstruction.

Author : Jason Brownlee
Publisher : Machine Learning Mastery
Page : 572 pages
File Size : 49,6 Mb
Release : 2018-08-30
Category : Computers
ISBN : 8210379456XXX

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Deep Learning for Time Series Forecasting by Jason Brownlee Pdf

Deep learning methods offer a lot of promise for time series forecasting, such as the automatic learning of temporal dependence and the automatic handling of temporal structures like trends and seasonality. With clear explanations, standard Python libraries, and step-by-step tutorial lessons you’ll discover how to develop deep learning models for your own time series forecasting projects.

Author : Jorge Luis Reyes Ortiz
Publisher : Springer
Page : 133 pages
File Size : 50,8 Mb
Release : 2015-01-14
Category : Technology & Engineering
ISBN : 9783319142746

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Smartphone-Based Human Activity Recognition by Jorge Luis Reyes Ortiz Pdf

The book reports on the author’s original work to address the use of today’s state-of-the-art smartphones for human physical activity recognition. By exploiting the sensing, computing and communication capabilities currently available in these devices, the author developed a novel smartphone-based activity-recognition system, which takes into consideration all aspects of online human activity recognition, from experimental data collection, to machine learning algorithms and hardware implementation. The book also discusses and describes solutions to some of the challenges that arose during the development of this approach, such as real-time operation, high accuracy, low battery consumption and unobtrusiveness. It clearly shows that it is possible to perform real-time recognition of activities with high accuracy using current smartphone technologies. As well as a detailed description of the methods, this book also provides readers with a comprehensive review of the fundamental concepts in human activity recognition. It also gives an accurate analysis of the most influential works in the field and discusses them in detail. This thesis was supervised by both the Universitat Politècnica de Catalunya (primary institution) and University of Genoa (secondary institution) as part of the Erasmus Mundus Joint Doctorate in Interactive and Cognitive Environments.

Author : Md Atiqur Rahman Ahad,Anindya Das Antar,Masud Ahmed
Publisher : Springer Nature
Page : 214 pages
File Size : 51,6 Mb
Release : 2020-07-30
Category : Computers
ISBN : 9783030513795

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IoT Sensor-Based Activity Recognition by Md Atiqur Rahman Ahad,Anindya Das Antar,Masud Ahmed Pdf

This book offer clear descriptions of the basic structure for the recognition and classification of human activities using different types of sensor module and smart devices in e.g. healthcare, education, monitoring the elderly, daily human behavior, and fitness monitoring. In addition, the complexities, challenges, and design issues involved in data collection, processing, and other fundamental stages along with datasets, methods, etc., are discussed in detail. The book offers a valuable resource for readers in the fields of pattern recognition, human–computer interaction, and the Internet of Things.

Author : Md Atiqur Rahman Ahad,Paula Lago,Sozo Inoue
Publisher : Springer Nature
Page : 126 pages
File Size : 54,8 Mb
Release : 2020-11-20
Category : Technology & Engineering
ISBN : 9789811582691

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Human Activity Recognition Challenge by Md Atiqur Rahman Ahad,Paula Lago,Sozo Inoue Pdf

The book introduces some challenging methods and solutions to solve the human activity recognition challenge. This book highlights the challenge that will lead the researchers in academia and industry to move further related to human activity recognition and behavior analysis, concentrating on cooking challenge. Current activity recognition systems focus on recognizing either the complex label (macro-activity) or the small steps (micro-activities) but their combined recognition is critical for analysis like the challenge proposed in this book. It has 10 chapters from 13 institutes and 8 countries (Japan, USA, Switzerland, France, Slovenia, China, Bangladesh, and Columbia).

Author : Xiaoli Li,Min Wu,Zhenghua Chen,Le Zhang
Publisher : Springer Nature
Page : 139 pages
File Size : 50,8 Mb
Release : 2021-02-17
Category : Computers
ISBN : 9789811605758

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Deep Learning for Human Activity Recognition by Xiaoli Li,Min Wu,Zhenghua Chen,Le Zhang Pdf

This book constitutes refereed proceedings of the Second International Workshop on Deep Learning for Human Activity Recognition, DL-HAR 2020, held in conjunction with IJCAI-PRICAI 2020, in Kyoto, Japan, in January 2021. Due to the COVID-19 pandemic the workshop was postponed to the year 2021 and held in a virtual format. The 10 presented papers were thorougly reviewed and included in the volume. They present recent research on applications of human activity recognition for various areas such as healthcare services, smart home applications, and more.

Author : Nobuo Kawaguchi,Nobuhiko Nishio,Daniel Roggen,Sozo Inoue,Susanna Pirttikangas,Kristof Van Laerhoven
Publisher : Springer Nature
Page : 250 pages
File Size : 47,9 Mb
Release : 2019-09-09
Category : Computers
ISBN : 9783030130015

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Human Activity Sensing by Nobuo Kawaguchi,Nobuhiko Nishio,Daniel Roggen,Sozo Inoue,Susanna Pirttikangas,Kristof Van Laerhoven Pdf

Activity recognition has emerged as a challenging and high-impact research field, as over the past years smaller and more powerful sensors have been introduced in wide-spread consumer devices. Validation of techniques and algorithms requires large-scale human activity corpuses and improved methods to recognize activities and the contexts in which they occur. This book deals with the challenges of designing valid and reproducible experiments, running large-scale dataset collection campaigns, designing activity and context recognition methods that are robust and adaptive, and evaluating activity recognition systems in the real world with real users.

Author : Diane J. Cook,Narayanan C. Krishnan
Publisher : John Wiley & Sons
Page : 288 pages
File Size : 55,9 Mb
Release : 2015-02-19
Category : Technology & Engineering
ISBN : 9781119010241

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Activity Learning by Diane J. Cook,Narayanan C. Krishnan Pdf

Defines the notion of an activity model learned from sensor data and presents key algorithms that form the core of the field Activity Learning: Discovering, Recognizing and Predicting Human Behavior from Sensor Data provides an in-depth look at computational approaches to activity learning from sensor data. Each chapter is constructed to provide practical, step-by-step information on how to analyze and process sensor data. The book discusses techniques for activity learning that include the following: Discovering activity patterns that emerge from behavior-based sensor data Recognizing occurrences of predefined or discovered activities in real time Predicting the occurrences of activities The techniques covered can be applied to numerous fields, including security, telecommunications, healthcare, smart grids, and home automation. An online companion site enables readers to experiment with the techniques described in the book, and to adapt or enhance the techniques for their own use. With an emphasis on computational approaches, Activity Learning: Discovering, Recognizing, and Predicting Human Behavior from Sensor Data provides graduate students and researchers with an algorithmic perspective to activity learning.

Author : Santosh Kumar Tripathy
Publisher : Springer Nature
Page : 145 pages
File Size : 49,6 Mb
Release : 2024-06-13
Category : Electronic
ISBN : 9783031516603

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Advances in Human Activity Detection and Recognition (HADR) Systems by Santosh Kumar Tripathy Pdf

Author : Ainhoa Berciano,Daniel Díaz-Pernil,Pedro Real,Walter Kropatsch,Helena Molina-Abril
Publisher : Springer Science & Business Media
Page : 631 pages
File Size : 48,7 Mb
Release : 2011-08-19
Category : Computers
ISBN : 9783642236716

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Computer Analysis of Images and Patterns by Ainhoa Berciano,Daniel Díaz-Pernil,Pedro Real,Walter Kropatsch,Helena Molina-Abril Pdf

The two volume set LNCS 6854/6855 constitutes the refereed proceedings of the International Conference on Computer Analysis of Images and Patterns, CAIP 2011, which took place in Seville, Spain, August 29-31, 2011. The 138 papers presented together with 2 invited talks were carefully reviewed and selected from 286 submissions. The papers are organized in topical section on: motion analysis, image and shape models, segmentation and grouping, shape recovery, kernel methods, medical imaging, structural pattern recognition, Biometrics, image and video processing, calibration; and tracking and stereo vision.

Author : Joy Iong-Zong Chen,João Manuel R. S. Tavares,Subarna Shakya,Abdullah M. Iliyasu
Publisher : Springer Nature
Page : 829 pages
File Size : 53,5 Mb
Release : 2020-07-23
Category : Technology & Engineering
ISBN : 9783030518592

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Image Processing and Capsule Networks by Joy Iong-Zong Chen,João Manuel R. S. Tavares,Subarna Shakya,Abdullah M. Iliyasu Pdf

This book emphasizes the emerging building block of image processing domain, which is known as capsule networks for performing deep image recognition and processing for next-generation imaging science. Recent years have witnessed the continuous development of technologies and methodologies related to image processing, analysis and 3D modeling which have been implemented in the field of computer and image vision. The significant development of these technologies has led to an efficient solution called capsule networks [CapsNet] to solve the intricate challenges in recognizing complex image poses, visual tasks, and object deformation. Moreover, the breakneck growth of computation complexities and computing efficiency has initiated the significant developments of the effective and sophisticated capsule network algorithms and artificial intelligence [AI] tools into existence. The main contribution of this book is to explain and summarize the significant state-of-the-art research advances in the areas of capsule network [CapsNet] algorithms and architectures with real-time implications in the areas of image detection, remote sensing, biomedical image analysis, computer communications, machine vision, Internet of things, and data analytics techniques.

Author : Anandakumar Haldorai
Publisher : Springer Nature
Page : 492 pages
File Size : 47,6 Mb
Release : 2024-06-13
Category : Electronic
ISBN : 9783031539725

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Artificial Intelligence for Sustainable Development by Anandakumar Haldorai Pdf