Human Activity Sensing - Corpus and Applications

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.

List of contents

Optimizing of the Number and Placements of Wearable IMUs for Automatic Rehabilitation Recording.- Identifying Sensors via Statistical Analysis of Body-Worn Inertial Sensor Data.- Compensation Scheme for PDR using Component-wise Error Models.- Towards the Design and Evaluation of Robust Audio-Sensing Systems.- A Wi-Fi Positioning Method Considering Radio Attenuation of Human Body.- Drinking gesture recognition from poorly annotated data: a case study.- Understanding how Non-experts Collect and Annotate Activity Data.- MEASURed: Evaluating Sensor-based Activity Recognition Scenarios by Simulating Accelerometer Measures from Motion Capture.- Benchmark performance for the Sussex-Huawei locomotion and transportation recognition challenge 2018.- Effects of Activity Recognition Window Size and Time Stabilization in the SHL Recognition Challenge.

Summary

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.

Product details

• Assisted by: Sozo Inoue (Editor), Nobuo Kawaguchi (Editor), Kristof van Laerhoven (Editor), Nobuhik Nishio (Editor), Nobuhiko Nishio (Editor), Susanna Pirttikangas (Editor), Daniel Roggen (Editor), Daniel Roggen et al (Editor), Kristof Van Laerhoven (Editor)
• Publisher: Springer, Berlin
• Languages: English
• Product format: Hardback
• Released: 31.08.2019
• EAN: 9783030130008
• ISBN: 978-3-0-3013000-8
• No. of pages: 250
• Dimensions: 158 mm x 243 mm x 21 mm
• Weight: 564 g
• Illustrations: XII, 250 p. 140 illus., 98 illus. in color.
• Series: Springer Series in Adaptive Environments; Springer Series in Adaptive Environments
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > Operating systems, user interfaces; B, Data Mining, computer science, Information Retrieval, Information Systems Applications (incl. Internet), Information Systems Applications (incl.Internet), Application software, Data Mining and Knowledge Discovery, Microprogramming, Control Structures and Microprogramming, Algorithms & data structures, Internet searching, Expert systems / knowledge-based systems, User Interfaces and Human Computer Interaction, User interfaces (Computer systems)