Sensor- and Video-Based Activity and Behavior Computing / Smart Innovation, Systems and Technologies Bd.291 (PDF)
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This book presents the best-selected research papers presented at the 3rd International Conference on Activity and Behavior Computing (ABC 2021), during 20-22 October 2021. The book includes works related to the field of vision- and sensor-based human action or activity and behavior analysis and recognition. It covers human activity recognition (HAR), action understanding, gait analysis, gesture recognition, behavior analysis, emotion, and affective computing, and related areas. The book addresses various challenges and aspects of human activity recognition-both in sensor-based and vision-based domains. It can be considered as an excellent treasury related to the human activity and behavior computing.
Sozo Inoue, Ph.D., is Professor in Kyushu Institute of Technology, Japan. His research interests include human activity recognition with smart phones, and healthcare application of Web/pervasive/ubiquitous systems. Currently he is working on verification studies in real field applications, and collecting and providing a large-scale open dataset for activity recognition, such as a mobile accelerator dataset with about 35,000 activity data from more than 200 subjects, nurses' sensor data combined with 100 patients' sensor data and medical records, and 34 households' light sensor data set for 4 months combined with smart meter data. Inoue has a Ph.D. of Engineering from Kyushu University in 2003. After completion of his degree, he was appointed as Assistant Professor in the Faculty of Information Science and Electrical Engineering at the Kyushu University, Japan. He then moved to the Research Department at the Kyushu University Library in 2006. Since 2009, he is appointed as Associate Professor in the Faculty of Engineering at Kyushu Institute of Technology, Japan, and moved to
Daniel Roggen, Ph.D., received the master's and Ph.D. degrees from the École Polytechnique Fédérale de Lausanne, Switzerland, in 2001 and 2005, respectively. He is currently Associate Professor with the Sensor Technology Research Centre, University of Sussex, where he leads the Wearable Technologies Laboratory and directs the Sensor Technology Research Centre. His research focuses on wearable and mobile computing, activity and context recognition, and intelligent embedded systems. He has established a number of recognized data sets for human activity recognition from wearable sensors, in particular the OPPORTUNITY dataset. He is Member of Task Force on Intelligent Cyber-Physical Systems of the IEEE Computational Intelligence Society.
Kaori Fujinami, Ph.D., received his B.S. and M.S. degrees in electrical engineering and his Ph.D. in computer science from Waseda University, Japan, in 1993, 1995, and 2005, respectively. From 1995 to 2003, he worked for Nippon Telegraph and Telephone Corporation (NTT) and NTT Comware Corporation as Software Engineer and Researcher. From 2005 to 2006, he was visiting Lecturer at Waseda University. From 2007 to 2017, he was Associate Professor at the Department of Computer and Information Sciences at Tokyo University of Agriculture and Technology (TUAT). In 2018, he became Professor at TUAT. His research interests are machine learning, activity recognition, human-computer interaction, and ubiquitous computing. He is Member of IPSJ, IEICE, and IEEE.
- 2022, 1st ed. 2022, 264 Seiten, Englisch
- Herausgegeben: Md Atiqur Rahman Ahad, Sozo Inoue, Daniel Roggen, Kaori Fujinami
- Verlag: Springer Nature Singapore
- ISBN-10: 9811903611
- ISBN-13: 9789811903618
- Erscheinungsdatum: 03.05.2022
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- Grösse: 9.02 MB
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