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Értesítés a kedvenc témákról
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Human Activity and Behavior Analysis

Advances in Computer Vision and Sensors: Volume 2
 
Kiadás sorszáma: 1
Kiadó: CRC Press
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Rövid leírás:

Human Activity and Behavior Analysis relates to the field of vision and sensor-based human action or activity and behavior analysis and recognition. The book includes a series of methodologies, surveys, relevant datasets, challenging applications, ideas, and future prospects.

Hosszú leírás:

Human Activity and Behavior Analysis relates to the field of vision and sensor-based human action or activity and behavior analysis and recognition. The book includes a series of methodologies, surveys, relevant datasets, challenging applications, ideas, and future prospects.


The book discusses topics such as action recognition, action understanding, gait analysis, gesture recognition, behavior analysis, emotion and affective computing, and related areas. This volume focuses on two main subject areas: Movement and Sensors, and Sports Activity Analysis.


The editors are experts in these arenas, and the contributing authors are drawn from high-impact research groups around the world. This book will be of great interest to academics, students, and professionals working and researching in the field of human activity and behavior analysis.

Tartalomjegyzék:

Preface Movement and Sensors1.  Testing the Applicability of Virtual Stochastic Sensors in Human Activity Recognition Claudia Krull, Pascal Krenckel, and Lauro Fialho Mu¨ Ller.2. Static Sign Language Recognition Using Segmented Images and HOG on Cluttered Backgrounds Arezoo Sadeghzadeh, Md Baharul Islam, and Md Atiqur Rahman Ahad. 3. (k,n)-Threshold Encoding Scheme for RFID-based Real-Time Event Extraction and Its Application to ADL Recognition Masayuki Numao and Ryota Fukumoto. 4. A CSI-based Human Activity Recognition using Canny Edge Detector Hossein Shahverdi, Parisa Fard Moshiri, Mohammad Nabati, Reza Asvadi, and Seyed Ali Ghorashi. 5. Function Estimation of Multiple IoT Devices by Communication Traffic Analysis Yuichi Hattori, Yutaka Arakawa, and Sozo Inoue. 6. A Method for Estimating the Number of Steps Taken Using a BLE Beacon Attached to the Soles of Footwear Yuki Ogane, Yu Enokibori, and Katsuhiko Kaji. 7. A Method for Estimating Upper-Arm Muscle Activities and sEMG with PPG Sensor Masahiro Okamoto and Kazuya Murao. 8. Development of Automatic Posture and Stumbling Judgement System using Deep Learning, Jetson Nano and Drone with Information-Sharing Function Shinji Kawakura, Masayuki Hirafuji, and Ryosuke Shibasaki. 9. Gait condition assessment methods for visualizing interventional expertise by means of posture detection Akinori Kunishima, Koki Suzuki, Atsushi Omata, Shogo Ishikawa, and Shinya Kiriyama. 10. Psychological Analysis in Human-Robot Collaboration from Workplace Stress Factors: A Review Nazmun Nahid, Min Xinyi, Md Atiqur Rahman Ahad, and Sozo Inoue. Sports Activity Analysis. 11. Real-Time Feedback System for Efficient Core Training Keisuke Sato, Ami Jinno, Nishiki Motokawa, Tahera Hossain, Anna Yokokubo, and Guillaume Lopez.12. Keeping athletes motivated by realtime co-running application Shun Ishii, Kazuki Imura, Tahera Hossain, Anna Yokokubo, and Guillaume Lopez. 13. Boxing movements recognition using IMUs during shadow boxing exercise Yoshinori Hanada, Tahera Hossain, Anna Yokokubo, and Guillaume Lopez. 14. FootbSense: Soccer Moves in Practice Environment Identification Using a Single IMU Hikari Aoyagi, Tahera Hossain, Anna Yokokubo, and Guillaume Lopez.