Human Activity Recognition and Prediction
Yun Fu (Hrsg.)
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Springer International Publishing
Naturwissenschaften, Medizin, Informatik, Technik / Elektronik, Elektrotechnik, Nachrichtentechnik
Beschreibung
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.
Kundenbewertungen
Transfer Learning, Pattern Recognition, Computer Vision, Actionlets, Machine Learning, Human Interaction, Action Prediction, Action Recognition, Activity Recognition, Discriminative Model, Activity Prediction, RGB-D