Human activity recognition and prediction
著者
書誌事項
Human activity recognition and prediction
Springer, c2016
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注記
Includes bibliographical references
内容説明・目次
内容説明
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.
目次
Introduction.- Action and Activities.- Action Recognition and Human Interaction.- Multimodal Action Recognition.- RGB-D Action Recognition.- Actionlets and Activity Prediction.- Time Series Modeling for Activity Prediction.- RGB-D Action Prediction.
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