NitroFlare Human Activity Recognition and Prediction

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    Human Activity Recognition and Prediction
    Springer | Signals & Communication | January 20, 2016 | ISBN-10: 3319270028 | 174 pages | pdf | 5.6 mb

    by Yun Fu (Editor)
    Covers the most state-of-the-art topics of activity recognition and prediction
    Discusses both methodology and real-world practice of human activity recognition
    Contains contributions from top experts in the field, who voice their unique perspectives included throughout


    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.

    Number of Illustrations and Tables
    64 illus., 6 in colour
    Topics
    Signal, Image and Speech Processing
    Image Processing and Computer Vision
    Biometrics

    More info and Hardcover at Springer

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