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Human Activity Recognition and Prediction / / edited by Yun Fu



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Titolo: Human Activity Recognition and Prediction / / edited by Yun Fu Visualizza cluster
Pubblicazione: Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Edizione: 1st ed. 2016.
Descrizione fisica: 1 online resource (179 p.)
Disciplina: 620
Soggetto topico: Signal processing
Image processing
Speech processing systems
Optical data processing
Biometrics (Biology)
Signal, Image and Speech Processing
Image Processing and Computer Vision
Biometrics
Persona (resp. second.): FuYun
Note generali: Description based upon print version of record.
Nota di bibliografia: Includes bibliographical references at the end of each chapters.
Nota di contenuto: 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.
Sommario/riassunto: 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. .
Titolo autorizzato: Human Activity Recognition and Prediction  Visualizza cluster
ISBN: 3-319-27004-4
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910254204703321
Lo trovi qui: Univ. Federico II
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