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Human activity recognition and predi...

Fu, Yun.

Human activity recognition and prediction

Record Type:	Electronic resources : Monograph/item
Title/Author:	Human activity recognition and predictionedited by Yun Fu.
other author:	Fu, Yun.
Published:	Cham :Springer International Publishing :2016.
Description:	vii, 174 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Machine learning.
Online resource:	http://dx.doi.org/10.1007/978-3-319-27004-3
ISBN:	9783319270043$q(electronic bk.)

Human activity recognition and prediction
Human activity recognition and prediction[electronic resource] /edited by Yun Fu. - Cham :Springer International Publishing :2016. - vii, 174 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9783319270043$q(electronic bk.)

Standard No.: 10.1007/978-3-319-27004-3doiSubjects--Topical Terms:

188639
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Human activity recognition and prediction
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245 0 0 $a Human activity recognition and prediction $h [electronic resource] / $c edited by Yun Fu.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2016.
300 $a vii, 174 p. : $b ill., digital ; $c 24 cm.
505 0 $a 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.
520 $a 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.
650 0 $a Machine learning. $3 188639
650 0 $a Human-computer interaction. $3 189333
650 1 4 $a Engineering. $3 210888
650 2 4 $a Signal, Image and Speech Processing. $3 273768
650 2 4 $a Image Processing and Computer Vision. $3 274051
650 2 4 $a Biometrics. $3 274525
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