國立虎尾科技大學 |

Human activity recognition and prediction

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Human activity recognition and prediction/ edited by Yun Fu.
其他作者:	Fu, Yun.
出版者:	Cham :Springer International Publishing : : 2016.,
面頁冊數:	vii, 174 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Machine learning. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-27004-3
ISBN:	9783319270043

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

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

561253
Machine learning.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Human activity recognition and prediction
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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.
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