國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Human activity recognition and predi...

Fu, Yun.

Human activity recognition and prediction

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Human activity recognition and predictionedited 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$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
LDR:02186nmm a2200337 a 4500 001 482386
003 DE-He213
005 20160808161257.0
006 m d
007 cr nn 008maaau
008 161007s2016 gw s 0 eng d
020 $a 9783319270043$q(electronic bk.)
020 $a 9783319270029$q(paper)
024 7 $a 10.1007/978-3-319-27004-3 $2 doi
035 $a 978-3-319-27004-3
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5
072 7 $a TTBM $2 bicssc
072 7 $a UYS $2 bicssc
072 7 $a TEC008000 $2 bisacsh
072 7 $a COM073000 $2 bisacsh
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .H918 2016
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
700 1 $a Fu, Yun. $3 679555
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-27004-3
950 $a Engineering (Springer-11647)