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Human action analysis with randomize...

Yu, Gang.

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Human action analysis with randomized trees

Record Type:	Electronic resources : Monograph/item
Title/Author:	Human action analysis with randomized trees/ by Gang Yu, Junsong Yuan, Zicheng Liu.
Author:	Yu, Gang.
other author:	Yuan, Junsong.
Published:	Singapore :Springer Singapore : : 2015.,
Description:	viii, 83 p. :ill., digital ;24 cm.
[NT 15003449]:	Introduction to Human Action Analysis -- Supervised Trees for Human Action Recognition and Detection -- Unsupervised Trees for Human Action Search -- Propagative Hough Voting to Leverage Contextual Information -- Human Action Prediction with Multi-class Balanced Random Forest -- Conclusion.
Contained By:	Springer eBooks
Subject:	Trees (Graph theory) -
Online resource:	http://dx.doi.org/10.1007/978-981-287-167-1
ISBN:	9789812871671 (electronic bk.)

Human action analysis with randomized trees
Yu, Gang.

Human action analysis with randomized trees[electronic resource] /by Gang Yu, Junsong Yuan, Zicheng Liu. - Singapore :Springer Singapore :2015. - viii, 83 p. :ill., digital ;24 cm. - Springer briefs in electrical and computer engineering. Signal processing,2191-8112. - Springer briefs in electrical and computer engineering.Signal processing..

Introduction to Human Action Analysis -- Supervised Trees for Human Action Recognition and Detection -- Unsupervised Trees for Human Action Search -- Propagative Hough Voting to Leverage Contextual Information -- Human Action Prediction with Multi-class Balanced Random Forest -- Conclusion.

This book will provide a comprehensive overview on human action analysis with randomized trees. It will cover both the supervised random trees and the unsupervised random trees. When there are sufficient amount of labeled data available, supervised random trees provides a fast method for space-time interest point matching. When labeled data is minimal as in the case of example-based action search, unsupervised random trees is used to leverage the unlabelled data. We describe how the randomized trees can be used for action classification, action detection, action search, and action prediction. We will also describe techniques for space-time action localization including branch-and-bound sub-volume search and propagative Hough voting.

ISBN: 9789812871671 (electronic bk.)

Standard No.: 10.1007/978-981-287-167-1doiSubjects--Topical Terms:

648365
Trees (Graph theory)

LC Class. No.: QA166.2

Dewey Class. No.: 511.52

Human action analysis with randomized trees
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245 1 0 $a Human action analysis with randomized trees $h [electronic resource] / $c by Gang Yu, Junsong Yuan, Zicheng Liu.
260 $a Singapore : $b Springer Singapore : $b Imprint: Springer, $c 2015.
300 $a viii, 83 p. : $b ill., digital ; $c 24 cm.
490 1 $a Springer briefs in electrical and computer engineering. Signal processing, $x 2191-8112
505 0 $a Introduction to Human Action Analysis -- Supervised Trees for Human Action Recognition and Detection -- Unsupervised Trees for Human Action Search -- Propagative Hough Voting to Leverage Contextual Information -- Human Action Prediction with Multi-class Balanced Random Forest -- Conclusion.
520 $a This book will provide a comprehensive overview on human action analysis with randomized trees. It will cover both the supervised random trees and the unsupervised random trees. When there are sufficient amount of labeled data available, supervised random trees provides a fast method for space-time interest point matching. When labeled data is minimal as in the case of example-based action search, unsupervised random trees is used to leverage the unlabelled data. We describe how the randomized trees can be used for action classification, action detection, action search, and action prediction. We will also describe techniques for space-time action localization including branch-and-bound sub-volume search and propagative Hough voting.
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650 0 $a Human behavior $x Research. $3 2048631
650 1 4 $a Engineering. $3 586835
650 2 4 $a Signal, Image and Speech Processing. $3 891073
650 2 4 $a Image Processing and Computer Vision. $3 891070
650 2 4 $a Probability Theory and Stochastic Processes. $3 891080
700 1 $a Yuan, Junsong. $3 2132765
700 1 $a Liu, Zicheng. $3 2058108
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830 0 $a Springer briefs in electrical and computer engineering. $p Signal processing. $3 2132766
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