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Human Action Analysis with Randomized Trees

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Human Action Analysis with Randomized Trees/ by Gang Yu, Junsong Yuan, Zicheng Liu.
Author:	Yu, Gang.
other author:	Yuan, Junsong.
Description:	VIII, 83 p. 30 illus. in color.online resource. :
Contained By:	Springer Nature eBook
Subject:	Signal processing. -
Online resource:	https://doi.org/10.1007/978-981-287-167-1
ISBN:	9789812871671

Human Action Analysis with Randomized Trees
Yu, Gang.

Human Action Analysis with Randomized Trees[electronic resource] /by Gang Yu, Junsong Yuan, Zicheng Liu. - 1st ed. 2015. - VIII, 83 p. 30 illus. in color.online resource. - SpringerBriefs in Signal Processing,2196-4076. - SpringerBriefs in 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

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

561459
Signal processing.

LC Class. No.: TK5102.9

Dewey Class. No.: 621.382

Human Action Analysis with Randomized Trees
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