Human Action Analysis with Randomized Trees

  • Gang Yu
  • Junsong Yuan
  • Zicheng Liu

Part of the SpringerBriefs in Electrical and Computer Engineering book series (BRIEFSELECTRIC)

Also part of the SpringerBriefs in Signal Processing book sub series (BRIEFSSIGNAL)

Table of contents

  1. Front Matter
    Pages i-viii
  2. Gang Yu, Junsong Yuan, Zicheng Liu
    Pages 1-8
  3. Gang Yu, Junsong Yuan, Zicheng Liu
    Pages 9-27
  4. Gang Yu, Junsong Yuan, Zicheng Liu
    Pages 29-56
  5. Gang Yu, Junsong Yuan, Zicheng Liu
    Pages 57-72
  6. Gang Yu, Junsong Yuan, Zicheng Liu
    Pages 73-81
  7. Gang Yu, Junsong Yuan, Zicheng Liu
    Pages 83-83

About this book

Introduction

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.

Keywords

Action Categorization Branch-and-bound Hough Voting Human Action Analysis Human Action Localization Human Action Recognition Random Tree Unsupervised Learning

Authors and affiliations

  • Gang Yu
    • 1
  • Junsong Yuan
    • 2
  • Zicheng Liu
    • 3
  1. 1.School of Electrical and Electronic Eng.Nanyang Technological UniversitySingaporeSingapore
  2. 2.School of Electrical and Electronic Eng.Nanyang Technological UniversitySingaporeSingapore
  3. 3.Microsoft ResearchRedmondUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-981-287-167-1
  • Copyright Information The Author(s) 2015
  • Publisher Name Springer, Singapore
  • eBook Packages Engineering
  • Print ISBN 978-981-287-166-4
  • Online ISBN 978-981-287-167-1
  • Series Print ISSN 2191-8112
  • Series Online ISSN 2191-8120
  • About this book
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