Human Action Analysis with Randomized Trees
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...
Main Authors: | , , |
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Format: | eBook |
Language: | English |
Published: |
Singapore
Springer Nature Singapore
2015, 2015
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Edition: | 1st ed. 2015 |
Series: | SpringerBriefs in Signal Processing
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Subjects: | |
Online Access: | |
Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Summary: | 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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Physical Description: | VIII, 83 p. 30 illus. in color online resource |
ISBN: | 9789812871671 |