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...
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2015
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oai:scholar.dlu.edu.vn:DLU123456789-578912023-11-11T05:56:33Z Human Action Analysis with Randomized Trees Yu, Gang Yuan, Junsong Liu, Zicheng General Mathematics Research Human behavior 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 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. 2015-09-01T02:04:29Z 2015-09-01T02:04:29Z 2015 Book 978-981-287-167-1 https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/57891 en application/pdf Springer |
| institution |
Thư viện Trường Đại học Đà Lạt |
| collection |
Thư viện số |
| language |
English |
| topic |
General Mathematics Research Human behavior Trees |
| spellingShingle |
General Mathematics Research Human behavior Trees Yu, Gang Yuan, Junsong Liu, Zicheng Human Action Analysis with Randomized Trees |
| description |
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. |
| format |
Book |
| author |
Yu, Gang Yuan, Junsong Liu, Zicheng |
| author_facet |
Yu, Gang Yuan, Junsong Liu, Zicheng |
| author_sort |
Yu, Gang |
| title |
Human Action Analysis with Randomized Trees |
| title_short |
Human Action Analysis with Randomized Trees |
| title_full |
Human Action Analysis with Randomized Trees |
| title_fullStr |
Human Action Analysis with Randomized Trees |
| title_full_unstemmed |
Human Action Analysis with Randomized Trees |
| title_sort |
human action analysis with randomized trees |
| publisher |
Springer |
| publishDate |
2015 |
| url |
https://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/57891 |
| _version_ |
1819780246721789952 |