Human Action Analysis with Randomized Trees

Gang Yu, Zicheng Liu, Junsong Yuan, et al.

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ca. 53,49

Springer Singapore img Link Publisher

Naturwissenschaften, Medizin, Informatik, Technik / Elektronik, Elektrotechnik, Nachrichtentechnik

Beschreibung

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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Schlagwörter

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