Please use this identifier to cite or link to this item: http://dl.pgu.ac.ir/handle/Hannan/7082
Title: Human Action Analysis with Randomized Trees
Authors: Yu, Gang
Yuan, Junsong
Liu, Zicheng
Keywords: Engineering;Computer vision;Distribution (Probability theory);Engineering;Signal, Image and Speech Processing;Image Processing and Computer Vision;Probability Theory and Stochastic Processes;621.382 23;TK7882.S65
Issue Date: 2015
Publisher: Springer Singapore;Imprint Springer,
place: Singapore
Series/Report no.: SpringerBriefs in Electrical and Computer Engineering,;2191-8112.;SpringerBriefs in Electrical and Computer Engineering,;2191-8112.
Abstract: 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.
Description: Printed edition:;9789812871664.
Table Of Contents: 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.
URI: http://dl.pgu.ac.ir/handle/Hannan/7082
ISBN: 9789812871671
9789812871664 (print)
Format: [electronic resource] /
Type Of Material: Book
Appears in Collections:Electronics

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