Learning Structured Data for Human Action Analysis

Author: Tuan Hue Thi
Edition:
Binding: Paperback
ISBN: 3846548332

Learning Structured Data for Human Action Analysis: A unified approach for visual pattern recognition

This book presents a unified solution to the challenging problem of human action analysis in video. Get Learning Structured Data for Human Action Analysis computer books for free.
Human action is represented as a structured set of local features so that different structured learning models can be applied to classify and localise action instances in video databases. A wide range of factors for a good human action analysis is also analysed. At the feature level, different detectors, descriptors and selectors will be employed, while at the learning level, different types of models will be proposed and described. Lastly, at the evaluation level, a few different datasets will be used to analyse the applicability of each structured learning model under different test scenarios. The analysis obtained from this work has confirmed Check Learning Structured Data for Human Action Analysis our best computer books for 2013. All books are available in pdf format and downloadable from rapidshare, 4shared, and mediafire.

Learning Structured Data for Human Action Analysis Download

Human action is represented as a structured set of local features so that different structured learning models can be applied to classify and localise action instances in video databases. A wide range of factors for a good human action analysis is also analysed. At the feature level, different detectors, descriptors and selectors will be employed, while at the learning level, different types of models will be proposed and described. Lastly, at the evaluation level, a few different datasets will be used to analyse the applicability of each structured learning model under different test scenarios uman action is represented as a structured set of local features so that different structured learning models can be applied to classify and localise action instances in video databases. A wide range of factors for a good human action analysis is also analysed. At the feature level, different detectors, descriptors and selectors will be employed, while at the learning level, different types of models will be proposed and described. Lastly, at the evaluation level, a few different datasets will be used to analyse the applicability of each structured learning model under different test scenarios. The analysis obtained from this work has confirmed

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