learning structured data human di thi tuan (9 risultati)

Condizione: New.

Taschenbuch. Condizione: Neu. Learning Structured Data for Human Action Analysis | A unified approach for visual pattern recognition | Tuan Hue Thi | Taschenbuch | 228 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846548332 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Paperback. Condizione: Brand New. 228 pages. 8.66x5.91x0.52 inches. In Stock.

Taschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a unified solution to the challenging problem of human action analysis in video. 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 that the structured learning of local features is an effective potential approach for the task of analysing human action. It helps not only to create a significant bridge between traditional approaches of local and global features, but also to provide a foundational guideline for future work in this direction. Many other potential applications in visual pattern recognition can also be developed using the frameworks developed in this book. 228 pp. Englisch.

Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Thi Tuan HueDr. Tuan Hue Thi obtained his PhD. from the University of New South Wales, Australia. His research interests include pattern recognition, computer vision and human behaviour analysis. His current works involve building sm.

Condizione: New. Print on Demand.

Condizione: New. PRINT ON DEMAND.

Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents a unified solution to the challenging problem of human action analysis in video. 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 that the structured learning of local features is an effective potential approach for the task of analysing human action. It helps not only to create a significant bridge between traditional approaches of local and global features, but also to provide a foundational guideline for future work in this direction. Many other potential applications in visual pattern recognition can also be developed using the frameworks developed in this book.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 228 pp. Englisch.

Taschenbuch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents a unified solution to the challenging problem of human action analysis in video. 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 that the structured learning of local features is an effective potential approach for the task of analysing human action. It helps not only to create a significant bridge between traditional approaches of local and global features, but also to provide a foundational guideline for future work in this direction. Many other potential applications in visual pattern recognition can also be developed using the frameworks developed in this book.