Group Behavior Recognition using Dynamic Bayesian Networks: Understanding intentions, goals and actions that take place inside teams - Tapa blanda

Gaitanis, Konstantinos D.

 
9783639126570: Group Behavior Recognition using Dynamic Bayesian Networks: Understanding intentions, goals and actions that take place inside teams
Tapa blanda
ISBN 10: 3639126572 ISBN 13: 9783639126570
Editorial: VDM Verlag Dr. Müller, 2009

Sinopsis

In this PhD thesis we analyze the concepts involved in the decision making of groups of agents and apply these concepts in creating a framework for performing group behavior recognition. We present an overview of the intention theory, as studied by some great theorists such as Searle, Bratmann and Cohen, and show the link with more recent researches. We study the advantages and drawbacks of some techniques in the domain and create a new model for representing and detecting group behaviors, the aim being to create a unified approach of the problem. Most of this thesis is consecrated in the detailed presentation of the model as well as the algorithm responsible for behavior recognition. Our model is tested on two different applications involving human gesture analysis and multimodal fusion of audio and video data. By means of these applications, we advance the argument that multivariate sets of correlated data can be efficiently analyzed under a unified framework of behavior recognition. We show that the correlation between different sets of data can be modeled as cooperation inside a team and that behavior recognition is a modern approach of classification and pattern recognition.

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

In this PhD thesis we analyze the concepts involved in the decision making of groups of agents and apply these concepts in creating a framework for performing group behavior recognition. We present an overview of the intention theory, as studied by some great theorists such as Searle, Bratmann and Cohen, and show the link with more recent researches. We study the advantages and drawbacks of some techniques in the domain and create a new model for representing and detecting group behaviors, the aim being to create a unified approach of the problem. Most of this thesis is consecrated in the detailed presentation of the model as well as the algorithm responsible for behavior recognition. Our model is tested on two different applications involving human gesture analysis and multimodal fusion of audio and video data. By means of these applications, we advance the argument that multivariate sets of correlated data can be efficiently analyzed under a unified framework of behavior recognition. We show that the correlation between different sets of data can be modeled as cooperation inside a team and that behavior recognition is a modern approach of classification and pattern recognition.

Biografía del autor

was born in Athens in 1981. He received his Engineering degree in 2004 and his PhD degree in 2007. Instead of spending most of his time in research, he is actively implied in ecology, self-construction using cob, cycling, renovative economical theories, strange musical instruments, martial arts and mostly, being in nature...

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
VDM Verlag Dr. Müller
Año de publicación
2009
Idioma
Inglés
ISBN 10 
3639126572
ISBN 13 
9783639126570
Encuadernación
Tapa blanda
Número de páginas
188
Contacto del fabricante
no disponible
Persona responsable
no disponible