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Multimedia Data Mining and Analysis from Motion Contents: Effective Techniques for Managing Motional Multimedia Data - Tapa blanda

Zhou, Yue

 
9783639102802: Multimedia Data Mining and Analysis from Motion Contents: Effective Techniques for Managing Motional Multimedia Data
Tapa blanda
ISBN 10: 3639102800 ISBN 13: 9783639102802
Editorial: VDM Verlag Dr. Müller, 2008

Sinopsis

Object motion in multimedia database contains important information for data content analysis especially event detection. The motion content in its raw form is real-value multidimensional time series. Processing and analyzing this kind of data is not trivial since most standard machine learning algorithms can only be applied to data in vector space. In this work, we explore the techniques to solve three problems related to motion cues in multimedia databases: object motion estimation, motion representation, and motion analysis to recognize activities and events. In this book we first discuss our work on object detection and tracking, which estimate the object motion. We then introduce our edit distance based approach to measure the similarity between motion trajectories in its raw form. We also present our work on a novel trajectory representation framework, "bag of segments," by which trajectories are transformed to a frequency in vector space so that most traditional machine learning algorithms can be directly applied to the motion trajectory data. Finally, we introduce our work on using the Granger causality test to analyze multi-object interactions from motion.

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Reseña del editor

Object motion in multimedia database contains important information for data content analysis especially event detection. The motion content in its raw form is real-value multidimensional time series. Processing and analyzing this kind of data is not trivial since most standard machine learning algorithms can only be applied to data in vector space. In this work, we explore the techniques to solve three problems related to motion cues in multimedia databases: object motion estimation, motion representation, and motion analysis to recognize activities and events. In this book we first discuss our work on object detection and tracking, which estimate the object motion. We then introduce our edit distance based approach to measure the similarity between motion trajectories in its raw form. We also present our work on a novel trajectory representation framework, "bag of segments," by which trajectories are transformed to a frequency in vector space so that most traditional machine learning algorithms can be directly applied to the motion trajectory data. Finally, we introduce our work on using the Granger causality test to analyze multi-object interactions from motion.

Biografía del autor

Yue Zhou is currently a member of research staff in Microsoft Corporation. His research focuses on data mining and machine learning technology for large scale databases including multimedia databases. He received his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana- Champaign in 2008.

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Editorial
VDM Verlag Dr. Müller
Año de publicación
2008
Idioma
Inglés
ISBN 10 
3639102800
ISBN 13 
9783639102802
Encuadernación
Tapa blanda
Número de páginas
136
Contacto del fabricante
no disponible
Persona responsable
no disponible