Object Identification and Categorization with Visual Context: Hierarchical Graphical Model-based Approaches - Tapa blanda

Kim, Sungho; So Kweon, In

 
9783639010336: Object Identification and Categorization with Visual Context: Hierarchical Graphical Model-based Approaches
Tapa blanda
ISBN 10: 3639010337 ISBN 13: 9783639010336
Editorial: VDM Verlag Dr. Müller, 2008

Sinopsis

The goal of object recognition is to label objects from images and to estimate the poses of the labeled objects. The field of object recognition has seen tremendous progress with successful applications in some specific domains such as face recognition. However, the current state-of-the-art methods show unsatisfactory results for more general object domains in complex natural environments with visual ambiguities. In this dissertation, we aim to enhance the object identification and categorization with theguide of visual context and graphical model. In this work, we propose a general framework for the cooperative object identification and object categorization. Examplars used in identification provide useful information of similarity in categorization. Conversely, novel objects are rejected in identification but the proposed object categorization can label the novel objects and segment them out for database update in identification. This work can be helpful to the engineers in artificial intelligence and machine vision.

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Reseña del editor

The goal of object recognition is to label objects from images and to estimate the poses of the labeled objects. The field of object recognition has seen tremendous progress with successful applications in some specific domains such as face recognition. However, the current state-of-the-art methods show unsatisfactory results for more general object domains in complex natural environments with visual ambiguities. In this dissertation, we aim to enhance the object identification and categorization with theguide of visual context and graphical model. In this work, we propose a general framework for the cooperative object identification and object categorization. Examplars used in identification provide useful information of similarity in categorization. Conversely, novel objects are rejected in identification but the proposed object categorization can label the novel objects and segment them out for database update in identification. This work can be helpful to the engineers in artificial intelligence and machine vision.

Biografía del autor

Sungho Kim#201 111-7, Eoeun-dong Yuseong-gu, Daejeon, Korea, 305-333Senior Researcher at the Agency for Defense Development, 2007~Current.Korea Advanced Institute of Science and Technology (KAIST), Ph.D. Degree, 2007.Korea Advanced Institute of Science and Technology (KAIST), M.S., 2002.Korea University, B.S., 2000.

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Editorial
VDM Verlag Dr. Müller
Año de publicación
2008
Idioma
Inglés
ISBN 10 
3639010337
ISBN 13 
9783639010336
Encuadernación
Tapa blanda
Número de páginas
208
Contacto del fabricante
no disponible
Persona responsable
no disponible