Object Identification and Categorization with Visual Context: Hierarchical Graphical Model-based Approaches - Couverture souple

Kim, Sungho; So Kweon, In

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

Synopsis

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.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

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.

Biographie de l'auteur

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.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
VDM Verlag Dr. Müller
Date d'édition
2008
Langue
anglais
ISBN 10 
3639010337
ISBN 13 
9783639010336
Reliure
Broché
Nombre de pages
208
Coordonnées du fabricant
non disponible
Personne responsable
non disponible