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On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities: 11 (Studies in Systems, Decision and Control, 11) - Softcover
Synopsis
In many computer vision applications, objects have to be learned and recognized in images or image sequences. This book presents new probabilistic hierarchical models that allow an efficient representation of multiple objects of different categories, scales, rotations, and views. The idea is to exploit similarities between objects and object parts in order to share calculations and avoid redundant information. Furthermore inference approaches for fast and robust detection are presented. These new approaches combine the idea of compositional and similarity hierarchies and overcome limitations of previous methods. Besides classical object recognition the book shows the use for detection of human poses in a project for gait analysis. The use of activity detection is presented for the design of environments for ageing, to identify activities and behavior patterns in smart homes. In a presented project for parking spot detection using an intelligent vehicle, the proposed approaches are used to hierarchically model the environment of the vehicle for an efficient and robust interpretation of the scene in real-time.
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From the Back Cover
In many computer vision applications, objects have to be learned and recognized in images or image sequences. This book presents new probabilistic hierarchical models that allow an efficient representation of multiple objects of different categories, scales, rotations, and views. The idea is to exploit similarities between objects and object parts in order to share calculations and avoid redundant information. Furthermore inference approaches for fast and robust detection are presented. These new approaches combine the idea of compositional and similarity hierarchies and overcome limitations of previous methods. Besides classical object recognition the book shows the use for detection of human poses in a project for gait analysis. The use of activity detection is presented for the design of environments for ageing, to identify activities and behavior patterns in smart homes. In a presented project for parking spot detection using an intelligent vehicle, the proposed approaches are used to hierarchically model the environment of the vehicle for an efficient and robust interpretation of the scene in real-time.
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On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities (Studies in Systems, Decision and Control, 11)
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On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities (Studies in Systems, Decision and Control)
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On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides important basic concepts, efficient methods as well as practical how-to examples for the use of hierarchical graphical modelsDiscusses the importance and the relationship between sharing and similarity of objects and object parts for ef. Seller Inventory # 448747087
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On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In many computer vision applications, objects have to be learned and recognized in images or image sequences. This book presents new probabilistic hierarchical models that allow an efficient representation of multiple objects of different categories, scales, rotations, and views. The idea is to exploit similarities between objects and object parts in order to share calculations and avoid redundant information. Furthermore inference approaches for fast and robust detection are presented. These new approaches combine the idea of compositional and similarity hierarchies and overcome limitations of previous methods. Besides classical object recognition the book shows the use for detection of human poses in a project for gait analysis. The use of activity detection is presented for the design of environments for ageing, to identify activities and behavior patterns in smart homes. In a presented project for parking spot detection using an intelligent vehicle, the proposed approaches are used to hierarchically model the environment of the vehicle for an efficient and robust interpretation of the scene in real-time. 216 pp. Englisch. Seller Inventory # 9783319358628
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On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities
Published by
Springer International Publishing, 2016
ISBN 10: 3319358626
ISBN 13: 9783319358628
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - In many computer vision applications, objects have to be learned and recognized in images or image sequences. This book presents new probabilistic hierarchical models that allow an efficient representation of multiple objects of different categories, scales, rotations, and views. The idea is to exploit similarities between objects and object parts in order to share calculations and avoid redundant information. Furthermore inference approaches for fast and robust detection are presented. These new approaches combine the idea of compositional and similarity hierarchies and overcome limitations of previous methods. Besides classical object recognition the book shows the use for detection of human poses in a project for gait analysis. The use of activity detection is presented for the design of environments for ageing, to identify activities and behavior patterns in smart homes. In a presented project for parking spot detection using an intelligent vehicle, the proposed approaches are used to hierarchically model the environment of the vehicle for an efficient and robust interpretation of the scene in real-time. Seller Inventory # 9783319358628
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On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities
ISBN 10: 3319358626
ISBN 13: 9783319358628
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Taschenbuch. Condition: Neu. Neuware -In many computer vision applications, objects have to be learned and recognized in images or image sequences. This book presents new probabilistic hierarchical models that allow an efficient representation of multiple objects of different categories, scales, rotations, and views. The idea is to exploit similarities between objects and object parts in order to share calculations and avoid redundant information. Furthermore inference approaches for fast and robust detection are presented. These new approaches combine the idea of compositional and similarity hierarchies and overcome limitations of previous methods. Besides classical object recognition the book shows the use for detection of human poses in a project for gait analysis. The use of activity detection is presented for the design of environments for ageing, to identify activities and behavior patterns in smart homes. In a presented project for parking spot detection using an intelligent vehicle, the proposed approaches are used to hierarchically model the environment of the vehicle for an efficient and robust interpretation of the scene in real-time.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 216 pp. Englisch. Seller Inventory # 9783319358628
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On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities (Studies in Systems, Decision and Control)
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On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities (Studies in Systems, Decision and Control)
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On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities
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On Hierarchical Models for Visual Recognition and Learning of Objects, Scenes, and Activities (Studies in Systems, Decision and Control)
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