Free Form 3d Object Recognition
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Free Form 3d Object Recognition
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Author :
language : en
Publisher:
Release Date :
Free Form 3d Object Recognition written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
This paper investigates a new approach to the recognition of 3D objects of arbitrary shape. The proposed solution follows the principle of model-based recognition using geometric 3D models and geometric matching. It is an alternative to the classical segmentation and primitive extraction approach and provides a perspective to escape its difficulties to deal with free-form shapes. Using the iterative closest point matching at the heart of the recognition, we propose means to extend its use to the recognition of 3D objects obtained from range data. Examples demonstrate the feasibility of this approach to free-form recognition.
How Well Performs Free Form 3d Object Recognition From Range Images
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Author :
language : en
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How Well Performs Free Form 3d Object Recognition From Range Images written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
This paper investigates the recognition performance of a geometric matching approach to the recognition of free-form objects obtained from range images. The heart of this approach is a closest point matching algorithm which, starting from an initial configuration of two rigid objects, iteratively finds their best correspondence. While the effective performance of this algorithm is known to depend largely on the chosen set of initial configurations, this paper investigates the quantitative nature of this dependence. In essence, we experimentally measure the range of successful configurations for a set of test objects and derive quantitative rules for the recognition strategy. These results show the conditions under which the closest point matching algorithm can be successfully applied to free-form 3D object recognition and help to design a reliable and cost-effective recognition system.
Geometric Matching For Free Form 3d Object Recognition
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Author :
language : en
Publisher:
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Geometric Matching For Free Form 3d Object Recognition written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
This paper investigates a new approach to the recognition of 3D objects of arbitrary shape. The proposed solution follows the principle of model-based recognition using geometric 3D models and geometric matching. It is an alternative to the classical segmentation and primitive extraction approach and provides a perspective to escape the difficulties found with it when dealing with free-form shapes. The heart of this new approach is geometric registration which is performed by a closest point matching algorithm. Reported investigations examine the practical effectiveness of this approach for views obtained from range imaging and address relevant aspects of associated computational costs. The paper proposes solutions allowing to keep track with these costs and presents results assessing the practical feasibility of this approach.
Framework For Representation And Recognition Of 3d Free Form Objects
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Author : Chitra Dorai
language : en
Publisher:
Release Date : 1996
Framework For Representation And Recognition Of 3d Free Form Objects written by Chitra Dorai and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computer vision categories.
3 D Object Recognition Representation And Matching
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Author : International Business Machines Corporation. Research Division
language : en
Publisher:
Release Date : 1998
3 D Object Recognition Representation And Matching written by International Business Machines Corporation. Research Division and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Computer vision categories.
Abstract: "Three-dimensional object recognition problem addresses a number of significant research issues in computer vision: representation of a 3D object, identification of the object, robust estimation of its pose, and registration of multiple views of the object for automatic model construction. This paper surveys the previous work in three important topics of computer vision: representation, matching, and pose estimation of a 3D object. It also presents an overview of the free-form surface matching problem, and describes Cosmos, our framework for representing and recognizing free-form objects. This vision system recognizes arbitrarily curved 3D rigid objects from a single view using dense surface data. We present both the theoretical aspects of this work and the experimental results of a prototype recognition system based on Cosmos."
Representations And Matching Techniques For 3d Free Form Object And Face Recognition
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Author : Ajmal Saeed Mian
language : en
Publisher:
Release Date : 2006
Representations And Matching Techniques For 3d Free Form Object And Face Recognition written by Ajmal Saeed Mian and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Computer vision categories.
[Truncated abstract] The aim of visual recognition is to identify objects in a scene and estimate their pose. Object recognition from 2D images is sensitive to illumination, pose, clutter and occlusions. Object recognition from range data on the other hand does not suffer from these limitations. An important paradigm of recognition is model-based whereby 3D models of objects are constructed offline and saved in a database, using a suitable representation. During online recognition, a similar representation of a scene is matched with the database for recognizing objects present in the scene . . . The tensor representation is extended to automatic and pose invariant 3D face recognition. As the face is a non-rigid object, expressions can significantly change its 3D shape. Therefore, the last part of this thesis investigates representations and matching techniques for automatic 3D face recognition which are robust to facial expressions. A number of novelties are proposed in this area along with their extensive experimental validation using the largest available 3D face database. These novelties include a region-based matching algorithm for 3D face recognition, a 2D and 3D multimodal hybrid face recognition algorithm, fully automatic 3D nose ridge detection, fully automatic normalization of 3D and 2D faces, a low cost rejection classifier based on a novel Spherical Face Representation, and finally, automatic segmentation of the expression insensitive regions of a face.
Recognition Of Free Form 3d Objects In Range Data Using Global And Local Features
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Author : Richard J. Campbell
language : en
Publisher:
Release Date : 2001
Recognition Of Free Form 3d Objects In Range Data Using Global And Local Features written by Richard J. Campbell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with categories.
Towards The Recognition Of 3d Free Form Objects
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Author :
language : en
Publisher:
Release Date :
Towards The Recognition Of 3d Free Form Objects written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
This paper investigates a new approach for the recognition of 3D objects of arbitrary shape. The proposed solution follows the principle of model-based recognition using geometric 3D models and geometric matching. It is an alternative to the classical segmentation and primitive extraction approach and provides a perspective to escape some of its difficulties to deal with free-form shapes. The heart of this new approach is a recently published iterative closest point matching algorithm, which is applied variously to a number of initial configurations. We examine methods to obtain successful matching. Our investigations refer to a recognition system used for the pose estimation of 3D industrial objects in automatic assembly, with objects obtained from range data. The recognition algorithm works directly on the 3D coordinates of the objects surface as measured by a range finder. This makes our system independent of assumptions on the objects geometry. Test and model objects are sets of 3D points to be compared with the iterative closest point matching algorithm. Substantially, we propose a set of rules to choose promising initial configurations for the iterative closest point matching; an appropriate quality measure which permits reliable decision; a method to represent the object surface in a way that improves computing time and matching quality. Examples demonstrate the feasibility of this approach to free-form recognition.
Representations And Techniques For 3d Object Recognition And Scene Interpretation
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Author : Derek Santhanam
language : en
Publisher: Springer
Release Date : 2011-08-18
Representations And Techniques For 3d Object Recognition And Scene Interpretation written by Derek Santhanam and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-18 with Computers categories.
One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physical scenes from images. The second section introduces representations for 3D object categories that account for the intrinsically 3D nature of objects and provide robustness to change in viewpoints. The third section discusses strategies to unite inference of scene geometry and object pose and identity into a coherent scene interpretation. Each section broadly surveys important ideas from cognitive science and artificial intelligence research, organizes and discusses key concepts and techniques from recent work in computer vision, and describes a few sample approaches in detail. Newcomers to computer vision will benefit from introductions to basic concepts, such as single-view geometry and image classification, while experts and novices alike may find inspiration from the book's organization and discussion of the most recent ideas in 3D scene understanding and 3D object recognition. Specific topics include: mathematics of perspective geometry; visual elements of the physical scene, structural 3D scene representations; techniques and features for image and region categorization; historical perspective, computational models, and datasets and machine learning techniques for 3D object recognition; inferences of geometrical attributes of objects, such as size and pose; and probabilistic and feature-passing approaches for contextual reasoning about 3D objects and scenes. Table of Contents: Background on 3D Scene Models / Single-view Geometry / Modeling the Physical Scene / Categorizing Images and Regions / Examples of 3D Scene Interpretation / Background on 3D Recognition / Modeling 3D Objects / Recognizing and Understanding 3D Objects / Examples of 2D 1/2 Layout Models / Reasoning about Objects and Scenes / Cascades of Classifiers / Conclusion and Future Directions
Representations And Techniques For 3d Object Recognition And Scene Interpretation
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Author : Derek Hoiem
language : en
Publisher: Morgan & Claypool Publishers
Release Date : 2011
Representations And Techniques For 3d Object Recognition And Scene Interpretation written by Derek Hoiem and has been published by Morgan & Claypool Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Computers categories.
One of the grand challenges of artificial intelligence is to enable computers to interpret 3D scenes and objects from imagery. This book organizes and introduces major concepts in 3D scene and object representation and inference from still images, with a focus on recent efforts to fuse models of geometry and perspective with statistical machine learning. The book is organized into three sections: (1) Interpretation of Physical Space; (2) Recognition of 3D Objects; and (3) Integrated 3D Scene Interpretation. The first discusses representations of spatial layout and techniques to interpret physical scenes from images. The second section introduces representations for 3D object categories that account for the intrinsically 3D nature of objects and provide robustness to change in viewpoints. The third section discusses strategies to unite inference of scene geometry and object pose and identity into a coherent scene interpretation. Each section broadly surveys important ideas from cognitive science and artificial intelligence research, organizes and discusses key concepts and techniques from recent work in computer vision, and describes a few sample approaches in detail. Newcomers to computer vision will benefit from introductions to basic concepts, such as single-view geometry and image classification, while experts and novices alike may find inspiration from the book's organization and discussion of the most recent ideas in 3D scene understanding and 3D object recognition. Specific topics include: mathematics of perspective geometry; visual elements of the physical scene, structural 3D scene representations; techniques and features for image and region categorization; historical perspective, computational models, and datasets and machine learning techniques for 3D object recognition; inferences of geometrical attributes of objects, such as size and pose; and probabilistic and feature-passing approaches for contextual reasoning about 3D objects and scenes. Table of Contents: Background on 3D Scene Models / Single-view Geometry / Modeling the Physical Scene / Categorizing Images and Regions / Examples of 3D Scene Interpretation / Background on 3D Recognition / Modeling 3D Objects / Recognizing and Understanding 3D Objects / Examples of 2D 1/2 Layout Models / Reasoning about Objects and Scenes / Cascades of Classifiers / Conclusion and Future Directions