Synopsis
Automatic object recognition is a fundamental problem in the fields of computer vision and machine learning, that has received a lot of research attention lately. While there are different methods, that build upon various low level features to construct object models, this work explores and implements the use of closed-contours as formidable object features. A hierarchical technique is employed to extract the contours, exploiting the inherent spatial relationships between the parent and child contours of an object. Fourier Descriptors are used to effectively and invariantly describe the extracted contours. A simple hierarchical, shape label and spatial descriptor matching method is implemented, to determine the nearest object-model. Multi-threaded architecture and GPU efficient image-processing functions are adopted making the technique efficient for use in real world applications. The technique is successfully tested on common traffic signs in real world images, with overall good performance and robustness being obtained as an end result.
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Hierarchical approach for object detection using shape descriptors
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Automatic object recognition is a fundamental problem in the fields of computer vision and machine learning, that has received a lot of research attention lately. While there are different methods, that build upon various low level features to construct object models, this work explores and implements the use of closed-contours as formidable object features. A hierarchical technique is employed to extract the contours, exploiting the inherent spatial relationships between the parent and child contours of an object. Fourier Descriptors are used to effectively and invariantly describe the extracted contours. A simple hierarchical, shape label and spatial descriptor matching method is implemented, to determine the nearest object-model. Multi-threaded architecture and GPU efficient image-processing functions are adopted making the technique efficient for use in real world applications. The technique is successfully tested on common traffic signs in real world images, with overall good performance and robustness being obtained as an end result. 56 pp. Englisch. Seller Inventory # 9783330353060
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Hierarchical approach for object detection using shape descriptors
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Hierarchical approach for object detection using shape descriptors
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Hierarchical approach for object detection using shape descriptors
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Hierarchical approach for object detection using shape descriptors
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Arshad Bassam SyedBassam Syed Arshad - Graduate College of The University of Texas, Rio Grande Valley. Degree of Master of Science.Automatic object recognition is a fundamental problem in the fields of computer vision and machine. Seller Inventory # 298255290
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Hierarchical approach for object detection using shape descriptors
Published by
LAP LAMBERT Academic Publishing Mai 2019, 2019
ISBN 10: 3330353066
ISBN 13: 9783330353060
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Automatic object recognition is a fundamental problem in the fields of computer vision and machine learning, that has received a lot of research attention lately. While there are different methods, that build upon various low level features to construct object models, this work explores and implements the use of closed-contours as formidable object features. A hierarchical technique is employed to extract the contours, exploiting the inherent spatial relationships between the parent and child contours of an object. Fourier Descriptors are used to effectively and invariantly describe the extracted contours. A simple hierarchical, shape label and spatial descriptor matching method is implemented, to determine the nearest object-model. Multi-threaded architecture and GPU efficient image-processing functions are adopted making the technique efficient for use in real world applications. The technique is successfully tested on common traffic signs in real world images, with overall good performance and robustness being obtained as an end result.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch. Seller Inventory # 9783330353060
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Hierarchical approach for object detection using shape descriptors
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Automatic object recognition is a fundamental problem in the fields of computer vision and machine learning, that has received a lot of research attention lately. While there are different methods, that build upon various low level features to construct object models, this work explores and implements the use of closed-contours as formidable object features. A hierarchical technique is employed to extract the contours, exploiting the inherent spatial relationships between the parent and child contours of an object. Fourier Descriptors are used to effectively and invariantly describe the extracted contours. A simple hierarchical, shape label and spatial descriptor matching method is implemented, to determine the nearest object-model. Multi-threaded architecture and GPU efficient image-processing functions are adopted making the technique efficient for use in real world applications. The technique is successfully tested on common traffic signs in real world images, with overall good performance and robustness being obtained as an end result. Seller Inventory # 9783330353060
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Hierarchical approach for object detection using shape descriptors
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ISBN 13: 9783330353060
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Taschenbuch. Condition: Neu. Hierarchical approach for object detection using shape descriptors | Bassam Syed Arshad | Taschenbuch | 56 S. | Englisch | 2019 | LAP LAMBERT Academic Publishing | EAN 9783330353060 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 116827453