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Synopsis
This thesis addresses the figure-ground segmentation problem in the context of complex systems for automatic object recognition. Firstly the problem of image segmentation in general terms is introduced, followed by a discussion about its importance for online and interactive acquisition of visual representations. Secondly a machine learning approach using artificial neural networks is presented. This approach on the basis of Generalized Learning Vector Quantization is investigated in challenging scenarios such as the real-time figure-ground segmentation of complex shaped objects under continuously changing environment conditions. The ability to fulfill these requirements characterize the novelty of the approach compared to state-of-the-art methods. Finally the proposed technique is extended in several aspects, which yields a framework for object segmentation that is applicable to improve current systems for visual object learning and recognition.
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About the Author
He studied computer science at Bielefeld University and received his diploma in 2005. As member of the Research Institute for Cognition and Robotics (CoR-Lab) and guest scientist at Honda Research Institute Europe GmbH he finished his PhD in 2011. Since 2011 he develops advanced driver assistance systems at Elektronische Fahrwerksysteme GmbH.
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- PublisherSüdwestdeutscher Verlag für Hochschulschriften
- Publication date2012
- ISBN 10 3838133714
- ISBN 13 9783838133713
- BindingPaperback
- LanguageEnglish
- Number of pages164
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Hypothesis-based image segmentation
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Südwestdeutscher Verlag Für Hochschulschriften AG Co. KG Jul 2015, 2015
ISBN 10: 3838133714
ISBN 13: 9783838133713
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This thesis addresses the figure-ground segmentation problem in the context of complex systems for automatic object recognition. Firstly the problem of image segmentation in general terms is introduced, followed by a discussion about its importance for online and interactive acquisition of visual representations. Secondly a machine learning approach using artificial neural networks is presented. This approach on the basis of Generalized Learning Vector Quantization is investigated in challenging scenarios such as the real-time figure-ground segmentation of complex shaped objects under continuously changing environment conditions. The ability to fulfill these requirements characterize the novelty of the approach compared to state-of-the-art methods. Finally the proposed technique is extended in several aspects, which yields a framework for object segmentation that is applicable to improve current systems for visual object learning and recognition. 164 pp. Englisch. Seller Inventory # 9783838133713
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Hypothesis-based image segmentation : A Machine Learning Approach
Published by
Südwestdeutscher Verlag Für Hochschulschriften AG Co. KG, 2012
ISBN 10: 3838133714
ISBN 13: 9783838133713
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Seller: AHA-BUCH GmbH, Einbeck, Germany
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This thesis addresses the figure-ground segmentation problem in the context of complex systems for automatic object recognition. Firstly the problem of image segmentation in general terms is introduced, followed by a discussion about its importance for online and interactive acquisition of visual representations. Secondly a machine learning approach using artificial neural networks is presented. This approach on the basis of Generalized Learning Vector Quantization is investigated in challenging scenarios such as the real-time figure-ground segmentation of complex shaped objects under continuously changing environment conditions. The ability to fulfill these requirements characterize the novelty of the approach compared to state-of-the-art methods. Finally the proposed technique is extended in several aspects, which yields a framework for object segmentation that is applicable to improve current systems for visual object learning and recognition. Seller Inventory # 9783838133713
Quantity: 1 available
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Hypothesis-based image segmentation
Published by
Südwestdeutscher Verlag für Hochschulschriften, 2012
ISBN 10: 3838133714
ISBN 13: 9783838133713
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Denecke AlexanderHe studied computer science at Bielefeld University and received his diploma in 2005. As member of the Research Institute for Cognition and Robotics (CoR-Lab) and guest scientist at Honda Research Institute Europe Gm. Seller Inventory # 5407651
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