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Anton Prokopov (6 results)
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Moving object detection using GMM on mobile devices
Language: English
Published by LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330079363 ISBN 13: 9783330079366
Paperback. Condition: Brand New. 64 pages. 8.66x5.91x0.15 inches. In Stock.
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Moving object detection using GMM on mobile devices
Language: English
Published by LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330079363 ISBN 13: 9783330079366
Taschenbuch. Condition: Neu. Moving object detection using GMM on mobile devices | Anton Prokopov (u. a.) | Taschenbuch | 64 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330079366 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
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Moving object detection using GMM on mobile devices
Language: English
Published by LAP LAMBERT Academic Publishing Mai 2017, 2017
ISBN 10: 3330079363 ISBN 13: 9783330079366
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book describes an automatic background-foreground detection for the purpose of further traffic analysis. The aim of this project was to investigate and implement the background removal algorithm that uses Gaussian Mixture Model to perform robust background subtraction in real time. This kind of a system can recognize the moving objects in the video sequence using only camera. It finds its application in traffic analysis. The implementation has been done firstly on a computer using C++ OpenCV library followed by translating the code for being executable on Android device. 64 pp. Englisch.
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Moving object detection using GMM on mobile devices
Language: English
Published by LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330079363 ISBN 13: 9783330079366
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Prokopov AntonAuthor holds a BSc degree in Computer Science from the University of Tartu in 2016 and is in pursuit of his MSc degree in the same field also in the University of Tartu. At the same time author works as a Software Engin.
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Moving object detection using GMM on mobile devices
Language: English
Published by LAP LAMBERT Academic Publishing Mai 2017, 2017
ISBN 10: 3330079363 ISBN 13: 9783330079366
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book describes an automatic background-foreground detection for the purpose of further traffic analysis. The aim of this project was to investigate and implement the background removal algorithm that uses Gaussian Mixture Model to perform robust background subtraction in real time. This kind of a system can recognize the moving objects in the video sequence using only camera. It finds its application in traffic analysis. The implementation has been done firstly on a computer using C++ OpenCV library followed by translating the code for being executable on Android device.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 64 pp. Englisch.
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Moving object detection using GMM on mobile devices
Language: English
Published by LAP LAMBERT Academic Publishing, 2017
ISBN 10: 3330079363 ISBN 13: 9783330079366
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book describes an automatic background-foreground detection for the purpose of further traffic analysis. The aim of this project was to investigate and implement the background removal algorithm that uses Gaussian Mixture Model to perform robust background subtraction in real time. This kind of a system can recognize the moving objects in the video sequence using only camera. It finds its application in traffic analysis. The implementation has been done firstly on a computer using C++ OpenCV library followed by translating the code for being executable on Android device.
