Particle filters are advanced for building robust object trackers capable of operation under difficult tracking conditions. An Excitation Particle Filter (EPF) is introduced in this book for object tracking. A new likelihood model is proposed. It depends on multiple likelihood functions: position likelihood; gray level intensity likelihood and similarity likelihood. Also, we modify the PF as a robust estimator to overcome the well-known sample impoverishment problem of the PF. The proposed enhanced PF (EPF) is implemented in software and evaluated. Simulation results demonstrated the superior performance of the proposed tracker in terms of accuracy, robustness and occlusion over classical tracking algorithms. Three efficient novel hardware architectures of the Sample Important Resample Filter (SIRF) and the EPF are introduced and implemented on FPGA platform. These architectures feature speed improvement, efficient memory utilization, and/or hardware resource saving.
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Lecturer at Department of Computers and Systems Engineering , Faculty of Engineering, Zagazig University. Lecturer at Nuclear Research Center. PhD. and Msc. in Electronic and Communication from Faculty of Engineering, Cairo University 2010 and 2002. Bsc. in Electronic and Communication from Faculty of Engineering, Zagazig University 1993.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Particle filters are advanced for building robust object trackers capable of operation under difficult tracking conditions. An Excitation Particle Filter (EPF) is introduced in this book for object tracking. A new likelihood model is proposed. It depends on multiple likelihood functions: position likelihood; gray level intensity likelihood and similarity likelihood. Also, we modify the PF as a robust estimator to overcome the well-known sample impoverishment problem of the PF. The proposed enhanced PF (EPF) is implemented in software and evaluated. Simulation results demonstrated the superior performance of the proposed tracker in terms of accuracy, robustness and occlusion over classical tracking algorithms. Three efficient novel hardware architectures of the Sample Important Resample Filter (SIRF) and the EPF are introduced and implemented on FPGA platform. These architectures feature speed improvement, efficient memory utilization, and/or hardware resource saving. 120 pp. Englisch. Bestandsnummer des Verkäufers 9783659243486
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Abd El-Halym HowidaLecturer at Department of Computers and Systems Engineering , Faculty of Engineering, Zagazig University. Lecturer at Nuclear Research Center. PhD. and Msc. in Electronic and Communication from Faculty of Engineeri. Bestandsnummer des Verkäufers 159139151
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Particle filters are advanced for building robust object trackers capable of operation under difficult tracking conditions. An Excitation Particle Filter (EPF) is introduced in this book for object tracking. A new likelihood model is proposed. It depends on multiple likelihood functions: position likelihood; gray level intensity likelihood and similarity likelihood. Also, we modify the PF as a robust estimator to overcome the well-known sample impoverishment problem of the PF. The proposed enhanced PF (EPF) is implemented in software and evaluated. Simulation results demonstrated the superior performance of the proposed tracker in terms of accuracy, robustness and occlusion over classical tracking algorithms. Three efficient novel hardware architectures of the Sample Important Resample Filter (SIRF) and the EPF are introduced and implemented on FPGA platform. These architectures feature speed improvement, efficient memory utilization, and/or hardware resource saving.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 120 pp. Englisch. Bestandsnummer des Verkäufers 9783659243486
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Particle filters are advanced for building robust object trackers capable of operation under difficult tracking conditions. An Excitation Particle Filter (EPF) is introduced in this book for object tracking. A new likelihood model is proposed. It depends on multiple likelihood functions: position likelihood; gray level intensity likelihood and similarity likelihood. Also, we modify the PF as a robust estimator to overcome the well-known sample impoverishment problem of the PF. The proposed enhanced PF (EPF) is implemented in software and evaluated. Simulation results demonstrated the superior performance of the proposed tracker in terms of accuracy, robustness and occlusion over classical tracking algorithms. Three efficient novel hardware architectures of the Sample Important Resample Filter (SIRF) and the EPF are introduced and implemented on FPGA platform. These architectures feature speed improvement, efficient memory utilization, and/or hardware resource saving. Bestandsnummer des Verkäufers 9783659243486
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Taschenbuch. Zustand: Neu. Particle Filters for Object Tracking | Enhanced Algorithm and Efficient Implementations | Howida Abd El-Halym (u. a.) | Taschenbuch | 120 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9783659243486 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 113177471
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Paperback. Zustand: Brand New. 120 pages. 8.66x5.91x0.28 inches. In Stock. Bestandsnummer des Verkäufers __3659243485
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Paperback. Zustand: Brand New. 120 pages. 8.66x5.91x0.28 inches. In Stock. Bestandsnummer des Verkäufers 3659243485
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