The vision-based hand tracking and gesture recognition is an extremely challenging problem due to the intricate nature of hand gestures this is a reason that available computer vision algorithms are computationally complex. In this research work a new methodology for 3D human hand gestures detection and recognition is proposed, which can be used for natural and intuitive human-computer interaction and other robotic systems. The proposed method based on morphology approaches to solve the problem of human hand tracking and gesture recognition of 3D objects from a single silhouette image. This new proposed method was applied and tested on the simulated Manipulated Robotic System (UniMAP Robot Manipulator Simulation System) that allows this robotic system to act as an intelligent system to track a human hand in 3D space and estimate its orientation and position in real time with the goal of ultimately using the algorithm with a robotic spherical wrist system. During experiment, there was no need for continuous camera calibration, experimental result shows that proposed method is a robust, unlike other approaches that use costly leaning functions or generalization methods.
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PhD, Mechatronic Eng. Senior Lecturer for HND(BTEC - Edexcel, UK) & affil. by Sharjah Instit. of Tech., Uni. of Sharjah & Ittihad Uni. UAE (2002-2012). Academic Qualif.; GCE Sci. & Tech.(Uni. of London, UK), B.Eng.(RNEC, UK), MSc Electronics Eng. (USTO, Algeria), MSc & PhD Busi. Admin., Mexico) & PhD Mechatronic Eng., (UniMAP), Malaysia.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -The vision-based hand tracking and gesture recognition is an extremely challenging problem due to the intricate nature of hand gestures this is a reason that available computer vision algorithms are computationally complex. In this research work a new methodology for 3D human hand gestures detection and recognition is proposed, which can be used for natural and intuitive human-computer interaction and other robotic systems. The proposed method based on morphology approaches to solve the problem of human hand tracking and gesture recognition of 3D objects from a single silhouette image. This new proposed method was applied and tested on the simulated Manipulated Robotic System (UniMAP Robot Manipulator Simulation System) that allows this robotic system to act as an intelligent system to track a human hand in 3D space and estimate its orientation and position in real time with the goal of ultimately using the algorithm with a robotic spherical wrist system. During experiment, there was no need for continuous camera calibration, experimental result shows that proposed method is a robust, unlike other approaches that use costly leaning functions or generalization methods. 220 pp. Englisch. Bestandsnummer des Verkäufers 9783659380327
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Hussain Abadal-Salam T.PhD, Mechatronic Eng. Senior Lecturer for HND(BTEC - Edexcel, UK) & affil. by Sharjah Instit. of Tech., Uni. of Sharjah & Ittihad Uni. UAE (2002-2012). Academic Qualif. GCE Sci. & Tech.(Uni. of London, UK), B. Bestandsnummer des Verkäufers 5152406
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Taschenbuch. Zustand: Neu. Human-Machine Interaction By Tracking Hand Movements | Novel Approach - Using Morphology Technique | Abadal-Salam T. Hussain | Taschenbuch | 220 S. | Englisch | 2013 | LAP LAMBERT Academic Publishing | EAN 9783659380327 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 105595624
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The vision-based hand tracking and gesture recognition is an extremely challenging problem due to the intricate nature of hand gestures this is a reason that available computer vision algorithms are computationally complex. In this research work a new methodology for 3D human hand gestures detection and recognition is proposed, which can be used for natural and intuitive human-computer interaction and other robotic systems. The proposed method based on morphology approaches to solve the problem of human hand tracking and gesture recognition of 3D objects from a single silhouette image. This new proposed method was applied and tested on the simulated Manipulated Robotic System (UniMAP Robot Manipulator Simulation System) that allows this robotic system to act as an intelligent system to track a human hand in 3D space and estimate its orientation and position in real time with the goal of ultimately using the algorithm with a robotic spherical wrist system. During experiment, there was no need for continuous camera calibration, experimental result shows that proposed method is a robust, unlike other approaches that use costly leaning functions or generalization methods.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 220 pp. Englisch. Bestandsnummer des Verkäufers 9783659380327
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The vision-based hand tracking and gesture recognition is an extremely challenging problem due to the intricate nature of hand gestures this is a reason that available computer vision algorithms are computationally complex. In this research work a new methodology for 3D human hand gestures detection and recognition is proposed, which can be used for natural and intuitive human-computer interaction and other robotic systems. The proposed method based on morphology approaches to solve the problem of human hand tracking and gesture recognition of 3D objects from a single silhouette image. This new proposed method was applied and tested on the simulated Manipulated Robotic System (UniMAP Robot Manipulator Simulation System) that allows this robotic system to act as an intelligent system to track a human hand in 3D space and estimate its orientation and position in real time with the goal of ultimately using the algorithm with a robotic spherical wrist system. During experiment, there was no need for continuous camera calibration, experimental result shows that proposed method is a robust, unlike other approaches that use costly leaning functions or generalization methods. Bestandsnummer des Verkäufers 9783659380327
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