As Smartphone is getting more potent, can do more superior stuffs that previous required a computer. For employing the high processing power of Smartphone is mobile computer vision, the ability for a device to capture; process; analyze; under- standing of images. For mobile computer vision, Smartphone must be faster and real time. In this book three applications have been developed on an Android platform using OpenCV and in built core library with own implemented algorithms called as CamTest. Real Time video processing methods are applied to each video frame captured from Smartphone, that is running on an Android platform. Effi- ciency of two Android applications have been compared with respect to video frame processing rate and found that OpenCV performs faster than the CamTest. Real Time object detection in mobile computer vision on Android is complicated task as it requires high performance. We analyzed object detection algorithms such as Scale Invariant Feature Transform (SIFT), Speeded Up Feature Transform (SURF), Fea- tures from Accelerated Segment Test (FAST), Maximally Stable Extremal Regions (MSER), Oriented FAST and Rotated BRIEF (ORB), Binary Robust Independent.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -As Smartphone is getting more potent, can do more superior stuffs that previous required a computer. For employing the high processing power of Smartphone is mobile computer vision, the ability for a device to capture; process; analyze; under- standing of images. For mobile computer vision, Smartphone must be faster and real time. In this book three applications have been developed on an Android platform using OpenCV and in built core library with own implemented algorithms called as CamTest. Real Time video processing methods are applied to each video frame captured from Smartphone, that is running on an Android platform. Effi- ciency of two Android applications have been compared with respect to video frame processing rate and found that OpenCV performs faster than the CamTest. Real Time object detection in mobile computer vision on Android is complicated task as it requires high performance. We analyzed object detection algorithms such as Scale Invariant Feature Transform (SIFT), Speeded Up Feature Transform (SURF), Fea- tures from Accelerated Segment Test (FAST), Maximally Stable Extremal Regions (MSER), Oriented FAST and Rotated BRIEF (ORB), Binary Robust Independent. 64 pp. Englisch. N° de réf. du vendeur 9783330082922
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Paperback. Etat : Brand New. 64 pages. 8.66x5.91x0.15 inches. In Stock. N° de réf. du vendeur 3330082925
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Deore Pramod J.Prof. Dr. Pramod J. Deore, BE (Electronics), ME ( Instrumentation), Phd (E & Tc). Prof. Shailaja Arjun Patil, BE (Electronics), ME (Electronics), Phd (Persuing), Mr.Chaudhari Sunil Bhimsing, BE (Electronics), ME ( E & . N° de réf. du vendeur 151237063
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Taschenbuch. Etat : Neu. Neuware -As Smartphone is getting more potent, can do more superior stuffs that previous required a computer. For employing the high processing power of Smartphone is mobile computer vision, the ability for a device to capture; process; analyze; under- standing of images. For mobile computer vision, Smartphone must be faster and real time. In this book three applications have been developed on an Android platform using OpenCV and in built core library with own implemented algorithms called as CamTest. Real Time video processing methods are applied to each video frame captured from Smartphone, that is running on an Android platform. Effi- ciency of two Android applications have been compared with respect to video frame processing rate and found that OpenCV performs faster than the CamTest. Real Time object detection in mobile computer vision on Android is complicated task as it requires high performance. We analyzed object detection algorithms such as Scale Invariant Feature Transform (SIFT), Speeded Up Feature Transform (SURF), Fea- tures from Accelerated Segment Test (FAST), Maximally Stable Extremal Regions (MSER), Oriented FAST and Rotated BRIEF (ORB), Binary Robust Independent.Books on Demand GmbH, Überseering 33, 22297 Hamburg 64 pp. Englisch. N° de réf. du vendeur 9783330082922
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As Smartphone is getting more potent, can do more superior stuffs that previous required a computer. For employing the high processing power of Smartphone is mobile computer vision, the ability for a device to capture; process; analyze; under- standing of images. For mobile computer vision, Smartphone must be faster and real time. In this book three applications have been developed on an Android platform using OpenCV and in built core library with own implemented algorithms called as CamTest. Real Time video processing methods are applied to each video frame captured from Smartphone, that is running on an Android platform. Effi- ciency of two Android applications have been compared with respect to video frame processing rate and found that OpenCV performs faster than the CamTest. Real Time object detection in mobile computer vision on Android is complicated task as it requires high performance. We analyzed object detection algorithms such as Scale Invariant Feature Transform (SIFT), Speeded Up Feature Transform (SURF), Fea- tures from Accelerated Segment Test (FAST), Maximally Stable Extremal Regions (MSER), Oriented FAST and Rotated BRIEF (ORB), Binary Robust Independent. N° de réf. du vendeur 9783330082922
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Taschenbuch. Etat : Neu. Real Time Video Processing and Object Detection on Mobile | Pramod J. Deore (u. a.) | Taschenbuch | 64 S. | Englisch | 2017 | LAP LAMBERT Academic Publishing | EAN 9783330082922 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. N° de réf. du vendeur 109327723
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