In this book, the problem of video object detection has been addressed. The object is detected by integrating the spatial segmentation as well as temporal segmentation. The spatial segmentation of frames has been formulated in spatio-temporal framework. A Compound MRF model is proposed to model the video sequence. This model takes care of the spatial and the temporal distributions as well. Besides taking in to account the pixel distributions in temporal directions, it also model the edges in the temporal direction. This model has been named as edgebased model. The MAP estimates of the labels have been obtained by a hybrid algorithm and is devised by integrating that global as well as local convergent criterion. Similarly temporal segmentation is obtained by a proposed entropy based window growing scheme. The spatial and temporal segmentation have been integrated to obtain the Video Object Plane (VOP) and hence object detection.
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Mr.Badri Narayan Subudhi received BE degree in E&TC from the BPUT, India in 2004 and M. Tech degree in Elect. syst. and Comm. Engg. from N.I.T, Rourkela, India. Dr. Pradipta Kumar Nanda is Professor and Head of the Department of E&TC, ITER, Bhubaneswar. Prior to this, he had served N. I. T, Rourkela from 1986 to 2007.
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this book, the problem of video object detection has been addressed. The object is detected by integrating the spatial segmentation as well as temporal segmentation. The spatial segmentation of frames has been formulated in spatio-temporal framework. A Compound MRF model is proposed to model the video sequence. This model takes care of the spatial and the temporal distributions as well. Besides taking in to account the pixel distributions in temporal directions, it also model the edges in the temporal direction. This model has been named as edgebased model. The MAP estimates of the labels have been obtained by a hybrid algorithm and is devised by integrating that global as well as local convergent criterion. Similarly temporal segmentation is obtained by a proposed entropy based window growing scheme. The spatial and temporal segmentation have been integrated to obtain the Video Object Plane (VOP) and hence object detection. 172 pp. Englisch. Bestandsnummer des Verkäufers 9783838314198
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Zustand: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: SUBUDHI BADRI NARAYANMr.Badri Narayan Subudhi received BE degree in E&TC from the BPUT, India in 2004 and M. Tech degree in Elect. syst. and Comm. Engg. from N.I.T, Rourkela, India. Dr. Pradipta Kumar Nanda is Professor and Head of. Bestandsnummer des Verkäufers 5412110
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Taschenbuch. Zustand: Neu. Video Image Segmentation and Object Detection Using MRF Model | A Spatio-temporal Segmentation scheme for Moving Object Detection | Badri Narayan Subudhi (u. a.) | Taschenbuch | 172 S. | Englisch | 2010 | LAP LAMBERT Academic Publishing | EAN 9783838314198 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 101490295
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this book, the problem of video object detection has been addressed. The object is detected by integrating the spatial segmentation as well as temporal segmentation. The spatial segmentation of frames has been formulated in spatio-temporal framework. A Compound MRF model is proposed to model the video sequence. This model takes care of the spatial and the temporal distributions as well. Besides taking in to account the pixel distributions in temporal directions, it also model the edges in the temporal direction. This model has been named as edgebased model. The MAP estimates of the labels have been obtained by a hybrid algorithm and is devised by integrating that global as well as local convergent criterion. Similarly temporal segmentation is obtained by a proposed entropy based window growing scheme. The spatial and temporal segmentation have been integrated to obtain the Video Object Plane (VOP) and hence object detection.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 172 pp. Englisch. Bestandsnummer des Verkäufers 9783838314198
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this book, the problem of video object detection has been addressed. The object is detected by integrating the spatial segmentation as well as temporal segmentation. The spatial segmentation of frames has been formulated in spatio-temporal framework. A Compound MRF model is proposed to model the video sequence. This model takes care of the spatial and the temporal distributions as well. Besides taking in to account the pixel distributions in temporal directions, it also model the edges in the temporal direction. This model has been named as edgebased model. The MAP estimates of the labels have been obtained by a hybrid algorithm and is devised by integrating that global as well as local convergent criterion. Similarly temporal segmentation is obtained by a proposed entropy based window growing scheme. The spatial and temporal segmentation have been integrated to obtain the Video Object Plane (VOP) and hence object detection. Bestandsnummer des Verkäufers 9783838314198
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