In this work a novel video summarization system based on unique properties from singular value decomposition (SVD) is presented. Deriving compact representations of video sequences that are intuitive for users and let them easily and quickly browse large collections of video data is fast becoming one of the most important topics in content-based video processing. Such representations, are collectively refer to as video summaries. They rapidly provide the user with information about the contents of the particular video while preserving the information. The need for automatic methods for generating video summaries is fueled both from the user and production viewpoints. With the proliferation of personal video recorder devices and hand-held cameras, many users generate many times more video footage than they can digest. On the other hand, in today’s fast-paced news coverage, programs such as sports and news must be processed quickly for production or their value quickly decreases. Such time constraints and the increasing number of services being offered place a large burden on production companies to process, edit, and distribute video material as quickly as possible.
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Prof Veeranna Kotagi is presently serving as Assistant Professor in CSE in East west college of Engineering , Bengaluru. Prof.Venkata Srinivasu Veesam is serving as Assistant Prof in R.V.R & J.C.College of Engg,Guntur.Prof.Krishna Gudi is currently serving as Assistant Prof in CSE in Kammavari Sangham Institute of Technology , Bengaluru.
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Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In this work a novel video summarization system based on unique properties from singular value decomposition (SVD) is presented. Deriving compact representations of video sequences that are intuitive for users and let them easily and quickly browse large collections of video data is fast becoming one of the most important topics in content-based video processing. Such representations, are collectively refer to as video summaries. They rapidly provide the user with information about the contents of the particular video while preserving the information. The need for automatic methods for generating video summaries is fueled both from the user and production viewpoints. With the proliferation of personal video recorder devices and hand-held cameras, many users generate many times more video footage than they can digest. On the other hand, in today's fast-paced news coverage, programs such as sports and news must be processed quickly for production or their value quickly decreases. Such time constraints and the increasing number of services being offered place a large burden on production companies to process, edit, and distribute video material as quickly as possible. 52 pp. Englisch. Seller Inventory # 9786137324271
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Kotagi VeerannaProf Veeranna Kotagi is presently serving as Assistant Professor in CSE in East west college of Engineering , Bengaluru. Prof.Venkata Srinivasu Veesam is serving as Assistant Prof in R.V.R & J.C.College of Engg,Guntu. Seller Inventory # 385844848
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In this work a novel video summarization system based on unique properties from singular value decomposition (SVD) is presented. Deriving compact representations of video sequences that are intuitive for users and let them easily and quickly browse large collections of video data is fast becoming one of the most important topics in content-based video processing. Such representations, are collectively refer to as video summaries. They rapidly provide the user with information about the contents of the particular video while preserving the information. The need for automatic methods for generating video summaries is fueled both from the user and production viewpoints. With the proliferation of personal video recorder devices and hand-held cameras, many users generate many times more video footage than they can digest. On the other hand, in today's fast-paced news coverage, programs such as sports and news must be processed quickly for production or their value quickly decreases. Such time constraints and the increasing number of services being offered place a large burden on production companies to process, edit, and distribute video material as quickly as possible.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch. Seller Inventory # 9786137324271
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - In this work a novel video summarization system based on unique properties from singular value decomposition (SVD) is presented. Deriving compact representations of video sequences that are intuitive for users and let them easily and quickly browse large collections of video data is fast becoming one of the most important topics in content-based video processing. Such representations, are collectively refer to as video summaries. They rapidly provide the user with information about the contents of the particular video while preserving the information. The need for automatic methods for generating video summaries is fueled both from the user and production viewpoints. With the proliferation of personal video recorder devices and hand-held cameras, many users generate many times more video footage than they can digest. On the other hand, in today's fast-paced news coverage, programs such as sports and news must be processed quickly for production or their value quickly decreases. Such time constraints and the increasing number of services being offered place a large burden on production companies to process, edit, and distribute video material as quickly as possible. Seller Inventory # 9786137324271
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Taschenbuch. Condition: Neu. Video Summarization using Singular Value Decomposition | Veeranna Kotagi (u. a.) | Taschenbuch | 52 S. | Englisch | 2018 | LAP LAMBERT Academic Publishing | EAN 9786137324271 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 111512787
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