Video content adaptation based on user preferences and network bandwidth / Badariyah Bakhtiar

The diversity of multimedia presentation environment sets strict requirements for multimedia applications and systems. Since the invention of the computer, content has been tailored towards a specific device, mainly by hand. Mobile device have become very widespread in recent years. However, the...

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Bibliographic Details
Main Author: Bakhtiar, Badariyah
Format: Thesis
Language:English
Published: Faculty of Computer and Mathematical Sciences 2007
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/1399/2/1399.pdf
https://ir.uitm.edu.my/id/eprint/1399/
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Summary:The diversity of multimedia presentation environment sets strict requirements for multimedia applications and systems. Since the invention of the computer, content has been tailored towards a specific device, mainly by hand. Mobile device have become very widespread in recent years. However, the differences in processing power, storage and display resolution of mobile terminals will lead to some problems that the same content is sent to heterogeneous terminals. Offering mobile services to nomadic users involved the limited display and networking capacity of the mobile devices. Although content adaptation techniques have been extensively studied for mobile computing systems in last decades, most of the previous work focused on adaptation with respect to terminal capabilities. Yet, video adaptation is still a challenging field. With the increasing amount of video formats, attention turned towards transcoding video from one format to another in order to make the video compatible with the new usage environment. Thus, the personalization of the service, access a nomadic user's system according to their preferences and network bandwidth based to their needs is a proposed solution. The personalization is using an agent-based approach. System architecture was designed and implement in video adaptation algorithms development. Through the algorithm, rule-based technique was used. Based on the experiment results, it is proved that the video content adaptation under e-leaming environment can be achieved by the algorithms effectively.