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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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2007
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| 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. |
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