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A Cloud-based Approach for Parallel Video Transcoding and Object Recognition

Thesis type
  • Master
Student Tauqeer Ahmad
Status Finished
Submitted in 2015
Proposal on 10. Jul 2014 17:00
Proposal room Seminarraum I5
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Presentation on 02. Feb 2015 16:00
Presentation room Seminarraum I5
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Nowadays, video communications between mobile devices are one of the most demanded multimedia services. Two-thirds of the world's mobile data traffic will be video by 2015. Mobile video will more than double every year between 2010 and 2015. However, mobile users demand more sophisticated multimedia services for seamless multimedia experience with features like real-time sharing collaboration, easy navigation. Mobile cloud computing is current trending approach that can overcome some of the mentioned problems.

Within the UMIC and Learning Layers Projects, the objective of this thesis project is to integrate and further develop existing multimedia services for mobile and web clients. The framework especially deals with problems like being capable of receiving video streams, processing in the cloud, and delivering of value-added video services together with object recognition results. It should also be scalable and easy extendable, enable collaborative video creation and consumption and improve the capabilities of metadata annotation in videos through the use of object recognition methods.

The candidate should have a basic knowledge and interest in Web and mobile (Android) development. The candidate should also have interest in working with next-generation Web technologies such as HTML5, video streaming, Web Sockets, and XMPP and cloud frameworks such as Hadoop and Map Reduce.

 

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