MASCOT : metadata for advanced scalable video coding tools : final report

The goal of the MASCOT project was to develop new video coding schemes and tools that provide both an increased coding efficiency as well as extended scalability features compared to technology that was available at the beginning of the project. Towards that goal the following tools would be used: - metadata-based coding tools; - new spatiotemporal decompositions; - new prediction schemes. Although the initial goal was to develop one single codec architecture that was able to combine all new coding tools that were foreseen when the project was formulated, it became clear that this would limit the selection of the new tools. Therefore the consortium decided to develop two codec frameworks within the project, a standard hybrid DCT-based codec and a 3D wavelet-based codec, which together are able to accommodate all tools developed during the course of the project

No tradeoff between confidentiality and performance: An analysis on H.264/SVC partial encryption

Agency for Science, Technology and Research (A*STAR

A Novel Framework to Select Intelligent Video Streaming Scheme for Learning Software as a Service

Cloud computing offers many benefits for government, business and educational institutions as exemplified in many cases. Options to deliver video streaming contents for educational purposes over cloud computing infrastructures are highlighted in this study. In such case, parameters that affect video quality directly or indirectly must be taken into account such as bandwidth, jitter and loss of data. Currently, several intelligent schemes to improve video streaming services have been proposed by researchers through different approaches. This study aims to propose a novel framework to select appropriate intelligent video streaming schemes for efficiently delivering educational video contents for Learning Software as a Service (LSaaS)