[[Context-based Adaptation]]

Context-based Adaptation

Future media Internet will allow new applications to be realised with support for ubiquitous media-rich content service technologies. Virtual collaboration [1] is one of them, which allows remotely located partners to meet in a virtual environment using state-of-the-art communication and audiovisual technologies. However, given the diversity of scenarios and usage environments in these types of applications, access to content is likely to pose significant challenges, which need to be addressed through the use of context-aware content adaptation. The challenges arise, as each combination of location, terminal scale, connectivity, user preferences and other local usage environment factors may require a different source and channel coding format for the content. It is clearly impossible to pre-generate and store all of these formats for every item of content, and so real-time adaptation of a very limited set of formats (probably only one) is required.

Most of context aware content adaptation frameworks and platforms [2-7] were developed within the mobile services application domain. They tried mostly to explore context to improve usability aspects by sensing how the available devices were being used. Generally, they reacted directly to the sensed low-level contexts. They usually lacked flexibility, as they did not make use of ontologies or made a rather static and limited use of ontologies. Therefore, they did not explore the inter-relations among different types of low-level contextual information; thus did not sufficiently address the aspects of interoperability, scalability and security/privacy. In fact, earlier research was typically application-centric, overlooking the aspects of gathering different types of contextual information from different spaces and interoperability in heterogeneous environments. Likewise, aspects concerning security of content and context metadata, and ensuring the privacy of users have only recently started to be addressed.

A wide variety of research work has been conducted on privacy and DRM [8] as well as on adaptation [9][10] to date. However, such work has been essentially carried out independently, without any significant exchange of information between the different groups addressing each of the two topics. Nonetheless, adaptation is an operation to be performed upon the content. Accordingly, and as long as the content is governed or protected, the content adaptation operation should also be subjected to certain rules and rights. Therefore, it is inevitable that these two separated communities cross the boarders eventually and start to work together.

Architecture of the Context-Based Content Adaptation Platform

The context-aware content adaptation platform considered and developed for a virtual collaboration application is conceptually illustrated in Figure 1. The proposed platform consists of the following four major modules: Adaptation Decision Engine (ADE), Adaptation Authoriser (AA), Context Providers (CxPs) and Adaptation Engine Stacks (AESs) comprising the Adaptation Engines (AEs) within.

Context-Aware Content Adaptation Platform Figure 1 - Context-aware content adaptation platform in a selected virtual collaboration scenario (i.e., the virtual classroom)

These modules are independent units that interact with each other through Web Services-based interfaces. The distributed modular architecture of the adaptation platform ensures scalability. Well-defined interfaces based on open standards also guarantee interoperability and flexibility of freely adding, removing and migrating modules. The use of ontologies in the ADE, while being also a vehicle for interoperability, provides the platform with context-aware analysis capabilities closer to real-world situations. The AA ensures the governed use of protected content. Flexible AESs enable the execution of a variety of adaptations that can be dynamically configured and requested on the fly.

Related Topics

  • Virtual Collaboration System
  • Contextual Information
    • Novel type of Contextual Information
  • Adaptation Decision
  • Adaptation Engines
    • Scalability Adaptation
  • Governed Content Adaptation (Adaptation Authoriser)
  • Security in context-based content adaptation
  • Ontologies (Concept)
    • Ontologies in Context-Aware Applications


To see the purposes and goals for the demo please visit the following page: Adaptation Platform Demo: Storyline


Video Databases

Title Modality Description URL
Video library and tools Video and tools A collection of video test sequence and tools from Network Systems Lab, SFU http://nsl.cs.sfu.ca/wiki/index.php/Video_Library_and_Tools
HDTV test sequences HD video A collection of video test sequences in headerless 10 bit YUV422 and 8 bit “Abekas” formats ftp://vqeg.its.bldrdoc.gov/HDTV/SVT_exports/
3D videos Raw video A collection of 3D video test sequences from 3DTV project https://www.3dtv-research.org/3dav/3DAV_Test_Data/EE4/FHG_HHI/
3D videos Compressed video A collection of 3D video test sequences from PHILIPS http://www.inition.com/inition/downloads/philipscontent/
HD collection HD video Japanese HD collection http://www.dcaj.org/cosme/
YUV Video Sequences CIF and QCIF video Commonly used video test sequences in the 4:2:0 YUV format. http://trace.eas.asu.edu/yuv/index.html

VISNET II Databases

Title Modality Description Request
High definition video and B-format audio data set HD video and B-format audio Description Request this database


[1] C.T.E.R. Hewage, H. Kodikara Arachchi, T. Masterton, A.C. Yu, H. Uzuner, S. Dogan, and A.M. Kondoz, “Content adaptation for virtual office environment using scalable video coding”, in Proc. 16th IST Mobile and Wireless Communications Jul. 2007.

[2] M. Keidi and A. Kemper, “Towards context-aware adaptable Web Services”, in Proc. 13th World Wide Web Conference, May 2004.

[3] T. Chaari, F. Laforest, and A. Celentano, “Adaptation in context-aware pervasive information systems: The SECAS project”, Int. J. of Pervasive Computing and Commun., 2006.

[4] [Online]. Available: http://www.cs.kuleuven.be/~davy/cogito.php

[5] H.L. Chen, “An intelligent broker architecture for pervasive context-aware systems”, Ph.D. Thesis, Dept. of Computer Science and Electrical Engineering, University of Maryland, MD, USA, 2004.

[6] A.K. Dey, “The context toolkit: A toolkit for context-aware applications”. [Online]. Available: http://www.cs.berkeley.edu/~dey/context.html

[7] T. Gu, H.K. Pung, and D. Q. Zhang, “A service-oriented middleware for building context aware Services”, Elsevier J. of Network and Computer Applications, Jan. 2005.

[8] E. Rodríguez, “Standardisation of the protection and governance of multimedia content”, Ph.D. Thesis, Dept. of Info. and Com. Technologies, 2006.

[9] A. Vetro and C. Timmerer, “Digital item adaptation: Overview of standardization and research activities”, IEEE Trans. Multimedia, 2005.

[10] C. Timmerer and H. Hellwagner, “Interoperable adaptive multimedia communication”, IEEE Multimedia Mag., Jan.-Mar. 2005.


context-based_adaptation.txt · Last modified: 2008/10/27 13:01 by annac
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