Abstract
This paper presents a constraints programming based approach to decide which of a set of available content adaptation tools and parameters should be selected in order to perform the best adaptation of a media asset targeting to enhance the final user’s experience in a particular usage scenario. The work is within the scope of the Universal Multimedia Access (UMA) framework and makes use of MPEG standards for content and usage environment description. The proposed technique has been evaluated within the CAIN framework, a content adaptation engine that integrates different content adaptation tools, and that uses media and usage environment metadata to identify the best adaptation tool from the available ones. First, mandatory constraints are imposed. If there is more than one adaptation tool capable of adapting the content fulfilling every mandatory constraint, another group of desirable constraints are applied to reduce the solution space. If at this step there are still several adaptation tools or parameter values able to adapt the content fulfilling mandatory and desirable restrictions, a final optimization step chooses the best adaptation tool and parameters.
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López, F., Martínez, J.M., Valdés, V. (2007). Multimedia Content Adaptation Within the CAIN Framework Via Constraints Satisfaction and Optimization. In: Marchand-Maillet, S., Bruno, E., Nürnberger, A., Detyniecki, M. (eds) Adaptive Multimedia Retrieval: User, Context, and Feedback. AMR 2006. Lecture Notes in Computer Science, vol 4398. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-71545-0_12
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DOI: https://doi.org/10.1007/978-3-540-71545-0_12
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