Metadata-driven multimedia transcoding for distance learning

Mazen Almaoui, Azadeh Kushki, Konstantinos N. Plataniotis

Abstract: Advances in multimedia processing capabilities of electronic devices and the rapid growth of the Internet have contributed to the proliferation of collaborative applications such as distance learning (DL) webcasting. A key technical challenge in such DL systems is providing access to rich media content to any user regardless of device capabilities, network heterogeneity, and personal preferences. A novel MPEG-21-based adaptation architecture is presented to overcome these challenges by performing (1) application layer transcoding that adapts the presentation format of DL content to match device media decoding capabilities and user-desired modality, (2) bitstream transcoding to adapt multimedia to match device processing capabilities and encoding bit-rate supported by the network. Experimental results indicate that the proposed system delivers personalized DL content to meet end-user environmental restrictions with small transcoding overhead.