ICME 2006 Toronto

Multi-User Collaboration and Cross Layer Optimization in Wireless Multimedia Communication

Organizers

Zhu Li
Multimedia Research Lab
Motorola Labs, USA
zhu.li@motorola.com
Pascal Frossard
Signal Processing Institute
EPFL, Switzerland
pascal.frossard@epfl.ch
Aggelos Katsaggelos
Dept of EECS
Northwestern University, USA
aggk@ece.northwestern.edu

Call for Papers

Technology advances in both computing and wireless communication have created a plethora of multimedia capable mobile devices connected with a variety of wireless communication networks. Serving and sharing multimedia content seamlessly among mobile users and across heterogeneous channels and networks, with limited communication resource and computing capabilities, present a challenge to the state-of-art of multimedia coding and communication. In particular, the application layer end-to-end media Quality of Service (QoS) requirements have to be mapped vertically to the coding and communication decisions, at various layers of communication stack, in an efficient manner. Novel algorithms that balance the communication and computing resources with the media qualities and user preferences, need to be investigated in a content-aware, cross-layer approaches. In addition, limited communication/computing resources are often shared by multiple communication sessions, each with independent objectives in QoS and requirements on resource. Conflicts in objective and requirement for communication and computation resource need to be resolved, in a distributed and collaborative fashion.

This special session seeks original contributions that address issues in video content analysis, intelligent coding and adaptation, cross layer optimization of coding/communication decisions, distributed and collaborative communication resource allocation, for wireless multimedia communication. Topics of interest include but are not limited to:

  • Video content analysis for richer quality metrics
  • Cross layer optimization for video adaptation
  • Distributed resource allocation and management for video communication
  • Signal processing/information theories to support collaborative video communications
  • Network utility maximization based on collaborative video communications
  • Pricing models for collaborative video transmissions
  • Game theoretical models for video contents interactions in multi-user environments
  • Incentive mechanisms for relaying video contents in multi-hop networks

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