A complexity-aware video adaptation mechanism for live streaming systems
EURASIP Journal on Applied Signal Processing
Proceedings of the 15th international conference on Multimedia
Video quality and system resources: Scheduling two opponents
Journal of Visual Communication and Image Representation
Statistical framework for video decoding complexity modeling and prediction
IEEE Transactions on Circuits and Systems for Video Technology
Informationally decentralized system resource management for multiple multimedia tasks
IEEE Transactions on Circuits and Systems for Video Technology
Power and distortion optimization for pervasive video coding
IEEE Transactions on Circuits and Systems for Video Technology
MPEG-21 standardization process: organization and rate distortion modeling for network adaptation
ICCOM'10 Proceedings of the 14th WSEAS international conference on Communications
Optimality and improvement of dynamic voltage scaling algorithms for multimedia applications
IEEE Transactions on Circuits and Systems Part I: Regular Papers
Computation of the complexity of vector quantizers by affine modeling
Signal Processing
Low-complexity video coding via power-rate-distortion optimization
Journal of Visual Communication and Image Representation
AppAdapt: opportunistic application adaptation in presence of hardware variation
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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Existing research on Universal Multimedia Access has mainly focused on adapting multimedia to the network characteristics while overlooking the receiver capabilities. Alternatively, part 7 of the MPEG-21 standard entitled Digital Item Adaptation (DIA) defines description tools to guide the multimedia adaptation process based on both the network conditions and the available receiver resources. In this paper, we propose a new and generic rate-distortion-complexity model that can generate such DIA descriptions for image and video decoding algorithms running on various hardware architectures. The novelty of our approach is in virtualizing complexity, i.e., we explicitly model the complexity involved in decoding a bitstream by a generic receiver. This generic complexity is translated dynamically into "real" complexity, which is architecture-specific. The receivers can then negotiate with the media server/proxy the transmission of a bitstream having a desired complexity level based on their resource constraints. Hence, unlike in previous streaming systems, multimedia transmission can be optimized in an integrated rate-distortion-complexity setting by minimizing the incurred distortion under joint rate-complexity constraints.