Processor design for portable systems
Journal of VLSI Signal Processing Systems - Special issue on technologies for wireless computing
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
IEEE Transactions on Circuits and Systems for Video Technology
Power-minimized bit allocation for video communication over wireless channels
IEEE Transactions on Circuits and Systems for Video Technology
IEEE Transactions on Circuits and Systems for Video Technology
Overview of the H.264/AVC video coding standard
IEEE Transactions on Circuits and Systems for Video Technology
A generalized hypothetical reference decoder for H.264/AVC
IEEE Transactions on Circuits and Systems for Video Technology
Power-rate-distortion analysis for wireless video communication under energy constraints
IEEE Transactions on Circuits and Systems for Video Technology
Rate-distortion analysis for H.264/AVC video coding and its application to rate control
IEEE Transactions on Circuits and Systems for Video Technology
Low-complexity skip prediction for H.264 through Lagrangian cost estimation
IEEE Transactions on Circuits and Systems for Video Technology
Power Scalable Video Encoding Strategy Based on Game Theory
PCM '09 Proceedings of the 10th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Rate-distortion-complexity analysis on AVS encoder
PCM'10 Proceedings of the Advances in multimedia information processing, and 11th Pacific Rim conference on Multimedia: Part II
Power-efficient video encoding on resource-limited systems: A game-theoretic approach
Future Generation Computer Systems
Aggregate power consumption modeling of live video streaming systems
Proceedings of the 4th ACM Multimedia Systems Conference
AppAdapt: opportunistic application adaptation in presence of hardware variation
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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In this paper, a joint complexity-distortion optimization approach is proposed for real-time H.264 video encoding under the power-constrained environment. The power consumption is first translated to the encoding computation costs measured by the number of scaled computation units consumed by basic operations. The solved problem is then specified to be the allocation and utilization of the computational resources. A computation allocation model (CAM) with virtual computation buffers is proposed to optimally allocate the computational resources to each video frame. In particular, the proposed CAM and the traditional hypothetical reference decoder model have the same temporal phase in operations. Further, to fully utilize the allocated computational resources, complexity-configurable motion estimation (CAME) and complexity-configurable mode decision (CAMD) algorithms are proposed for H.264 video encoding. In particular, the CAME is performed to select the path of motion search at the frame level, and the CAMD is performed to select the order of mode search at the macroblock level. Based on the hierarchical adjusting approach, the adaptive allocation of computational resources and the fine scalability of complexity control can be achieved.