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Balanced Parallel Scheduling for Video Encoding with Adaptive GOP Structure
PrePrint
ISSN: 1045-9219
Hsu-Feng Hsiao, National Chiao Tung University, Hsinchu
Chen-Tsang Wu, National Chiao Tung University, Hsinchu
Due to the nature of dynamic GOP structure, parallel scheduling for video encoding becomes challenging. To address this, the balanced frame-level parallel scheduling algorithms are developed. The proposed approaches first determine the frame priority and then the thread priority assignment for scheduling. The concept of the algorithms lies in the analysis of coding complexity, temporal influence, and the required temporal burden to finish coding. To complete the scheduling with dynamic GOP structure, a block-based abrupt and gradual scene change detection algorithm is also proposed to determine GOP structure adaptively. The experiments show that the scheduling performance is close to the optimal. In addition, the concept of batch processing is incorporated so that the required buffer can be reduced.
Index Terms:
Artificial Intelligence,Parallelism and concurrency,Modes of Computation,Computation by Abstract Devices,Theory of Computation,Video coding,Compression (Coding),Image Processing and Computer Vision,Computing Methodologies,Video analysis,Vision and Scene Understanding
Citation:
Hsu-Feng Hsiao, Chen-Tsang Wu, "Balanced Parallel Scheduling for Video Encoding with Adaptive GOP Structure," IEEE Transactions on Parallel and Distributed Systems, 11 Jan. 2013. IEEE computer Society Digital Library. IEEE Computer Society, <http://doi.ieeecomputersociety.org/10.1109/TPDS.2013.7>
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