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Reconfigurable architectures and processors for real-time video motion estimation

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Abstract

With the recent proliferation of multimedia applications, several fast block matching motion estimation algorithms have been proposed in order to minimize the processing time in video coding. While some of these algorithms adopt pre-defined search patterns that directly reflect the most probable motion structures, other data-adaptive approaches dynamically configure the search pattern to avoid unnecessary computations and memory accesses. Either of these approaches leads to rather difficult hardware implementations, due to their configurability and adaptive nature. As a consequence, two different but quite configurable architectures are proposed in this paper. While the first architecture reflects an innovative mechanism to implement motion estimation processors that support fast but regular search algorithms, the second architecture makes use of an application specific instruction set processor (ASIP) platform, capable of implementing most data-adaptive algorithms that have been proposed in the last few years. Despite their different natures, these two architectures provide highly configurable hardware platforms for real-time motion estimation. By considering a wide set of fast and adaptive algorithms, the efficiency of these two architectures was compared and several motion estimators were synthesized in a Virtex-II Pro XC2VP30 FPGA from Xilinx, integrated within a ML310 development platform. Experimental results show that the proposed architectures can be easily reconfigured in run-time to implement a wide set of real-time motion estimation algorithms.

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Acknowledgments

This work has been supported by the POSI program and the Portuguese Foundation for Science and for Technology (FCT) under the research project Adaptive H.264/AVC Motion Estimation Processor for Mobile and Battery Supplied Devices (AMEP) POSI/EEA-CPS/60765/2004.

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Correspondence to Leonel Sousa.

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Dias, T., Roma, N., Sousa, L. et al. Reconfigurable architectures and processors for real-time video motion estimation. J Real-Time Image Proc 2, 191–205 (2007). https://doi.org/10.1007/s11554-007-0049-6

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  • DOI: https://doi.org/10.1007/s11554-007-0049-6

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