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Fast global motion estimation on single instruction multiple data processors for real-time devices

机译:用于实时设备的单指令多数据处理器上的快速全局运动估计

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Global motion estimation is a fundamental tool for image processing and computer vision. Since low-cost real-time devices have limited computational resources, the computational burden of global motion estimation remains considerable for low-cost devices. Hence, a fast global motion estimation algorithm for single instruction multiple data (SIMD) processors with which a CPU in modern mobile computing devices is commonly equipped is proposed. Conventional projection-based global motion estimation is modified to improve the prediction accuracy for videos containing large motions. To significantly increase the parallelism, the exact sizes of the variables in each processing step of the proposed algorithm are determined by considering the size of an SIMD register. Simulation results demonstrate that the proposed scheme is considerably fast and accurate, even for videos containing large motions.
机译:全局运动估计是用于图像处理和计算机视觉的基本工具。由于低成本实时设备具有有限的计算资源,因此对于低成本设备而言,全局运动估计的计算负担仍然很大。因此,提出了一种通常用于现代移动计算设备中的CPU的用于单指令多数据(SIMD)处理器的快速全局运动估计算法。修改了基于常规投影的全局运动估计,以提高包含大运动的视频的预测精度。为了显着提高并行度,通过考虑SIMD寄存器的大小来确定所提出算法的每个处理步骤中变量的确切大小。仿真结果表明,即使对于包含大运动的视频,所提出的方案也相当快且准确。

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