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Superpixel Accelerator for Computer Vision Applications on Arria 10 SoC

机译:适用于Arria 10 SoC的计算机视觉应用的超像素加速器

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摘要

Superpixel segmentation is a very popular image segmentation technique used in various computer vision tasks. Recently, a number of superpixel algorithms have been proposed in literature. One such algorithm is considered as the-state-of-the-art in superpixel segmentation: Simple Linear Iterative Clustering or SLIC. However, its original implementation has a long execution time on high performance processors designed within the common mobile and enterprise applications, as well on high-end processors such as Intel Xeon. Overall, the execution time for single-threaded implementation is considered critical for real-time or near real-time applications. In this paper, we explore the possibility of accelerating parts of the SLIC image segmentation critical for performance, by designing the image segmentation accelerator for Intel's Arria 10 SoC. We propose a novel architecture to enable hardware acceleration by addressing the problem of hardware/software partitioning to minimize the overall program latency.
机译:超像素分割是在各种计算机视觉任务中使用的非常流行的图像分割技术。最近,在文献中已经提出了许多超像素算法。一种这样的算法被认为是超像素分割中的最新技术:简单线性迭代聚类或SLIC。但是,它的原始实现在常见的移动和企业应用程序中设计的高性能处理器以及高端处理器(例如Intel Xeon)上具有较长的执行时间。总体而言,单线程实现的执行时间被认为对于实时或接近实时的应用程序至关重要。在本文中,我们通过设计用于英特尔Arria 10 SoC的图像分段加速器,探索了加速对性能至关重要的SLIC图像分段的可能性。我们提出了一种新颖的体系结构,通过解决硬件/软件分区问题来最大程度地减少总体程序延迟,从而实现硬件加速。

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