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Resource-Efficient and High-Throughput VLSI Design of Global Optical Flow Method for Mobile Systems

机译:用于移动系统的全局光学流量方法的资源高效和高吞吐量VLSI设计

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Most very-large-scale integration (VLSI) designs of the global optical flow method focus on reducing external memory accesses due to global and iterative processes for low-power operation in mobile systems. However, to achieve this goal, considerable amounts of resources are used and the throughput is decreased. To address these issues, we propose a multirow-based propagation approach and an efficient VLSI architecture. This approach divides an image into multiple small subimages. The flow of each subimage is then estimated sequentially using a small amount of internal memory without accessing any external memory. To avoid discontinuity artifacts stemming from the boundaries of the subimages, boundary conditions are imposed based on the smoothness of the optical flow. In addition, the main equations of the global optical flow method are simplified to boost the processing speed. The experimental results demonstrate that the external memory bandwidth is reduced by 96.7% with negligible accuracy degradation. Furthermore, the proposed design uses 63.4%-98% less internal memory and achieves 1.9x-18.8x higher throughput-per-watt compared to state-of-the-art designs of the global optical flow method.
机译:全局光学流量方法的大多数非常大的集成(VLSI)设计侧重于减少移动系统中的低功耗操作的全局和迭代过程导致的外部存储器访问。但是,为了实现这一目标,使用了大量资源,并且吞吐量减少。为了解决这些问题,我们提出了一种基于多管的传播方法和高效的VLSI架构。该方法将图像划分为多个小型子程。然后使用少量内部存储器顺序地估计每个子图的流程,而不访问任何外部存储器。为了避免来自子图像的边界的不连续的伪像,基于光流的平滑度施加边界条件。另外,简化了全局光学流量方法的主方程以提高处理速度。实验结果表明,外部存储器带宽减少了96.7%,精度可忽略不计。此外,与全局光学流量方法的最先进设计相比,所提出的设计使用63.4%-98%-98%-98%较少的吞吐量为1.9×18.8倍。

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