一种实时应用的horn - schunck光流算法的fpga优化架构

Michael Kunz, Alexander Ostrowski, P. Zipf
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引用次数: 23

摘要

图像序列的光流估计是运动检测的关键问题之一。然而,由于计算成本高,对光流的实时处理仍然是一个开放的任务。本文提出了一种基于Horn和Schunck算法的fpga优化光流估计架构。虽然现有的fpga实现仅具有部分实时能力,但在Stratix IV上,我们的架构能够以30 fps的帧率迭代计算640 × 512像素的帧中的每个像素的光流,并以全流水线形式以20 fps的帧率计算高达4k分辨率(4,096 × 2,304像素)的光流。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An FPGA-optimized architecture of horn and schunck optical flow algorithm for real-time applications
Optical flow estimation of image sequences is one of the key elements for motion detection. However, processing the optical flow in real-time is still an open task due to its computationally expensive nature. In this paper we present an FPGA-optimized architecture for optical flow estimation based on the algorithm of Horn and Schunck. While existing FPGA-realizations are only partly real-time capable, on a Stratix IV our architecture enables the computation of the optical flow for each pixel of a frame with 640 × 512 pixels at a framerate of 30 fps in iterative and up to 4k resolution (4,096 × 2,304 pixels) at a framerate of 20 fps in full-pipelined form.
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