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Human tracking of track and field athletes based on FPGA and computer vision
Microprocessors and Microsystems ( IF 2.6 ) Pub Date : 2021-01-15 , DOI: 10.1016/j.micpro.2021.104020
Xin Jiang

An essential issue that sports science faces in understanding the game's flow is to analyze the game's situation. The use of information technology can help to achieve this goal. Computing speed, the size of the system, consider the accuracy of the complex data analysis. From the practical application of views, technical problems can be divided into three significant respects. This article aims to accelerate image recognition and object tracking; propose a one-dimensional data pipeline architecture on a Field-Programmable Gate Array (FPGA). It is met by a small circuit considering calculation and the spatiotemporal data dependency between two high-velocity flows. The volleyball game has been selected as the target application. FPGA design, pre-processing, color filtering, digitization, noise reduction, including such as template matching. Design and implementation by training stations of the Spartan-6 FPGA Xilinx Atlys of the Spartan-6 FPGA LX45 'were evaluated. Computing power will reach per 100 frames at a resolution of SVGA 800 × 600 pixels. Design, excellent with the scalability, can more easily improve the performance in the case of using a large FPGA. The proposed system consists of the Atlys substrate and Atlys VmodCAM stereo camera board. The average accuracy rate before the game situation and the game with 87.1 percent and 65.7 percent. Since the streaming input data, you can improve the precision by taking into account the previous and the next frame. And 90.4 percent will be able to improve to 72.2 percent by using a moving average filter and template matching.



中文翻译:

基于FPGA和计算机视觉的田径运动员人工追踪

体育科学在理解游戏流程时面临的一个基本问题是分析游戏情况。信息技术的使用可以帮助实现这一目标。计算速度,系统大小,考虑复杂数据分析的准确性。从实际应用的角度来看,技术问题可以分为三个重要方面。本文旨在加速图像识别和对象跟踪;提出了一种在现场可编程门阵列(FPGA)上的一维数据流水线架构。考虑到计算和两个高速流之间的时空数据相关性,可以通过一个小电路来解决。排球比赛已被选为目标应用。FPGA设计,预处理,色彩过滤,数字化,降噪,包括模板匹配。评估了由Spartan-6 FPGA Xilinx培训中心设计和实施的Spartan-6 FPGA LX45的Atlys。计算能力将达到每100帧,分辨率为SVGA 800×600像素。具有出色可扩展性的设计在使用大型FPGA的情况下可以更轻松地提高性能。拟议的系统由Atlys基板和Atlys VmodCAM立体摄像机板组成。比赛前和比赛前的平均准确率分别为87.1%和65.7%。由于流输入数据,因此可以通过考虑上一帧和下一帧来提高精度。通过使用移动平均滤波器和模板匹配,可以将90.4%的比例提高到72.2%。

更新日期:2021-01-22
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