当前位置: X-MOL 学术Microprocess. Microsyst. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Simulation of basketball motion image resolution based on FPGA and gaussian mixture model
Microprocessors and Microsystems ( IF 2.6 ) Pub Date : 2021-01-07 , DOI: 10.1016/j.micpro.2021.103873
Aijun Liu

Basketball shooting thrown assumes an essential function in the Free-Basketball. A serious problem to play any of the tosses to the right, untimely to prepare all of the accounts. And prepared to not regularly excessively to tenacious. The point of this article is to change the free bio-feedback control. Elements of the elbow and the shoulder will be determined by the frame preparation strategy with a video acquisition. The learning control arrangement naming framework presented herein can be evaluated and given phonetic gradually, as described above, the input boundary. Method respects the identification and control of learning and the right of shooting performance. Test results show that the free toss and shooting style upgrades, including location shooting pocket and bolts. Video preparation circuit and framework to deal with top record successive frames are the keys these days. The circuit proposed in the article, improvement of open memory library, focused on the strong identification of the basis of the target stream of balls moving the details of the calculation of the Gaussian Mixture Model (GMM). According to the present invention, facility layout, detailed GMM conditions, reduce the use of dual multipliers, and pressure method reduce the device's complexity and allow the expansion of capacity. The proposed circuit is proposed to enable a high-speed and reasonable asset to defeat the implementation. It is planned to have a business, Filed Programmable Gate Array (FPGA) gadgets as a target.



中文翻译:

基于FPGA和高斯混合模型的篮球运动图像分辨率仿真

篮球投篮是自由篮球的一项重要功能。严重地问题是无法正确地准备所有账目而进行正确的选择。并准备不经常过度顽强。本文的重点是更改免费的生物反馈控制。肘部和肩膀的元素将通过视频采集的帧准备策略确定。如上所述,可以评估本文介绍的学习控制布置命名框架,并逐步给其语音以语音作为输入边界。方法尊重学习的识别和控制以及射击表演的权利。测试结果表明,自由抛掷和射击风格得到了升级,包括位置射击口袋和螺栓。如今,视频准备电路和处理最高记录连续帧的框架是关键。本文中提出的电路,开放式存储库的改进,集中在对目标球流的基础进行强力识别的高斯混合模型(GMM)的计算细节上。根据本发明,设备布局,详细的GMM条件,减少对偶乘法器的使用以及压力方法降低了设备的复杂性并允许容量的扩大。提出的提议电路使高速合理的资产无法实现。计划将商业的可编程门阵列(FPGA)小工具作为目标。重点在于对目标球流的基础进行强有力的识别,详细介绍了高斯混合模型(GMM)的计算。根据本发明,设备布局,详细的GMM条件,减少对偶乘法器的使用以及压力方法降低了设备的复杂性并允许容量的扩大。提出的提议电路是为了使高速合理的资产无法实现。计划将商业的可编程门阵列(FPGA)小工具作为目标。重点在于对目标球流的基础进行强有力的识别,详细介绍了高斯混合模型(GMM)的计算。根据本发明,设备布局,详细的GMM条件,减少对偶乘法器的使用以及压力方法降低了设备的复杂性并允许容量的扩大。提出的提议电路使高速合理的资产无法实现。计划将商业的可编程门阵列(FPGA)小工具作为目标。的复杂性并允许容量的扩展。提出的提议电路使高速合理的资产无法实现。计划将商业的可编程门阵列(FPGA)小工具作为目标。的复杂性并允许容量的扩展。提出的提议电路使高速合理的资产无法实现。计划将商业的可编程门阵列(FPGA)小工具作为目标。

更新日期:2021-01-16
down
wechat
bug