• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

基于计算机视觉的射击动作智能矫正方法。

Intelligent Correction Method of Shooting Action Based on Computer Vision.

机构信息

School of Sport Sciences, Lingnan Normal Univesity, Zhanjiang 524048, China.

Department of Physical Education, Tangshan Normal University, Tangshan 063000, China.

出版信息

Comput Intell Neurosci. 2022 Jul 11;2022:8753473. doi: 10.1155/2022/8753473. eCollection 2022.

DOI:10.1155/2022/8753473
PMID:35860645
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9293490/
Abstract

Aiming at the problem that the students' long-term use of nonstandard shooting action leads to poor basketball teaching effect, an intelligent correction method of shooting action based on computer vision is proposed. Combined with the principle of computer vision, the image acquisition model of basketball shooting action is constructed. The edge contour and adaptive feature segmentation of basketball images are detected, and abnormal shooting movements are recognized. The intelligent correction model of shooting action is constructed, and the intelligent correction of shooting action is realized. Finally, through experiments, it is proved that the visual analysis and intelligent correction effect of basketball shooting action are obviously better, and it can correct shooting action in real time and accurately.

摘要

针对学生长期使用非标准投篮动作导致篮球教学效果差的问题,提出了一种基于计算机视觉的投篮动作智能矫正方法。结合计算机视觉原理,构建了篮球投篮动作的图像采集模型。检测篮球图像的边缘轮廓和自适应特征分割,识别异常投篮动作。构建投篮动作智能矫正模型,实现投篮动作的智能矫正。最后通过实验证明,该方法对篮球投篮动作的视觉分析和智能矫正效果明显更好,能够实时、准确地矫正投篮动作。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a586/9293490/b1079a570c18/CIN2022-8753473.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a586/9293490/d07875a5aecb/CIN2022-8753473.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a586/9293490/cc83ea30f73c/CIN2022-8753473.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a586/9293490/bfa6338b0ac2/CIN2022-8753473.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a586/9293490/4b5065fb9fd8/CIN2022-8753473.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a586/9293490/b1079a570c18/CIN2022-8753473.005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a586/9293490/d07875a5aecb/CIN2022-8753473.001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a586/9293490/cc83ea30f73c/CIN2022-8753473.002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a586/9293490/bfa6338b0ac2/CIN2022-8753473.003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a586/9293490/4b5065fb9fd8/CIN2022-8753473.004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a586/9293490/b1079a570c18/CIN2022-8753473.005.jpg

相似文献

1
Intelligent Correction Method of Shooting Action Based on Computer Vision.基于计算机视觉的射击动作智能矫正方法。
Comput Intell Neurosci. 2022 Jul 11;2022:8753473. doi: 10.1155/2022/8753473. eCollection 2022.
2
Concrete Application of Computer Virtual Image Technology in Modern Sports Training.计算机虚拟影像技术在现代体育训练中的具体应用。
Comput Intell Neurosci. 2022 Mar 8;2022:6807106. doi: 10.1155/2022/6807106. eCollection 2022.
3
Study on eye movement characteristics and intervention of basketball shooting skill.篮球投篮技能的眼动特征及干预研究。
PeerJ. 2022 Oct 31;10:e14301. doi: 10.7717/peerj.14301. eCollection 2022.
4
Aiming at a far target under different viewing conditions: visual control in basketball jump shooting.不同视觉条件下针对远距离目标:篮球跳投中的视觉控制
Hum Mov Sci. 2002 Oct;21(4):457-80. doi: 10.1016/s0167-9457(02)00116-1.
5
A video images-aware knowledge extraction method for intelligent healthcare management of basketball players.一种基于视频图像感知的篮球运动员智能医疗健康管理知识提取方法。
Math Biosci Eng. 2023 Jan;20(2):1919-1937. doi: 10.3934/mbe.2023088. Epub 2022 Nov 9.
6
Application Effect of Motion Capture Technology in Basketball Resistance Training and Shooting Hit Rate in Immersive Virtual Reality Environment.运动捕捉技术在沉浸式虚拟现实环境下篮球对抗训练及投篮命中率中的应用效果。
Comput Intell Neurosci. 2022 Jun 24;2022:4584980. doi: 10.1155/2022/4584980. eCollection 2022.
7
Adoption of Machine Learning Algorithm-Based Intelligent Basketball Training Robot in Athlete Injury Prevention.基于机器学习算法的智能篮球训练机器人在运动员损伤预防中的应用
Front Neurorobot. 2021 Jan 15;14:620378. doi: 10.3389/fnbot.2020.620378. eCollection 2020.
8
Set shot shooting performance and visual acuity in basketball.篮球中的定点投篮表现与视力
Optom Vis Sci. 1992 Oct;69(10):765-8. doi: 10.1097/00006324-199210000-00004.
9
Late information pick-up is preferred in basketball jump shooting.篮球跳投时,较晚获取信息更佳。
J Sports Sci. 2006 Sep;24(9):933-40. doi: 10.1080/02640410500357101.
10
Research on deep reinforcement learning basketball robot shooting skills improvement based on end to end architecture and multi-modal perception.基于端到端架构和多模态感知的深度强化学习篮球机器人投篮技术改进研究
Front Neurorobot. 2023 Oct 13;17:1274543. doi: 10.3389/fnbot.2023.1274543. eCollection 2023.

引用本文的文献

1
Retracted: Intelligent Correction Method of Shooting Action Based on Computer Vision.撤回:基于计算机视觉的射击动作智能校正方法。
Comput Intell Neurosci. 2023 Oct 4;2023:9759637. doi: 10.1155/2023/9759637. eCollection 2023.

本文引用的文献

1
Formulaic language identification model based on GCN fusing associated information.基于融合关联信息的图卷积网络的公式化语言识别模型
PeerJ Comput Sci. 2022 Jun 3;8:e984. doi: 10.7717/peerj-cs.984. eCollection 2022.
2
Control of Time Delay Force Feedback Teleoperation System With Finite Time Convergence.具有有限时间收敛性的时延力反馈遥操作系统控制
Front Neurorobot. 2022 May 6;16:877069. doi: 10.3389/fnbot.2022.877069. eCollection 2022.
3
Brain-computer interface-based assessment of color vision.基于脑机接口的色觉评估。
J Neural Eng. 2021 Nov 26;18(6). doi: 10.1088/1741-2552/ac3264.
4
GMNet: Graded-Feature Multilabel-Learning Network for RGB-Thermal Urban Scene Semantic Segmentation.GMNet:用于RGB-热红外城市场景语义分割的分级特征多标签学习网络
IEEE Trans Image Process. 2021;30:7790-7802. doi: 10.1109/TIP.2021.3109518. Epub 2021 Sep 14.
5
Restoration of Motion Blurred Image by Modified DeblurGAN for Enhancing the Accuracies of Finger-Vein Recognition.基于改进的 DeblurGAN 对运动模糊图像的恢复以提高手指静脉识别的准确率。
Sensors (Basel). 2021 Jul 6;21(14):4635. doi: 10.3390/s21144635.
6
Computer Vision for 3D Perception and Applications.计算机视觉的三维感知与应用
Sensors (Basel). 2021 Jun 8;21(12):3944. doi: 10.3390/s21123944.
7
What and How: Generalized Lifelong Spectral Clustering via Dual Memory.是什么与如何实现:通过双重记忆的广义终身谱聚类
IEEE Trans Pattern Anal Mach Intell. 2021 Feb 11;PP. doi: 10.1109/TPAMI.2021.3058852.
8
A Track Geometry Measuring System Based on Multibody Kinematics, Inertial Sensors and Computer Vision.基于多体运动学、惯性传感器和计算机视觉的轨道几何测量系统。
Sensors (Basel). 2021 Jan 20;21(3):683. doi: 10.3390/s21030683.
9
An Automated Light Trap to Monitor Moths (Lepidoptera) Using Computer Vision-Based Tracking and Deep Learning.基于计算机视觉跟踪和深度学习的自动诱虫灯监测蛾类(鳞翅目)
Sensors (Basel). 2021 Jan 6;21(2):343. doi: 10.3390/s21020343.
10
View-invariant Deep Architecture for Human Action Recognition using Two-stream Motion and Shape Temporal Dynamics.使用双流运动和形状时间动态的用于人类动作识别的视图不变深度架构
IEEE Trans Image Process. 2020 Jan 15. doi: 10.1109/TIP.2020.2965299.