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数据集:用于基于计算机视觉分析 आसन的资源
Yogesh Suryawanshi1, Namrata Gunjal2, Burhanuddin Kanorewala1
1Vishwakarma University, Pune, India.
Data in brief
|June 29, 2023
概括
创建了一个新的姿势数据集,包含 11,344 个图像和 80 个有效和无效姿势的视频. 本资源有助于开发用于姿势分析和校正的计算机视觉算法.
科学领域:
- 计算机视觉 计算机视觉
- 机器学习 机器学习
- 健康与健康 保健与健康
背景情况:
- 提供了显著的身体和心理健康益处,但掌握姿势对初学者来说可能是个挑战.
- 准确的姿势识别需要强大的数据集来训练计算机视觉算法.
- 现有的资源可能缺乏足够的多样性或细节来进行先进的姿势分析.
研究的目的:
- 为计算机视觉应用创建一套关于 आसन (姿势) 的综合数据集.
- 为正确和不正确的姿势提供标记图像和视频.
- 促进用于练习和教学的人工智能工具的开发.
主要方法:
- 通过使用三星Galaxy M30s移动设备收集了10种的图像和视频数据.
- 捕获了11,344张图像和80个视频,将它们分为"有效 (右) "和"无效 (错误) "的姿势.
- 将数据集组织成10个子文件,每个子文件包含不同的有效和无效姿势数据.
主要成果:
- 现在可以获得一个包含11,344张图像和80个姿势视频的多样化数据集.
- 数据集包括对10种 आसन的正确和不正确执行之间的明确区别.
- 数据的结构使其易于集成到用于姿势识别的机器学习管道中.
结论:
- 这个姿势数据集是开发先进计算机视觉技术的基础资源.
- 它可以创建用于姿势检测,纠正和个性化指导的工具.
- 该数据集支持研究人员,应用程序开发人员和从业者推进技术和练习.
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