This dissertation presents a methodology for recording speed climbing training sessions with multiple cameras and annotating the videos with relevant data, including body position, hand and foot placement, and timing. The annotated data is then analyzed using deep learning techniques to create a standard dataset of speed climbing training videos. The results demonstrate the potential of the new dataset for improving speed climbing training and research, including identifying areas for improvement, creating personalized training plans, and analyzing the effects of different training methods.The findings will also be applied to the training process of the Jiangxi climbing team through further empirical research to test the findings and further explore the feasibility of this study.

翻译：本文提出了一种利用多摄像头记录速度攀岩训练过程，并对视频进行身体位置、手脚摆放及计时等相关数据标注的方法。随后，借助深度学习技术对标注数据进行分析，以构建标准的速度攀岩训练视频数据集。研究结果表明，该新数据集在改进速度攀岩训练与科研方面具有潜力，包括识别待改进之处、制定个性化训练计划以及分析不同训练方法的效果。相关发现还将通过进一步的实证研究应用于江西攀岩队的训练实践，以检验研究结果并进一步探讨本研究的可行性。