Automated recognition of the cricket batting backlift technique in video footage using deep learning architectures.
Automated recognition of the cricket batting backlift technique in video footage using deep learning architectures.
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DOI：
10.1038/s41598-022-05966-6
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发表时间：
2022-02-03
影响因子：
4.6
通讯作者：
Noorbhai H
中科院分区：
文献类型：
--
作者：
Moodley T;van der Haar D;Noorbhai H
有有限的研究证明了使用机器学习的板球击球技术的有效性。这项研究演示了如何在视频片段中自动识别板球中的击球后举技术，并比较了流行的深度学习架构，即AlexNet，Inception V3，Inception Resnet V2和Xception的性能。创建包含横向和直背举类的数据集，并根据标准机器学习指标进行评估。这些架构具有相似的性能，在横向类中有一个假阳性，精确度得分为100%，沿着召回率得分为95%，每个架构的f1得分为98%。AlexNet架构在四个架构中表现最差，因为它错误地将四个图像分类为直线类。最适合问题域的架构是Xception架构，其准确度损失为0.03%和98.2.5%，从而证明了其区分横向和直背举的能力。这项研究为自动识别运动员模式和动作捕捉提供了一种方法，使运动科学家，生物力学家和视频分析师在该领域的工作更具挑战性。
There have been limited studies demonstrating the validation of batting techniques in cricket using machine learning. This study demonstrates how the batting backlift technique in cricket can be automatically recognised in video footage and compares the performance of popular deep learning architectures, namely, AlexNet, Inception V3, Inception Resnet V2, and Xception. A dataset is created containing the lateral and straight backlift classes and assessed according to standard machine learning metrics. The architectures had similar performance with one false positive in the lateral class and a precision score of 100%, along with a recall score of 95%, and an f1-score of 98% for each architecture, respectively. The AlexNet architecture performed the worst out of the four architectures as it incorrectly classified four images that were supposed to be in the straight class. The architecture that is best suited for the problem domain is the Xception architecture with a loss of 0.03 and 98.2.5% accuracy, thus demonstrating its capability in differentiating between lateral and straight backlifts. This study provides a way forward in the automatic recognition of player patterns and motion capture, making it less challenging for sports scientists, biomechanists and video analysts working in the field.
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