Abstract
Based on the training effect evaluation of swimmers, this paper proposes an infrared image detection method based on HOG feature extraction and infrared image detection technology. Since optical images are easily affected by illumination and other factors in complex environments, infrared images are chosen as the object of training effect evaluation in this study. Infrared images have the advantages of illumination insensitivity, through fog and so on, which can better reflect the posture and action of swimmers. The infrared image detection method based on HOG feature extraction is described in detail, and the feature vector of swimmers is obtained. By detecting the infrared images of the training set and the test set, the evaluation results of the training effect of the swimmers are obtained. The experimental results show that this method can accurately detect the swimmer's posture and movement, and provides an effective means for evaluating the training effect.
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Tingrui, Z. Evaluation of infrared image detection based on HOG feature extraction in swimmer training effectiveness. Opt Quant Electron 56, 198 (2024). https://doi.org/10.1007/s11082-023-05787-5
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DOI: https://doi.org/10.1007/s11082-023-05787-5