Abstract
In order to weaken the limitation between the adjacent nodes of shooting action teaching image and fully expose the necessary image features, an automatic detection method of shooting action teaching image features based on artificial intelligence is proposed. Starting from the decomposition of shooting teaching action, the practical attribute of shooting teaching image is defined, and then the standardized image detection environment based on artificial intelligence is built according to the action essentials of consistent shooting. On this basis, through the way of extracting the characteristics of teaching image, calculating the characteristic scale value of shooting action, combining with the feature description principle of automatic detection, the design of automatic detection method of shooting action teaching image characteristics is completed. The experimental results show that, compared with the traditional feature method, the UTI traction coefficient between the adjacent nodes of the image increases to 0.33, while the matching time required for detection decreases to 17.5 mm, so as to fully expose the necessary features of the shooting action teaching image.
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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Yu, S., Liu, J. (2020). Automatic Detection of Image Features in Basketball Shooting Teaching Based on Artificial Intelligence. In: Liu, S., Sun, G., Fu, W. (eds) e-Learning, e-Education, and Online Training. eLEOT 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 340. Springer, Cham. https://doi.org/10.1007/978-3-030-63955-6_15
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DOI: https://doi.org/10.1007/978-3-030-63955-6_15
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