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Application of Video Abnormal Behavior Detection Algorithm in Evaluation of Track and Field Teaching and Training Effect

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  • Jian Zhang

    (Sichuan International Studies University, China)

  • Le Yu

    (Sichuan International Studies University, China)

  • Wei Chen

    (Sichuan International Studies University, China)

  • Jing Ya Zhao

    (Sichuan International Studies University, China)

Abstract

With the development of track and field, people pay more and more attention to the quality of classroom teaching of track and field technology, and the evaluation of teaching quality plays a key role in it. In today's educational reform, teaching evaluation plays an important role as an important method to test teachers' teaching and students' learning. With the rapid development of machine learning, especially deep learning, image-based individual abnormal behavior detection technology is becoming more and more mature, but there are still many difficulties to be solved in video-based group abnormal behavior detection technology. Therefore, it is necessary to study the detection algorithm. Based on machine vision theory, image processing theory and video analysis technology, this paper studies three key technologies involved in human abnormal behavior detection in video: moving target detection, moving target tracking and abnormal behavior detection.

Suggested Citation

  • Jian Zhang & Le Yu & Wei Chen & Jing Ya Zhao, 2024. "Application of Video Abnormal Behavior Detection Algorithm in Evaluation of Track and Field Teaching and Training Effect," International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), IGI Global, vol. 19(1), pages 1-18, January.
    • Handle: RePEc:igg:jwltt0:v:19:y:2024:i:1:p:1-18
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