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A deep learning algorithm for fast motion video sequences based on improved codebook model

  • S.I.: Artificial Intelligence Technologies in Sports and Art Data Applications
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Abstract

Fast motion video sequence processing is quite difficult. In order to improve the effect of fast motion video sequence processing, this paper improves the traditional codebook model algorithm and proposes an improved codebook model algorithm. Moreover, this paper analyzes and summarizes the development and application of background modeling-based methods in moving target detection, and points out the applicability and limitations of traditional methods, which lays the foundation for the further research of moving target detection based on background modeling in the complex background. In addition, this paper analyzes the characteristics of fast motion videos, and combines deep learning algorithms to improve the feature recognition effect of fast motion video sequences. Finally, this paper verifies the effect of this method through experimental research. Through experimental research, we know that the improved algorithm proposed in this paper can realize effective processing of fast motion video, and can improve the feature recognition effect of motion video frames.

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Funding

The Research is Supported by: 1. Henan Province Scientific and Technological Research Project "Design of Rangefinder for High-precision Field Competitions Based on the Internet of Things" in 2019 (Project Number: 192102310292); 2. This work was supported in part by the National Natural Science Foundation of China under Grants U1804152.

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Authors and Affiliations

  1. Department of Physical Education, Henan University of Engineering, Zhengzhou, 450001, China

    Kai Zhou

  2. School of Physical Education (Main Campus), Zhengzhou University, Zhengzhou, 450001, China

    Zhendong Zhang & Rui Yuan

  3. Department of Marine Sports, Pukyong National University, Busan, 48513, Korea

    Rui Yuan

  4. School of Information Engineering, Zhengzhou University, Zhengzhou, 450001, China

    Enqing Chen

Authors
  1. Kai Zhou
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  2. Zhendong Zhang
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Corresponding author

Correspondence to Rui Yuan.

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The authors declared that they have no conflicts of interest to this work. We declare that we do not have any commercial or associative interest that represents a conflict of interest in connection with the work submitted.

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Zhou, K., Zhang, Z., Yuan, R. et al. A deep learning algorithm for fast motion video sequences based on improved codebook model. Neural Comput & Applic 35, 4353–4368 (2023). https://doi.org/10.1007/s00521-022-07079-7

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  • DOI: https://doi.org/10.1007/s00521-022-07079-7

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