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Cognitive psychological analysis based on multilayer semantics of web video and feature extraction of psychological images

  • Xin-di GuoEmail author
Article
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Abstract

In order to improve the accuracy of psychological analysis by extracting network video and image features, it is difficult to analyze video semantics and blur the boundaries of psychological images. In order to solve the above problems, this paper proposes a cognitive psychological analysis algorithm based on multi-layer semantics and feature extraction of psychological images in network video. Firstly, this algorithm proposes a hierarchical semantic description of network video. It can be divided into two stages: network video layering and semantic template based on layering. Then, the algorithm divides the mental image into multiple segmentation. Each segmentation focuses on the impact of different network video and different types of image features on data convergence. At the same time, interface blurring processing mechanism and image data semantic hierarchical classification method are designed. Finally, the simulation results show that the proposed algorithm is credible, feasible and effective.

Keywords

Cognitive psychological analysis Multilayer video semantics Feature extraction Psychological images 

Notes

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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Psychology, School of Basic Medicine and Forensic PathologyBaotou Medical CollegeBaotouChina

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