Laser Journal, Volume. 45, Issue 12, 245(2024)

Facial expression recognition in infrared thermal imaging based on artificial intelligence

FENG Yuhan1... SUN Jian2 and ZHANG Li1,* |Show fewer author(s)
Author Affiliations
  • 1School of Information Engineering, Xinyang Agriculture and Forestry University, Xinyang Henan 464000, China
  • 2College of Computer and Information Technology, Xinyang Normal University, Xinyang Henan 464000, China
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    In the work of facial expression recognition in infrared thermal imaging, because infrared thermal imaging is easy to be disturbed by noise and the processing process is complicated, the time cost of facial expression recognition is relatively high. In view of this situation, an artificial intelligence-based facial expression recognition based on infrared thermal imaging is proposed. After collecting the infrared thermal imaging information, grayscale processing and denoising are carried out, and the two eyes are used as the benchmark to complete the normalization of the image. On this basis, artificial intelligence technology is adopted to segment the image according to the proportion of three chambers and five eyes, and facial expression features are extracted by using space-time descriptors, and facial expression features are described by histograms, and facial expression labels are made. Used to recognize facial expressions. The experimental results show that the proposed facial expression recognition method based on artificial intelligence takes less time in feature processing, the algorithm has high efficiency, and can maintain a high level of recognition rate under complex environment. It has good performance in practical application, and is suitable for application in practical projects.

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    FENG Yuhan, SUN Jian, ZHANG Li. Facial expression recognition in infrared thermal imaging based on artificial intelligence[J]. Laser Journal, 2024, 45(12): 245

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    Paper Information

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    Received: Feb. 20, 2024

    Accepted: Mar. 10, 2025

    Published Online: Mar. 10, 2025

    The Author Email: Li ZHANG (zhangli190227@163.com)

    DOI:10.14016/j.cnki.jgzz.2024.12.245

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