基于人工智能的红外热成像面部表情识别
Facial expression recognition in infrared thermal imaging based on artificial intelligence
冯玉涵 1孙剑 2张莉1
作者信息
- 1. 信阳农林学院信息工程学院,河南 信阳 464000
- 2. 信阳师范大学计算机与信息技术学院,河南 信阳 464000
- 折叠
摘要
在红外热成像面部表情识别工作中,由于红外热成像容易受到噪声干扰,处理过程比较繁琐,导致面部表情识别时间成本比较高.针对这一情况,提出基于人工智能的红外热成像面部表情识别.在采集到红外热成像信息后,对其进行灰度化处理和去噪处理,并以双眼作为基准,完成图像的归一化处理,在此基础上,采用人工智能技术按照三庭五眼的比例分割图像,利用空时描述子提取出面部表情特征,以直方图描述面部表情特征,制作面部表情标签,用于识别面部表情.实验结果表明:提出的基于人工智能的红外热成像面部表情识别方法在特征处理上所需时间较少,算法运行效率高,并且能在复杂环境下保持高水平的识别率,在实际应用上表现良好,适合应用到实际项目中.
Abstract
In the work of facial expression recognition in infrared thermal imaging,because infrared thermal ima-ging is easy to be disturbed by noise and the processing process is complicated,the time cost of facial expression recog-nition 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 ex-pression features are described by histograms,and facial expression labels are made.Used to recognize facial expres-sions.The experimental results show that the proposed facial expression recognition method based on artificial intelli-gence takes less time in feature processing,the algorithm has high efficiency,and can maintain a high level of recogni-tion rate under complex environment.It has good performance in practical application,and is suitable for application in practical projects.
关键词
人工智能/红外热成像/面部表情/特征识别/图像预处理Key words
artificial intelligence/infrared thermal imaging/facial expression/feature recognition/image prepro-cessing引用本文复制引用
出版年
2024
NETL
NSTL
万方数据