| 刘小燕,郭群,龚军辉,孙彪,刘敏.基于面部红外热图的恐惧情绪识别[J].电子测量与仪器学报,2017,31(3):353-360 |
| 基于面部红外热图的恐惧情绪识别 |
| Recognition of fearful emotion based on facial infrared thermal images |
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| DOI：10.13382/j.jemi.2017.03.004 |
| 中文关键词: 情绪识别 红外热图 传热模型 血液灌注 标准偏差 |
| 英文关键词:emotion recognition infrared thermal images heat transfer model blood perfusion standard deviation |
| 基金项目:国家自然科学基金(61374149)、教育部博士点基金(20130161110010)、湖南省研究生科研创新项目(CX2016B128)资助 |
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| Author | Institution |
| Liu Xiaoyan | College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; |
| Guo Qun | College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; |
| Gong Junhui | 1. College of Electrical and Information Engineering, Hunan University, Changsha 410082, China;
2. College of Electrical and Information Engineering, Hunan Institute of Engineering, Xiangtan 411101, China |
| Sun Biao | College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; |
| Liu Min | College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; |
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| 中文摘要: |
| 恐惧情绪是人体应对外界刺激的一种反应，其产生会引起人体面部皮肤温度的变化。根据红外热图反映物体表面温度分布的原理，提出了一种基于面部红外热图对恐惧情绪进行识别的方法。首先采用指数函数拟合方法对现有的传热模型进行简化，将红外热像仪所采集的面部红外热图转化为血液灌注伪彩色图，寻找感兴趣区域(前额区域)；然后，提取感兴趣区域的血液灌注变化曲线的相关特征(斜率、置信度、均值、标准偏差)，并采用斯皮尔曼相关系数分析其与受试对象恐惧程度自评分之间的相关性；最后采用与恐惧程度自评分相关性最高的标准偏差对受试对象进行恐惧情绪的识别。实验结果表明，当受试对象产生恐惧情绪时，前额区域的血液灌注呈现出明显的下降趋势，这与现有的恐惧情绪研究结论一致；血液灌注值的标准偏差可以作为恐惧情绪识别的主要特征(阈值0.14)。采用本文所提出的方法，对28例样本进行测试，受试对象恐惧情绪的识别准确率达到85.7%，具有较高的可靠性。 |
| 英文摘要: |
| Fearful emotion is a response to the external stimuli of human. The generation of fearful emotion could lead to the change in the facial skin temperature. According to the principle of infrared thermal images reflecting the temperature distribution on the surface of objects, a method based on infrared thermal images is proposed to recognize the fearful emotion. Firstly, a heat transfer model is simplified by curving fitting of exponential function, and the facial infrared thermal image is converted into the blood perfusion pseudo color image to find the regions of interest (forehead region). Then, features of the blood perfusion change curves are extracted (slope, confidence coefficient, mean value, and standard deviation), and the correlation between the features and the self assessment score of the fearful emotion is analyzed using Spearman correlation coefficient. Finally, the standard deviation which is highly related to the self assessment score is applied to recognize the fearful emotion of the subject. The experimental results show that there is an obvious decrease in the blood perfusion of forehead region in the presence of fearful emotion, which is consistent with observations of previous studies, and the standard deviation (with a threshold of 0.14) of the blood perfusion values is a main feature for recognition of the fearful emotion. The proposed method is demonstrated to be satisfactory and reliable with an accuracy of 85.7% for all the 28 tested subjects. |
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