基于面部视觉特征的精神疲劳可拓辨识模型

Mental Fatigue Recognition Extension Model Based on Facial Visual Cues

在基于面部视觉特征的精神疲劳辨识中,被测者的生活、工作负担和睡眠质量等背景信息对于准确辨识疲劳具有非常重要的作用,但却无法直接从面部视频中获取。为此,以可拓学的理论和思想方法为基础,结合经典数学的一些方法和现有的计算机视觉技术,提出并构建了一种全新的精神疲劳可拓辨识模型。该模型基于矛盾转化的思想,将无法直接从面部视频中获取到的背景信息转化为与之相关联的可以直接从面部视频中获取到的面部疲态的计算,并融合现有的面部疲劳特征进行精神疲劳辨识。实验结果验证了该模型的有效性。

The background information, such as life burden, work load and sleep quality, plays a very important role m mental fatigue recognition based on facial visual cues, however, they cannot be directly extracted from facial video. Based on the theory, ideals and methods of extenics, combined with some classic mathematical methods and existing computer vision technology, this paper proposed a new mental fatigue extension recognition model. Based on the idea of contradic- tions transformation, the background information which cannot be directly extracted from the facial video is translated into the corresponding facial fatigue appearance in the model, and the facial fatigue appearance can be directly extracted from the facial video. And this model also proposes a fusion approach for existing facial fatigue visual cues and facial fa- tigue appearance to recognize mental fatigue. The experimental results verify the validity of the model.