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Is the perceived agreeability of a face related to the fractal dimension of the face?

机译:一张脸的可感知性是否与该脸的分形维有关?

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Why do people feel happy and good or empathize more, with smiling faces than with expressionless faces? To understand the mechanism involved in the recognition of facial imagery, we evaluated the degree of agreeability for 46 expressionless and smiling facial images obtained from young persons including 84 subjects having no pre-acquired knowledge to the experiments. Each image was presented to every subject and was asked to rank agreeability on a scale from 1 to 10. By using of two types of fractal analysis, i.e., planner and cubic analyses, fractal dimensions of facial images were obtained in order to characterize the complexity of the images. Furthermore, we calculated the local fractal dimensions around parts of eyes and mouths. The results showed a significant difference in the local fractal dimension around mouths between the expressionless and smiling faces. On the other hand, we found a strong correlation between the degree of agreeability and fractal dimensions of whole faces. However, a significant correlation between the local fractal dimensions around mouths and agreeability was not found. These showed that humans recognized face in the wholly way, rather than locally, when we defined the agreeability of facial imagery. These results imply that the fractal dimension obtained in relation to complexity in imagery optically information is useful in characterizing the psychological processes of cognition and awareness.
机译:为什么人们会以微笑的面孔而不是无表情的面孔感到快乐和幸福,或更多的同情心?为了了解面部图像识别所涉及的机制,我们评估了从年轻人中获得的46张无表情和微笑的面部图像(包括84位对实验没有先验知识的人)的同意程度。每幅图像都被呈现给每个对象,并被要求在1到10的等级上对一致性进行排名。通过使用两种类型的分形分析,即计划者分析和三次分析,获得了面部图像的分形维数以表征复杂性。的图像。此外,我们计算了眼睛和嘴巴部分周围的局部分形维数。结果表明,在无表情和笑脸之间,嘴周围的局部分形维数存在显着差异。另一方面,我们发现一致性程度和整张脸的分形维数之间有很强的相关性。但是,没有发现嘴周围的局部分形维数与舒适度之间存在显着的相关性。这些表明,当我们定义面部图像的一致性时,人类会完全而非局部地识别面部。这些结果表明,与图像光学信息的复杂性相关的分形维数可用于表征认知和意识的心理过程。

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