Face recognition from range data by structural analysis
Syntactic and structural pattern recognition
Fractals everywhere
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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 favorability 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 favorability 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 favorability and fractal dimensions of whole faces. However, a significant correlation between the local fractal dimensions around mouths and favorability was not found. These showed that humans recognized face in the wholly way, rather than locally, when we defined the favorability 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.