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On March 17, NetEase Smart News reported on a groundbreaking study that reveals how men and women smile differently. This difference has led to the development of artificial intelligence capable of automatically determining gender based on a person's smile.
While previous techniques have focused on static images and fixed facial features, this new research from Bradford University marks a significant shift. It’s the first time that dynamic facial movements—specifically smiles—have been used to distinguish between genders.
Under the leadership of Professor Hassan Ugail, the research team placed 49 markers on participants' faces, focusing on key areas like the eyes, mouth, and nose. They analyzed the subtle movements of deep facial muscles during a smile, measuring factors such as the distance between points, the fluidity of movement, and the speed at which different parts of the face change.
The team then compared these patterns between men and women. The results showed that women’s smiles are more expressive and flexible, with wider mouth movements and more pronounced lip shapes.
Professor Ugail commented, “It’s interesting—women are often seen as more skilled at expressing smiles, and our findings back this up. Their smiles tend to be brighter and more open, with larger mouth and lip movements compared to men.â€
To test their method, the researchers developed an algorithm and applied it to 109 video clips of people smiling. The system was able to accurately determine the gender of the individuals in 86% of cases.
“We used a basic machine learning model for this study, just to test the concept,†said Professor Ugail. “With more advanced AI, we believe the accuracy could be significantly improved.â€
The research not only aims to enhance machine learning capabilities but also raises important questions about future applications. For example, how will the system handle transgender expressions? And what impact does plastic surgery have on its accuracy?
“Since the system measures the movement of deep facial muscles, even if someone changes their appearance through surgery, the underlying dynamics of their smile should remain the same,†explained Professor Ugail.
This technology could potentially become the next major biometric tool, as it relies on unique, hard-to-mimic dynamic features rather than static physical traits.
The study was originally published in *The Visual Computer*, an international journal dedicated to computer graphics and vision.
(Source: ScienceDaily | Compilation: NetEase Smart Studio | Engagement: nariiy)
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