Face recognition technology is once again making headlines. Recently, in a middle school simulation exam in Beijing, students are required to "brush their faces" for identification. This trend has gained attention since the introduction of Face ID on the iPhone X, sparking widespread interest and even a "sharp face" craze. However, despite its growing popularity, brush face technology is still in its early stages, with immature technology and user experience. It's clear that this field is still facing many challenges on the road to technological advancement, but we remain hopeful that it will eventually shine brightly in the tech world.
From checking the housing fund to attendance and security checks, more and more daily activities are now associated with "face scanning." Even in public restrooms at Ritan Park in Beijing, toilet paper dispensers require facial recognition. With the integration of face recognition into government services, proving your identity in the future may no longer require lengthy paperwork — just a quick scan.
Chinese enthusiasm for face recognition is also evident in the investment landscape. Companies like Face++ and Shangtang Technology have raised significant funding, with Face++ securing $100 million in Series C financing and Shangtang raising $410 million in a B-round round, placing them among AI unicorns.
The tipping point for commercial application of face recognition seems to be approaching. While the iPhone X might not have fully realized its potential, it has definitely brought more attention to the technology.
There are three main algorithms used in face recognition: 1:1, 1:N, and N:N. 1:1 is the most basic form, where a person’s image is compared against a stored photo to confirm identity. This is commonly seen in mobile phone unlocking, online payments, and ticket purchases. 1:N is used for searching or identifying someone from a large database, often applied in security systems. N:N involves comparing multiple faces simultaneously, which is more complex.
Despite its rapid development, face recognition is not yet perfect. China leads in practical applications, while the U.S. and Europe are strong in research. Many Chinese tech companies are focusing on quick wins rather than long-term innovation. Startups often overemphasize technology without considering real-world scenarios.
Face recognition still faces challenges such as poor lighting, different angles, and disguises. A recent TV show demonstrated how easy it is to fool systems using photos and 3D models. Experts warn that current systems lack robust living detection, making them vulnerable to attacks.
For startups, success depends not just on technology, but on understanding real-world applications. Investors are looking for companies that can solve practical problems, not just develop better algorithms. Giants have advantages in data and resources, but startups can thrive by focusing on niche markets and deep industry knowledge.
While high-accuracy areas like financial payments remain challenging, there's optimism about less demanding fields like entertainment and retail. As the technology matures, face recognition could become a key part of everyday life, transforming how we interact with the digital world.
The Smart series of Android Tablet PC can be used as self-service payment terminals in shops and restaurants. Hengstar Smart digital signage tablets are also widely used in school education, shopping malls, supermarkets, restaurants, movie theaters, hotels, retail stores, etc. A front camera that supports facial recognition has also been added to certain specific applications, so users can get a personalized experience through our Smart Tablet PC.
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