The integrated application of AI (artificial intelligence) technology extends to the field of anti-aging. At the AMWC World Beauty and Anti-Aging Conference held on October 18, how AI technology is applied to beauty and anti-aging has become one of the hot topics.
Fu Siying, Meitu Yifufu Intelligent Drive Strategy Director, shared that currently, AI has been combined with big data to be applied in the anti-aging field. He said that by analyzing the data of the study population, some key time points of aging were discovered. Take common facial lines as an example. Mouth lines, glabellar lines and tear troughs usually begin to appear in the late 30s, but do not stabilize until the late 50s.
"Compared with traditional naked-eye observation of skin conditions, AI skin measurement can automatically extract skin features, process high-dimensional and complex image data, and have the ability to continuously improve and evolve through large-scale data continuous training." Fu Siying said.
Beauty and anti-aging is becoming a huge consumer market. iiMedia Consulting data shows that the market size of China's cosmetics industry will reach 516.90 billion yuan in 2023, of which the market size in the anti-aging field will be 73.98 billion yuan. Globally, the global anti-aging market will reach US$250.3 billion (approximately RMB 1,775.553 billion) in 2023, a year-on-year increase of 7.8%; it is expected to reach US$294.7 billion (approximately RMB 2,090.513 billion) in 2025.
At the above-mentioned skin beauty forum, Meitu Yifu Skin Detection and Digital Standards Joint Laboratory shared its latest progress in the field of AI skin detection, especially in anti-aging, with the theme of "Application of AI Technology in the Field of Anti-Aging" A breakthrough in applications.
Fu Siying, director of Meitu Yifufu Intelligent Drive Strategy, mentioned in her sharing that AI has been combined with big data to be applied in the anti-aging field. He said, “Because AI can convert originally unstructured skin images and three-dimensional structures into structured data, it provides scientific researchers and skin care experts with data information that is convenient for research and reference. Through such transformation, it can Understand the process of skin aging more systematically, establish a database of skin aging characteristics, and provide a solid data foundation for subsequent anti-aging research and product development."
Fu Siying shared the results of an AI skin measurement data analysis of 400,000+ people. He said that by analyzing the data of the study population, some key time points of aging were discovered. Taking common facial lines as an example, lines at the corners of the mouth, glabellar lines and tear troughs usually begin to appear in the late 30s, but do not stabilize until the late 50s. Nasolabial folds and crow's feet gradually begin to increase relatively early at the age of 26, but reach a stable state in the early 50s. These data provide important basis for skin care brands, medical beauty brands, etc. to formulate anti-aging strategies.
"Compared with traditional naked-eye observation of skin conditions, AI skin measurement can automatically extract skin features, process high-dimensional and complex image data, and have the ability to continuously improve and evolve through large-scale data continuous training." Fu Siying said.
Wang Fudi, chief researcher of Meitu Yifu Skin Detection and Digital Standards Joint Laboratory, shared another set of data analyzed through AI skin measurement - based on data cutting of different parts of the face, using deep learning methods for aging prediction. It was found that the eye area had the most accurate age prediction in areas such as the forehead, eyes, nose, cheeks and mouth. Its average predicted value deviated from the true value by only 2.83 years.
Wang Fudi said that from the research results, it can be seen that the eyes are an important area of aging and are also the most focused facial part when people communicate during traffic. The aging changes in this area will give people an intuitive and impactful impression.
In addition to the above-mentioned epidemiological studies, Wang Fudi's team also linked the changes in the three-dimensional structure of the face with the aging characteristics of the two-dimensional layer. His team found that morphological changes in the mouth were significantly related to labial grooves, and then confirmed the causal relationship between the two through genetic data. This is the first study to verify the relationship between facial morphology and facial aging from a genetic perspective. These research results will not only promote the application of AI technology in the field of anti-aging, but also provide new directions for the development of personalized skin care and medical beauty industries.
On August 8 this year, the group standard "Human Skin Age-Specific Anti-Aging Evaluation Standard Table" issued by the China Anti-Aging Promotion Association and formulated with the participation of Meitu Yifu was released and implemented. This group standard clearly marks the range and rate of changes in facial skin aging characteristics at each age stage, which has strong practical significance. After the subject undergoes skin testing, researchers can use this standard to understand whether the subject's facial condition is at a normal level and what the trend of facial aging will be in the next period of time.
In recent years, the use of AI technology and big data in the industry has also shown a gradual upward trend. Data shows that the global skin analyzer market size will be US$1.358 billion in 2022 and will reach US$6.9903 billion by 2029, with a compound annual growth rate of 26.4% during the forecast period. Other survey data shows that consumers also have high trust in the comprehensiveness of skin measurement information and the accuracy of results provided by Al Skin Tester.