3D Face Geometry Optimization Using Artificial Intelligence and Computer Graphics

Abstract

Human face plays an indispensable role in emotional expression and information exchange, which attracts large number of researchers to study face recognition. Nowadays, with the rapid development of computer graphics, artificial intelligence, and other technologies, the ability of the human vision system to recognize facial expressions and facial organs is enhanced. More and more experts think about how to make the computer vision system have this capability. By combining artificial intelligence and computer graphics, this paper studies how to optimize the 3D face network model and extract geometric features for 3D face recognition. We propose a 3D face network model based on Poisson equation to realize face hole recognition and boundary preprocessing. Besides, we also establish the 3D face surface equation and equal face value extraction and enhance the face feature based on facial semantic information. We study the hole repair of 3D face model based on Poisson equation integrating semantic information and achieve the purpose of optimizing the 3D face model. After the optimization, the method is compared with mesh repair and Poisson repair, which demonstrates that our Poisson-based 3D face hole repairing model obtains the best results among compared methods.

Research on Face Attribute Recognition Technology Based on Fine-Grained Features

“…From Eq. ( 10), we obtain features 12 , YY and 3 Y at each scale with scaled attention weights, and compared with the initial input features 12 , XX and 3 X , i Y exchanges information with neighboring features of different sizes, which strengthens the ability to characterize the expression features under fine-grained conditions, such as the key parts of the eyes, the corners of the mouth, and the eyebrows. The introduction of the multiscale attention mechanism strengthens the connection between features of different scales, enriches the semantic information of high-dimensional features, and at the same time, the high-dimensional features can also feed back effective information to the low-dimensional features, which is conducive to the network's ability to capture local key information.…”

“…In this era of booming artificial intelligence, a large amount of training data and modeling algorithms are springing up in academia and industry, utilizing the innate advantages of AI to enhance accurate prediction and rapid response to various emergencies. Therefore, the issue of mining facial features deeply to improve the performance of face attribute recognition as well as recognition fairness is of great practical significance [10][11][12].…”

“…12 , YY and 3 Y of different scales need to be fused to the same scale by convolution and deconvolution before performing the concat operation. Empirically, it can be considered to convolve12 , YY to 3 Y this scale, but in the fine-grained case, the probability of losing key local features in the convolution pooling process is higher, in this paper, the 1 Y convolution shrinks the scale and the 3 Y inverse convolution enlarges the scale to 2 Y the same scale, which increases the computational amount, but retains the fine-grained features as much as possible, and paves the way for the subsequent work of expression categorization.…”

Artificial Intelligence in Plastic Surgery: Insights from Plastic Surgeons, Education Integration, ChatGPT’s Survey Predictions, and the Path Forward

“…14,15 AI algorithms can analyze large datasets of facial images, three-dimensional models, and medical records to identify patient-specific factors that affect surgical outcomes. 16,17 One of the most significant benefits of AI in plastic surgery is its ability to improve surgical accuracy and precision, 18 and that it can assist surgeons in identifying and locating critical structures, reducing the risk of damage to surrounding tissues and improving surgical outcomes, for example, in facial reconstruction and breast reconstruction. 19 Regarding specific areas of impact, respondents expressed their opinions on the potential influence of AI in different subspecialties of plastic surgery.…”