An Empirical Study of Portrait Rights on Emotional Evolution in Virtual Social Scenarios by Transformer and Cloud Computing

Abstract

Facial expression recognition technology can improve the possibility of fugitives and persons subject to execution being discovered by public security and judicial personnel in the virtual world, thereby improving the actual effectiveness and credibility of the law. There may also be a risk of portrait rights infringement with this technology, and the user of the technology needs to inform the person whose facial expression is being extracted in advance and obtain permission. With the rapid progression of deep learning and artificial intelligence, 3D facial expression modeling has garnered increased significance in computer vision and graphics. We propose an innovative approach combining Transformer models with cloud computing to simulate facial expression evolution in virtual social environments. Leveraging Transformer-based feature extraction, our model integrates emotional cues from various modalities to accurately capture subtle changes over time.