In recent years, the positive impact of virtual reality restorative environments on mental health has been confirmed by numerous studies. This study employed OpenAI's Sora model to create three types of virtual videos with restorative effects: natural, animal, and human environments. Using a facial emotion recognition system built with Keras, OpenCV, and PyQt5, along with the fer2013 facial expression database, and the psychological indicator detection technology of the PAD emotion scale, we conducted an experiment with 24 college students to assess their emotional responses and intensity to these three types of virtual videos in immersive virtual reality scenarios. We also collected subjective and objective physiological data from participants after they experienced different restorative virtual videos and analyzed the data using statistical methods.The results indicate that the three types of virtual videos generated by the Sora model had a positive impact on the participants' emotions. Most participants experienced a significant increase in positive emotions such as gentleness and surprise after watching the virtual natural environment videos, while negative emotions like anxiety and unease were effectively alleviated. Further analysis showed that the animal and natural environments were more effective in emotional regulation than the human environment.This study innovatively investigates the application of AI technology, particularly the Sora model, in virtual reality restorative environments, paving new directions for the exploration and application of AI technology in the emotional regulation of college students and providing new insights for future research.