Exploration of Personalized User Experience Optimization in Virtual Reality with Deep Learning

Abstract

With the continuous development of virtual reality technology, optimizing personalized user experience has become crucial, which is the core of enhancing immersion and interactivity. Based on the application of deep learning technology, users' behavior patterns and needs can be efficiently analyzed and optimized, to achieve personalized adjustment of virtual reality experience. This paper describes the main models in deep learning, including convolutional neural networks (CNNS), recurrent neural networks (RNN), short- and long-term memory networks (LSTM), and generative adversarial networks (GANS). Then, it analyzes the status problems of virtual reality personalized user experience, including user adaptability difference, lack of immersion and interaction, comfort and motion sickness. Finally, an optimization strategy based on deep learning is proposed to provide a new technical path for the personalized experience of virtual reality.