Design of Real Time Display Algorithm for Naked Eye 3D Images Based on Binocular Vision

Vision is the most direct and effective way for human beings to perceive the outside world and obtain information. The naked-eye 3D image display technology is a multimedia technology that can provide pictures with depth information, and can give people a realistic and 3D feeling. Image matching is an important research direction in the field of computer vision, which has important theoretical and application value. Traditional image matching methods are mostly based on feature descriptors and similarity measurement methods, which are difficult to deal with complex scenes and large-scale data. This article aims at designing a real-time display algorithm of naked-eye 3D images based on binocular vision, and proposes an image matching model based on binocular vision and convolutional neural network (CNN). The design of this algorithm will involve image acquisition, feature extraction and matching, fusion and display. The model test results show that the image matching accuracy and retrieval efficiency of this method are obviously improved compared with the traditional GAN model. This method has good performance and advantages in dealing with complex scenes and large-scale data, and provides new ideas and methods for the research and application in the field of computer vision.