Research on 3D Panoramic Display Model of Interior Space Design Based on Intelligent Algorithm

This study proposes a 3D panoramic display model of interior space design based on intelligent algorithm, aiming to realize the intelligent display of interior design schemes through deep convolutional network (DCNN). The model combines DCNN with advanced image processing technology to optimize important elements such as geometric features, lighting effects, material rendering, etc. of the space from multiple dimensions to generate a 3D panorama with strong sense of reality and in line with design requirements. Through training and testing on a large amount of interior design data, the model can accurately identify different elements in the design, including walls, furniture, decorations, etc., and automatically generate corresponding 3D display effects according to the input design requirements. The experimental results show that in typical interior design scenarios, the model can efficiently process the spatial layout and show high accuracy in lighting, material and color restoration. Through data analysis, this study compares the display accuracy and rendering speed of the model in different test sets. The results show that the model has achieved an accuracy rate of 95% in spatial layout accuracy, and the error is within 5% in detail presentation (such as material texture, light and shadow effects), which has high reliability. The simulation test also proves that the model can run stably under various indoor environment settings and provide high-quality display effects.