Real-Virtual 3D Scene-Fused Integral Imaging Based on Improved SuperPoint

To enrich 3D scenes, a real-virtual fusion-based integral imaging method is proposed. It combines the Softargmax function with Gaussian weighting coefficients for sub-pixel feature point extraction from SuperPoint detection results. SIFT is also used for feature point detection and matching, along with the improved SuperPoint. Subsequently, based on the multi-view 3D reconstruction, the real object is reconstructed into a 3D model. A virtual model is then fused with the 3D reconstructed model of the real object to generate a real-virtual fusion elemental image array based on the display platform's optical parameters. The experimental results demonstrate that the proposed method can optically reconstruct more realistic and vivid real-virtual fusion 3D images. This method can enrich a scene's content, enhance visualization and interactivity, save costs and time, and provide flexibility and customization.