A Review of 3D Reconstruction Technology for Furniture Modeling: The Integrated Application of Machine Vision and Image Processing

As the core field of cross-integration between machine vision and intelligent manufacturing, 3D reconstruction technology for furniture modeling completes the high-precision digital transformation of furniture entities through the integration of multi-perspective image analysis, point cloud processing methods, and deep learning technical means. This paper systematically reviews the 3D reconstruction technology of furniture based on machine vision and image processing. This research focuses on the data collection, modeling algorithm, and model optimization of three core links, analyzing the contact type and non-contact measurement technology. The paper expounds on the process from sparse reconstruction to end-to-end modeling in deep learning and summarizes the late optimization method. Research shows that although this technology has achieved remarkable results in digital furniture design, virtual display, and cultural heritage protection, it still faces the challenges of complex material reconstruction and balancing precision and efficiency. In the future, the in-depth application and standardized development of this technology in the furniture industry will be promoted through the fusion of multimodal data and intelligent reconstruction.