Abstract:
Fast, high-precision texture maps and high-frame-rate level of detail (LOD) generation for realistic 3-D models are foundational data infrastructures for smart cities. Ho...Show MoreMetadata
Abstract:
Fast, high-precision texture maps and high-frame-rate level of detail (LOD) generation for realistic 3-D models are foundational data infrastructures for smart cities. However, LOD generation faces three main issues: reduced model accuracy from mesh simplification, inefficient texture memory utilization, and browsing lag with detail loss. This article proposed a novel LOD rendering method with multilevel structure-keeping mesh simplification and fast texture alignment for realistic 3-D models. First, a multilevel structure-keeping mesh simplification method with mesh segmentation and vertex classification was used to generate a simplified mesh with high-precision structure preservation. Second, a fast texture alignment method was proposed that uses segmentation information and least-squares conformal map (LSCM) parameterization to acquire texture blocks. The method integrated integral images and a precise multitemplate strategy to align texture blocks, to obtain texture maps with high completeness and high occupancy. Finally, by integrating these methods, an LOD generation method with fast multilevel pyramid construction and adaptive tree organization is proposed. This method achieved high-precision multilevel structure keeping, along with a high-occupancy rate of texture maps, facilitating a high frame rate for LOD model construction. Compared with quadratic error function (QEF), quadratic error metrics (QEMs), low-poly, computational geometry algorithms library (CGAL), and Nvdiffrec, the proposed mesh simplification algorithm demonstrated average accuracy improvements of 12.1%, 24.2%, 57.1%, 17.9%, and 3.2%, respectively. Compared with open multi-view environment (OpenMVE), ContextCapture, and Xatlas, the proposed texture alignment algorithm achieved average occupancy improvements of 27.74%, 11.89%, and 4.80%, respectively. Compared with the state-of-the-art ContextCapture and Smart3D, the proposed method for browsing large-scale realistic 3-D models increased the...
Published in: IEEE Transactions on Geoscience and Remote Sensing ( Volume: 62)