Vertex Reduction Optimization on Drone Photo-Based 3D Orthomosaic for Smart Parking Virtual Reality Content in the KST Samaun Samadikun Area

Abstract

In creating virtual reality content for smart parking, realistic, lightweight, and easily accessible 3D modeling is essential. A 3D orthomosaic is a 3D model produced from photogrammetric processing of drone aerial photography, and it has been used in this study to create visualizations of the KST Samaun Samadikun environment. However, this 3D orthomosaic has weaknesses because it requires a long data processing time and consists of very many polygon points, so the file size is very large, which can affect VR performance. Therefore, this study was conducted to optimize the 3D orthomosaic model by reducing the number of polygon points without significantly reducing visual quality. The methodology used is Research and development (R & D) through an experimental approach. The stages of aerial photogrammetry using drones include processing aerial photos into 3D orthomosaic models and reducing polygon points, while testing visual quality, file size, loading time, and display performance in a Virtual Reality environment. This study leads to a 3D orthomosaic model that is a compressed version of the original and more computationally efficient without an obvious visual degradation. It is anticipated that the results will be used as a reference in creating realistic, informative, and optimized 3D orthomosaic-based virtual reality content from drones for smart parking. The main generalizable contribution is a normalized asset-optimization and evaluation pipeline; we view the 50% geometry design as a validated practical baseline under the tested conditions rather than an absolute optimum.