High-quality 3D tree mesh model generation from point clouds

High-fidelity 3D tree mesh models have broad applications in virtual geographic environments, forest ecology, and digital entertainment. Although laser point clouds provide precise data, existing point cloud-based methods struggle with accuracy and completeness due to tree structural complexity, leaf occlusion, and data gaps. To address these challenges, we propose a novel framework that integrates data-driven and morphology-knowledge-driven techniques for generating high-quality tree mesh models with accurate trunk and overall crown morphology.

高保真三维树木网格模型在虚拟地理环境、森林生态学与数字娱乐领域具备广泛应用前景。尽管激光点云（laser point clouds）能够提供高精度数据，但受树木结构复杂、叶片遮挡以及数据缺失等因素制约，现有基于点云的建模方法难以兼顾精度与完整性。为应对上述挑战，本文提出一种融合数据驱动与形态学知识驱动技术的新型框架，能够生成兼具精确树干形态与完整树冠结构的高质量三维树木网格模型。