Lu Yunhong, Li Xiangnan, Li Mingliang
School of Computer and Control Engineering, Yantai University, Yantai 264005, China.
Yantai Science and Technology Innovation Promotion Center, Yantai 264005, China.
Biomimetics (Basel). 2024 Sep 29;9(10):590. doi: 10.3390/biomimetics9100590.
In practical applications, integrating three-dimensional models of bionic devices with simulation systems can predict their behavior and performance under various operating conditions, providing a basis for subsequent engineering optimization and improvements. This study proposes a framework for characterizing three-dimensional models of objects, focusing on extracting 3D structures and generating high-quality 3D models. The core concept involves obtaining the density output of the model from multiple images to enable adaptive boundary surface detection. The framework employs a hierarchical octree structure to partition the 3D space based on surface and geometric complexity. This approach includes recursive encoding and decoding of the octree structure and surface geometry, ultimately leading to the reconstruction of the 3D model. The framework has been validated through a series of experiments, yielding positive results.
在实际应用中，将仿生设备的三维模型与仿真系统集成，可以预测它们在各种运行条件下的行为和性能，为后续的工程优化和改进提供依据。本研究提出了一个用于表征物体三维模型的框架，重点是提取三维结构并生成高质量的三维模型。核心概念是从多个图像中获取模型的密度输出，以实现自适应边界表面检测。该框架采用分层八叉树结构，根据表面和几何复杂度对三维空间进行划分。这种方法包括八叉树结构和表面几何的递归编码和解码，最终实现三维模型的重建。该框架已通过一系列实验得到验证，取得了积极的成果。
