关键词: 电力设备, 清晰度评分, 运动恢复结构, 高斯溅射, 三维重建

Abstract:

To address the issues of missing camera poses in captured images and poor reconstruction quality in 3D modeling of power equipment, a 3D Gaussian splatting 3D modeling method for power equipment based on video sequences wasproposed. Theffmpeg was adopted to extract video frames at a reduced rate, and the Scharr operator was employed to quantify the sharpness of video frames to screen high-quality images for forming an input dataset, ensuring the completeness of equipment poses and the quality of modeling data. Through multi-view feature point extraction and matching, combined with an incremental structure-from-motion algorithm to optimize and generate a sparse 3D point cloud, the geometric foundation of the model was established. 3D Gaussian point clouds constructed from the sparse point cloud were projected onto the image plane using Gaussian splatting, and Gaussian parameters were iteratively optimized by designing a loss function.Differentiable rasterization rendering technology was integrated to generate a photorealistic 3D Gaussian model of power equipment. Experimental results of power equipment modeling indicate that the proposed method can efficiently reconstruct 3D models with rich details and accurate geometryand can form three-dimensional global visualization in virtual space by combining multi-modal monitoring data, possessing important engineering application value.

Key words: power equipment, sharpness score, structure-from-motion, Gaussian splatting, 3D reconstruction