基于巡检视频的COLMAP图像三维重建效率与精度评估OA
Evaluation of efficiency and accuracy for COLMAP-based image 3D reconstruction through inspection videos
为了提高室内巡检的数字化水平,研究了基于COLMAP的多视图几何重建算法在室内环境下的重建效率和精度.选取7个典型场景并基于巡检视频开展三维重建实验,定义有效图像数量、重叠程度、重建效率、重建精度等指标,实现重建结果的全面评估.结果表明:基于幂律函数的拟合后,重建时间与有效图像数量的1.15次幂成正比;重建效率随图像重叠程度先提高后降低,最优重叠程度约为70%;消费级相机的重建精度为厘米级,同一场景误差受重建密度影响小,不同场景最不利标定情况下的平均绝对(相对)误差为2.29 cm(3.49%).揭示了室内场景图像三维重建效率与精度的一般规律,为更高效的室内巡检影像采集与应用指明了方向.
To improve the digital level of indoor inspection,the reconstruction efficiency and accuracy of the multi-view geometry reconstruction algorithm based on COLMAP in indoor environments were studied.Seven typical scenes were selected,and 3D reconstruction experiments were conducted based on inspection videos.Indices such as the number of effective images,overlap ratio,reconstruction efficiency and accuracy were de-fined to achieve comprehensive evaluation of reconstruction results.The results indicate that after fitting based on the power law function,the reconstruction time is proportional to the 1.15th power of the number of effec-tive images.The reconstruction efficiency first increases and then decreases with the image overlap ratio,and the optimal overlap ratio is approximately 70%.The reconstruction accuracy of consumer-grade cameras is centimeter-level.The error in the same scene is less affected by the reconstruction density,and the average ab-solute(relative)error under the most unfavorable calibration of different scenes is 2.29 cm(3.49%).The general rules of 3D reconstruction efficiency and accuracy for indoor scene images are revealed,pointing out the direction for more efficient image acquisition and application in indoor inspection.
林佳瑞;周绍杰;王宇平;曾申翔;衣子俊;潘鹏
清华大学土木工程系,北京 100084||住房城乡建设部数字建造与孪生重点实验室,北京 100084清华大学土木工程系,北京 100084||住房城乡建设部数字建造与孪生重点实验室,北京 100084国网北京市电力公司,北京 100031清华大学土木工程系,北京 100084清华大学土木工程系,北京 100084清华大学土木工程系,北京 100084||住房城乡建设部数字建造与孪生重点实验室,北京 100084
建筑与水利
室内巡检图像三维重建COLMAP重建精度重建效率
indoor inspectionimage 3D reconstructionCOLMAPreconstruction accuracyreconstruction efficiency
《东南大学学报(自然科学版)》 2026 (2)
183-190,8
国家电网公司科学技术资助项目(5200-202311481A-3-2-ZN).
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