Feature Line Extraction from 3D Model of Oblique Photogrammetry Based on Multi-Objective Weighted Shortest Path
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摘要: 针对倾斜摄影测量三维重建得到的三维模型在地物拐角棱线处结构粗糙、噪声较大、规则性缺失，难以快速准确提取出理想特征线的难题，提出一种基于多目标加权最短路径的特征线提取方法. 首先对模型进行预处理，使模型具有完整、连续的拓扑结构，并将模型以有向图结构进行组织；其次顾及距离、方向和三角网变化趋势计算权重，约束迪杰斯特拉算法获取最短路径得到特征线；最后，为了修复模型特征不明显的棱线区域，设计了一种棱线修复算法. 研究结果表明：与交互式方法对比，本文方法效率高，只需选取两个特征点指定目标，同时提取结果不依赖人工经验，客观性强；与基于边和面的自动提取方法相比，本文方法受噪声影响小，能在简单交互下提取到指定特征线.Abstract: Oblique photogrammetry 3D models suffer from coarse structure, high noise and regularity deficiency in corner or ridge regions, which make it difficult to extract feature lines quickly and accurately from these regions. To deal with this problem, a method of feature line extraction from 3D model of photogrammetry based on multi-objective weighted shortest path is proposed. First, the model is pre-processed to build a complete and continuous topological structure, and organized as a weighted directed graph. Then, considering the distance, direction and the change trend of the triangulation, the weights are calculated; the Dijkstra algorithm is constrained to obtain the shortest path to get the feature lines. Finally, using the feature line extraction results, a method is proposed to repair the regions without distinct features. Results show that compared with the interactive method, the proposed method is efficient and only need select two feature points to specify the target. At the same time, the extraction results do not rely on artificial experience and are highly objective. Compared with the automatic extraction method based on edges and faces, this method is less affected by noise, and can extract the specified feature line under simple interaction.
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Key words:
- 3D model /
- photogrammetry /
- feature extraction /
- directed graphs /
- shortest path
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图 1 基于多目标加权最短路径的倾斜摄影测量三维模型特征线提取算法流程
Figure 1. Flow of feature line extraction from 3D model of oblique photogrammetry based on multi-objective weighted shortest path
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