Guided Next Best View for 3D Reconstruction of Large Complex Structures
Guided Next Best View for 3D Reconstruction of Large Complex Structures
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DOI：
10.3390/rs11202440
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发表时间：
2019-10-01
期刊：
影响因子：
5
通讯作者：
Zweiri, Yahya
中科院分区：
文献类型：
--
作者：
Almadhoun, Randa;Abduldayem, Abdullah;Zweiri, Yahya
提出了一种基于仿形阶段和效用函数的次佳视图（NBV）方法，用于无人机（UAV）的三维重建。所提出的方法执行初始扫描，以建立一个粗略的模型，稍后用于提高覆盖的完整性和减少飞行时间的结构。然后，启动更彻底的NBV过程，利用粗糙模型来创建感兴趣结构的密集3D重建。所提出的方法利用反射对称的功能，如果它存在于初始扫描的结构。所提出的NBV方法实现了一个新的效用函数，它由四个主要组成部分：信息理论，模型密度，行驶距离，和预测措施的基础上对称的结构。该系统比经典的信息增益方法具有更高的密度，熵减少和覆盖完整性。仿真和真实的实验结果表明了该方法的有效性和实用性。
In this paper, a Next Best View (NBV) approach with a profiling stage and a novel utility function for 3D reconstruction using an Unmanned Aerial Vehicle (UAV) is proposed. The proposed approach performs an initial scan in order to build a rough model of the structure that is later used to improve coverage completeness and reduce flight time. Then, a more thorough NBV process is initiated, utilizing the rough model in order to create a dense 3D reconstruction of the structure of interest. The proposed approach exploits the reflectional symmetry feature if it exists in the initial scan of the structure. The proposed NBV approach is implemented with a novel utility function, which consists of four main components: information theory, model density, traveled distance, and predictive measures based on symmetries in the structure. This system outperforms classic information gain approaches with a higher density, entropy reduction and coverage completeness. Simulated and real experiments were conducted and the results show the effectiveness and applicability of the proposed approach.