Young G C, Dey S, Rogers A D, Exton D
Department of Zoology, University of Oxford, Oxford, United Kingdom.
Operation Wallacea, Wallace House, Lincolnshire, United Kingdom.
PLoS One. 2017 Apr 13;12(4):e0175341. doi: 10.1371/journal.pone.0175341. eCollection 2017.
We present a method to construct and analyse 3D models of underwater scenes using a single cost-effective camera on a standard laptop with (a) free or low-cost software, (b) no computer programming ability, and (c) minimal man hours for both filming and analysis. This study focuses on four key structural complexity metrics: point-to-point distances, linear rugosity (R), fractal dimension (D), and vector dispersion (1/k). We present the first assessment of accuracy and precision of structure-from-motion (SfM) 3D models from an uncalibrated GoPro™ camera at a small scale (4 m2) and show that they can provide meaningful, ecologically relevant results. Models had root mean square errors of 1.48 cm in X-Y and 1.35 in Z, and accuracies of 86.8% (R), 99.6% (D at scales 30-60 cm), 93.6% (D at scales 1-5 cm), and 86.9 (1/k). Values of R were compared to in-situ chain-and-tape measurements, while values of D and 1/k were compared with ground truths from 3D printed objects modelled underwater. All metrics varied less than 3% between independently rendered models. We thereby improve and rigorously validate a tool for ecologists to non-invasively quantify coral reef structural complexity with a variety of multi-scale metrics.
我们提出了一种方法,可使用标准笔记本电脑上的单个经济高效的相机来构建和分析水下场景的3D模型,该方法具有以下特点:(a)使用免费或低成本软件;(b)无需计算机编程能力;(c)拍摄和分析所需的人工时间最少。本研究聚焦于四个关键的结构复杂性指标:点对点距离、线性粗糙度(R)、分形维数(D)和矢量离散度(1/k)。我们首次对未校准的GoPro™相机在小规模(4平方米)下通过运动恢复结构(SfM)生成的3D模型的准确性和精度进行了评估,并表明它们能够提供有意义的、与生态相关的结果。模型在X-Y方向的均方根误差为1.48厘米,在Z方向为1.35厘米,线性粗糙度(R)精度为86.8%,分形维数(D,尺度为30 - 60厘米时)精度为99.6%,分形维数(D,尺度为1 - 5厘米时)精度为93.6%以及矢量离散度(1/k)精度为86.9%。线性粗糙度(R)的值与现场使用链和卷尺测量的值进行了比较,而分形维数(D)和矢量离散度(1/k)的值与水下建模的3D打印物体的地面真值进行了比较。在独立渲染的模型之间,所有指标变化均小于3%。我们从而改进并严格验证了一种工具供生态学家使用各种多尺度指标以非侵入性方式量化珊瑚礁结构复杂性。