Research on 3D surface reconstruction and body size measurement of pigs based on multi-view RGB-D cameras

周长(图论) 点云 长方体 计算机视觉 RGB颜色模型 人工智能 体表 计算机科学 点(几何) 曲面重建 投影(关系代数) 曲面(拓扑) 数学 算法 几何学 组合数学
作者
Shuai Shi,Ling Yin,Liang Shihao,Zhong Haojie,Tian Xuhong,Caixing Liu,Sun Aidong,Hanxing Liu
出处
期刊:Computers and Electronics in Agriculture [Elsevier]
卷期号:175: 105543-105543 被引量:68
标识
DOI:10.1016/j.compag.2020.105543
摘要

Body measurement is an important technique to acquire the livestock body parameters for precision agriculture and effective management of livestock. Traditionally, the livestock body parameters are often manually measured, which suffers from several drawbacks, including unstable accuracy, low efficiency, difficulty in measuring complex parameters, and potentially negative influence on animal welfare. Considering this, this paper presents a 3D surface reconstruction and body size measurement system based on multi-view RGB-D cameras. We use Kinect depth cameras to obtain the point clouds of the freely walking pigs from three different views (i.e., upper-view, left-view and right-view). The registration parameters are obtained by a rectangular cuboid, which can be used to reconstruct three local point clouds. Thereafter, the distribution of the point cloud projection in different directions is used to locate the measuring positions, which then contribute to the precise measurement of several key parameters, such as body length, body height, body width and abdominal girth. Moreover, the polar coordinate transform is developed to improve the measurement accuracy of the abdominal girth. The experiments performed on forty pigs have shown that our average relative errors in the body length, height, width and abdominal girth are 2.97%, 3.35%, 4.13% and 4.67%, respectively, which demonstrate the feasibility and accuracy of the proposed system.

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