Automated method for measuring body size parameters of live pigs based on non-rigid registration of point clouds

被引:0
作者
Gao, Zicheng [1 ]
Lei, Jie [1 ]
Wu, Jianhuan [1 ]
Zhang, Jialong [2 ]
Ruchay, Alexey [3 ]
Pezzuolo, Andrea [4 ]
Guo, Hao [1 ]
机构
[1] China Agr Univ, Coll Land Sci & Technol, Beijing 100083, Peoples R China
[2] China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China
[3] Russian Acad Sci, Fed Res Ctr Biol Syst & Agrotechnol, 9 Yanvarya 29, Orenburg 460000, Russia
[4] Univ Padua, Dept Land Environm Agr & Forestry, Viale Univ 16, I-35020 Legnaro, PD, Italy
来源
PROCEEDINGS OF 2023 IEEE INTERNATIONAL WORKSHOP ON METROLOGY FOR AGRICULTURE AND FORESTRY, METROAGRIFOR | 2023年
基金
中国国家自然科学基金;
关键词
body size measurement; automated method; non-rigid registration; 3D point cloud; pig farming; VISUAL IMAGE-ANALYSIS; GROWTH; SYSTEM;
D O I
10.1109/MetroAgriFor58484.2023.10424170
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
With the increasing demand of human and the development of automation technology, there is an urgent need for automated livestock body measurement methods. An object of this paper is to investigate an automated method for measuring body size parameters of live pigs based on non-rigid registration of point clouds. We choose Xtion pro camera as point cloud acquisition equipment to obtain RGB-D data from the upper left and upper right. Pig body point clouds are extracted from the acquired data after preprocessing. We perform coarse registration to the measured point clouds and the template point cloud so that the two point clouds are aligned. Moreover, non-rigid registration methods are used in order to make the shape of the measured data fit with the template data. Finally, the different body size parameters are estimated according to the landmarks that marked on the template point cloud in advance. The results have shown that this method is reliable for measuring pig body size parameters compared to manually measured values, especially in measuring the hip height, shoulder width, and hip width, in which the average relative errors are 2.92%, 5.78%, and 4.83%.
引用
收藏
页码:472 / 477
页数:6
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