Research and Preliminary Evaluation of Key Technologies for 3D Reconstruction of Pig Bodies Based on 3D Point Clouds
文献类型: 外文期刊
第一作者: Lei, Kaidong
作者: Lei, Kaidong;Tang, Xiangfang;Li, Xiaoli;Lu, Qinggen;Long, Teng;Zhang, Xinghang;Xiong, Benhai
作者机构:
关键词: 3D point clouds; data processing; 3D reconstruction of pig bodies; body automated monitoring; precision livestock farming
期刊名称:AGRICULTURE-BASEL ( 影响因子:3.3; 五年影响因子:3.5 )
ISSN:
年卷期: 2024 年 14 卷 6 期
页码:
收录情况: SCI
摘要: In precision livestock farming, the non-contact perception of live pig body measurement data is a critical technological branch that can significantly enhance breeding efficiency, improve animal welfare, and effectively prevent and control diseases. Monitoring pig body measurements allows for accurate assessment of their growth and production performance. Currently, traditional sensing methods rely heavily on manual measurements, which not only have large errors and high workloads but also may cause stress responses in pigs, increasing the risk of African swine fever, and its costs of prevention and control. Therefore, we integrated and developed a system based on a 3D reconstruction model that includes the following contributions: 1. We developed a non-contact system for perceiving pig body measurements using a depth camera. This system, tailored to the specific needs of laboratory and on-site pig farming processes, can accurately acquire pig body data while avoiding stress and considering animal welfare. 2. Data preprocessing was performed using Gaussian filtering, mean filtering, and median filtering, followed by effective estimation of normals using methods such as least squares, principal component analysis (PCA), and random sample consensus (RANSAC). These steps enhance the quality and efficiency of point cloud processing, ensuring the reliability of 3D reconstruction tasks. 3. Experimental evidence showed that the use of the RANSAC method can significantly speed up 3D reconstruction, effectively reconstructing smooth surfaces of pigs. 4. For the acquisition of smooth surfaces in 3D reconstruction, experimental evidence demonstrated that the RANSAC method significantly improves the speed of reconstruction. 5. Experimental results indicated that the relative errors for chest girth and hip width were 3.55% and 2.83%, respectively. Faced with complex pigsty application scenarios, the technology we provided can effectively perceive pig body measurement data, meeting the needs of modern production.
分类号:
- 相关文献
作者其他论文 更多>>
-
Controllable self-cleaning FET self-assembled RNA-cleaving DNAzyme based DNA nanotree for culture-free Staphylococcus aureus detection
作者:Wang, Hui;Chen, Ruipeng;He, Yue;Zhu, Xiaoyan;Yu, Zhixue;Pan, Dongxia;Yang, Liang;Tang, Xiangfang;Xiong, Benhai;Feng, Zemeng;He, Yue
关键词:Self-cleaning field effect transistor; DNA origami; Electrochemical biosensor; Carbon nanotube; Superhydrophobic-oleophobic coating
-
First Report of Diaporthe eres Causing Leaf Spot on Rhododendron latoucheae in China
作者:Wu, Xueping;Li, Zhu;Wu, Xueping;Shi, Suhuan;Tang, Xianying;Li, Xiaoli;Ding, Haixia;Li, Huie;Liu, Lingling
关键词:Diaporthe eres; leaf spot; Rhododendron latoucheae Franch
-
A disposable immunosensor array using cellulose paper assembled chemiresistive biosensor for simultaneous monitoring of mycotoxins AFB1 and FB1
作者:He, Yue;Wang, Hui;Yu, Zhixue;Tang, Xiangfang;Zhou, Mengting;Xiong, Benhai;He, Yue;Guo, Yuming
关键词:Immunosensor; Mycotoxins; Paper-based biosensor; s-SWCNTs; Chemiresistive
-
Pestalotiopsis kenyana causes leaf spot disease on Rhododendron agastum in China
作者:Li, Xiaoli;Lin, Jianjun;Ding, Haixia;Liu, Lingling;Li, Huie;Lin, Jianjun;Zuo, Yingping;Peng, Lijuan
关键词:Rhododendron agastum; Pestalotiopsis kenyana; Pathogenicity; Leaf spot
-
Data-driven optimization of nitrogen fertilization and quality sensing across tea bud varieties using near-infrared spectroscopy and deep learning
作者:Zhang, Wenkai;Ji, Xusheng;Luo, Xuelun;He, Qinghai;Li, Xiaoli;He, Yong;Luo, Ying;Huang, Fuyin;Yan, Peng;Sanaeifar, Alireza;Guo, Hongen;He, Qinghai
关键词:Tea bud quality; Nitrogen status diagnosis; Near-infrared spectroscopy; Deep learning; Leaf color variants; Quality components
-
Advanced deep learning algorithm for instant discriminating of tea leave stress symptoms by smartphone-based detection
作者:Huang, Zhenxiong;Gouda, Mostafa;Ye, Sitan;Wang, Tiancheng;Song, Xinbei;Li, Xiaoli;He, Yong;Li, Siyi;Gouda, Mostafa;Zhang, Xuechen;Zhang, Jin
关键词:Tea leaves; Infield stress detection; Canopy image; Deep learning models; YOLOv8m algorithm; Natural scenes
-
Peptide aptamer-based colorimetric sensor for the detection of L-tryptophan in porcine serum
作者:Wang, Wenjing;He, Yumin;He, Suxiang;Feng, Zemeng;Yin, Yulong;He, Yumin;He, Suxiang;Liu, Xiaoying;Gui, Qing-wen;Deng, Lei;Cao, Zhong;Cao, Zhong;Xiong, Benhai
关键词:Peptide aptamer; Gold nanoparticle; L-tryptophan; Colorimetric sensor