Reconstruction and Body Size Detection of 3D Sheep Body Model Based on Point Cloud Data

  • Yanqing Zhou
  • Heru XueEmail author
  • Chunlan Wang
  • Xinhua Jiang
  • Xiaojing Gao
  • Jie Bai
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 546)


Aiming at the high workload, low precision, strong stress of the traditional manual measurement to obtain the sheep growth parameters, a novel measurement technology was proposed. The specimen of the Sunite sheep about 2–3 years old were chosen for study. By reverse engineering technology, point cloud data of sheep was captured by the 3D laser scanner. Because of noise point cloud data, the improved algorithm of k-nearest neighbor was used to process the data. To improve the subsequent processing time and efficiency, octree coding was employed to reduce data, which can get evenly distribution of point cloud data and retain sheep features. Then, 3D surface model of sheep body was reconstructed using Delaunay triangulation. Some parameters were extracted, including sheep body length, body height, hip height, hip width and chest width. Compared actual parameters values with computing values of two ways, by Geomagic platform and the proposed algorithms on the Matlab, average relative errors of two ways were 1.23% and 1.01%, respectively. So results of the proposed algorithm were with small error range. Using the point clouds can reconstruct sheep surface for computing body size without stress.


Sheep body parameters Point clouds Octree coding Three-dimensional reconstruction Data pretreatment 



This work was supported by national and international scientific and technological cooperation special projects (No. 2015DFA00530), supported by national natural science foundation of China (No. 61461041).


  1. 1.
    Zhang, L., et al.: Advances in body size measurement and conformation appraisal for sheep. Trans. Chin. Soc. Agric. Eng. 32, 190–197 (2016)Google Scholar
  2. 2.
    Zhen, Y., et al.: 3D synchronization imaging system for linear appraisal of dairy cow conformation. Trans. Chin. Soc. Agric. Mach. 40(2), 175–179 (2009)Google Scholar
  3. 3.
    Wu, J.H., et al.: Extracting the three-dimensional shape of live pigs using stereo photogrammetry. Comput. Electron. Agric. 44(3), 203–222 (2004)MathSciNetCrossRefGoogle Scholar
  4. 4.
    Vieira, A., et al.: Development and validation of a visual body condition scoring system for dairy goats with picture-based training. J. Dairy Sci. 98(9), 6597–6608 (2015)CrossRefGoogle Scholar
  5. 5.
    Menesatti, P., et al.: A low-cost stereovision system to estimate size and weight of live sheep. Comput. Electron. Agric. 103(2), 33–38 (2014)CrossRefGoogle Scholar
  6. 6.
    Zhang, L., et al.: Design and experiment of non-stress measuring system for sheep’s conformation parameters. Trans. Chin. Soc. Agric. Mach. 47(11), 307–315 (2016)Google Scholar
  7. 7.
    Schofield, C.P., et al.: Monitoring pig growth using a prototype imaging system. J. Agric. Eng. Res. 72(3), 205–210 (1999)MathSciNetCrossRefGoogle Scholar
  8. 8.
    Bewley, J.M., et al.: Potential for estimation of body condition scores in dairy cattle from digital images. J. Dairy Sci. 91(9), 3439–3453 (2008)CrossRefGoogle Scholar
  9. 9.
    Yu, D.M., et al.: Application of reverse engineering technology in constructing prototype surface. Appl. Mech. Mater. 34, 1154–1158 (2010)CrossRefGoogle Scholar
  10. 10.
    Liu, T., et al.: Reconstruction and application of 3D pig body model based on point cloud data. Nongye Jixie Xuebao/Trans. Chin. Soc. Agric. Mach. 45(6), 291–295 (2014)Google Scholar
  11. 11.
    Li, S., et al.: Three-dimensional geometrical modeling of the exterior configuration of a cattle hoof by reverse engineering technology. Trans. Chin. Soc. Agric. Eng. 20(2), 156–160 (2004)MathSciNetGoogle Scholar
  12. 12.
    Zhang, B., et al.: Feature detection and three-dimensional reconstruction for papaya harvesting. J. Agric. Mech. Res. 12, 212–216 (2016)Google Scholar
  13. 13.
    Yu, D.M., et al.: Reconstructing of prototype surface with reverse engineering and data process technology. Key Eng. Mater. 458(458), 368–373 (2011)Google Scholar
  14. 14.
    Zhang, Q.F., Sun, X.S.: Measuring principle and developmental prospect of 3D laser scanner. Beijing Surv. Mapp. 1, 39–42 (2011)Google Scholar
  15. 15.
    Fang, F., Cheng, X.: A fast data reduction method for massive scattered point clouds based on slicing. Geomat. Inf. Sci. Wuhan Univ. 38(11), 1353–1357 (2013)Google Scholar
  16. 16.
    Wang Chunlan, X.H., Jiang, X., Zhou, Y.: The research of removing stray noise fast from point cloud data of three dimension. J. Inner Mongolia Agric. Univ. 38(1), 93–97 (2017)Google Scholar
  17. 17.
    Lee, K.H., Woo, H., Suk, T.: Point data reduction using 3D grids. Int. J. Adv. Manuf. Technol. 18(3), 201–210 (2001)CrossRefGoogle Scholar
  18. 18.
    Wang, Y., et al.: Research on 3D modeling method based on hybrid octree structure. Open Electr. Electron. Eng. J. 8(1), 323–329 (2014)CrossRefGoogle Scholar
  19. 19.
    Romanoni, A., et al.: Automatic 3D reconstruction of manifold meshes via delaunay triangulation and mesh sweeping, pp. 1–8 (2016)Google Scholar
  20. 20.
    Sowande, O.S., Sobola, O.S.: Body measurements of west African dwarf sheep as parameters for estimation of live weight. Trop. Anim. Health Prod. 40(6), 433–439 (2008)CrossRefGoogle Scholar
  21. 21.
    Mahmud, M.A., et al.: Live body weight estimation using cannon bone length and other body linear measurements in Nigerian breeds of sheep. J. Adv. Vet. Anim. Res. 1(4), 169–176 (2014)CrossRefGoogle Scholar

Copyright information

© IFIP International Federation for Information Processing 2019

Authors and Affiliations

  • Yanqing Zhou
    • 1
  • Heru Xue
    • 1
    Email author
  • Chunlan Wang
    • 1
  • Xinhua Jiang
    • 1
  • Xiaojing Gao
    • 1
  • Jie Bai
    • 1
  1. 1.College of Computer and Information EngineeringInner Mongolia Agricultural UniversityHohhotChina

Personalised recommendations