Posture standardization of pig point cloud based on skeleton extraction and transformation

Authors

  • Jimin Zhu 1. State Key Laboratory of Swine and Poultry Breeding Industry, Guangzhou, Guangdong 510640, China 2. College of Mathematics Informatics, South China Agricultural University, Guangzhou 510642, China
  • Zhaoda Chen 2. College of Mathematics Informatics, South China Agricultural University, Guangzhou 510642, China
  • Ling Yin 1. State Key Laboratory of Swine and Poultry Breeding Industry, Guangzhou, Guangdong 510640, China 2. College of Mathematics Informatics, South China Agricultural University, Guangzhou 510642, China 3. National Engineering Research Center for Swine Breeding Industry, Guangzhou 510642, China
  • Gengyuan Cai 1. State Key Laboratory of Swine and Poultry Breeding Industry, Guangzhou, Guangdong 510640, China 3. National Engineering Research Center for Swine Breeding Industry, Guangzhou 510642, China 5. School of Foreign Studies, South China Agricultural University, Guangzhou 510642, China
  • Xiaochen Yao 4. Guangdong Zhongxin Breeding Technology Co.,Ltd, Guangzhou 511458, China
  • Sumin Zhang 1. State Key Laboratory of Swine and Poultry Breeding Industry, Guangzhou, Guangdong 510640, China 2. College of Mathematics Informatics, South China Agricultural University, Guangzhou 510642, China 3. National Engineering Research Center for Swine Breeding Industry, Guangzhou 510642, China
  • Huan Zhang 5. School of Foreign Studies, South China Agricultural University, Guangzhou 510642, China

DOI:

https://doi.org/10.25165/ijabe.v18i2.8644

Keywords:

pig point cloud, body size measurement, posture transfer, skeleton extraction

Abstract

Pig body measurement is an important evaluation criterion for breeding and production management. Automatic measurement algorithms for pig body sizes exhibit sensitivity to the point cloud posture, but non-standard pig postures may result in inaccurate joint point localization in body measurement, further affecting measurement accuracy and the commercial application of these algorithms. To address this challenge, this paper proposed a pig point cloud posture transformation method based on pig’s skeleton model to adjust non-standard postures before conducting body size measurements. The method utilized an improved L1-median skeleton model to extract the three-dimensional skeleton of the pig point cloud, capturing the skeleton joint points on the target pig’s head, body, and limbs. By binding the skeleton joint points with the local point cloud and using rotation matrices, non-standard postures were adjusted to standard ones, enabling accurate body size measurements. The experimental results demonstrated that the average relative errors between the transferred posture and the original standard posture were reduced to 0.89% in body length, 0.76% in body width (front), 1% in body width (back), 0.89% in body height (front), 1.7% in body height (back), 2.03% in thoracic circumference, 3.37% in abdominal circumference, and 1.89% in rump circumference. To conclude, the posture standardization transfer method can significantly reduce errors in important body size parameters such as body length, body height, and body width. The method displays a greater stability and robustness compared to existing posture normalization and regression adjustment methods, providing both guidance and insight for future research in intelligent agriculture. Key words: pig point cloud; body size measurement; posture transfer; skeleton extraction DOI: 10.25165/j.ijabe.20251802.8644 Citation: Zhu J M, Chen Z D, Yin L, Cai G Y, Yao X C, Zhang S M, et al. Posture standardization of pig point cloud based on skeleton extraction and transformation. Int J Agric & Biol Eng, 2025; 18(2): 63–74.

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Published

2025-04-25

How to Cite

Zhu, J., Chen, Z., Yin, L., Cai, G., Yao, X., Zhang, S., & Zhang, H. (2025). Posture standardization of pig point cloud based on skeleton extraction and transformation. International Journal of Agricultural and Biological Engineering, 18(2), 63–74. https://doi.org/10.25165/ijabe.v18i2.8644

Issue

Vol. 18 No. 2 (2025): IJABE

Section

Animal, Plant and Facility Systems

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