Calculating Volume of Pig Point Cloud Based on Improved Poisson Reconstruction

作者：Junyong Lin, Hongyu Chen, Runkang Wu, Xueyin Wang, Xinchang Liu, He Wang, Zhenfang Wu, Gengyuan Cai, Ling Yin, Runheng Lin, Huan Zhang, Sumin Zhang · 发表于：Animals · 年份：2024 · DOI：10.3390/ani14081210 · 被引用次数：10 · 研究领域：Animal Behavior and Welfare Studies、Industrial Vision Systems and Defect Detection、Effects of Environmental Stressors on Livestock

Pig point cloud data can be used to digitally reconstruct surface features, calculate pig body volume and estimate pig body weight. Volume, as a pig novel phenotype feature, has the following functions: (a) It can be used to estimate livestock weight based on its high correlation with body weight. (b) The volume proportion of various body parts (such as head, legs, etc.) can be obtained through point cloud segmentation, and the new phenotype information can be utilized for breeding pigs with smaller head volumes and stouter legs. However, as the pig point cloud has an irregular shape and may be partially missing, it is difficult to form a closed loop surface for volume calculation. Considering the better water tightness of Poisson reconstruction, this article adopts an improved Poisson reconstruction algorithm to reconstruct pig body point clouds, making the reconstruction results smoother, more continuous, and more complete. In the present study, standard shape point clouds, a known-volume Stanford rabbit standard model, a measured volume piglet model, and 479 sets of pig point cloud data with known body weight were adopted to confirm the accuracy and reliability of the improved Poisson reconstruction and volume calculation algorithm. Among them, the relative error was 4% in the piglet model volume result. The average absolute error was 2.664 kg in the weight estimation obtained from pig volume by collecting pig point clouds, and the average relative error was 2.478%. Concur...