Affiliations: [a]
College of Electronic Information Engineering, Inner Mongolia University, Hohhot, China
| [b]
State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, Inner Mongolia University, Hohhot, China
| [c]
College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot, China
Correspondence:
[*]
Corresponding author. Zhiqiang Zheng, zqzheng@imu.edu.cn and College of Mechanical and Electrical Engineering, Inner Mongolia Agricultural University, Hohhot 010018, China. E-mail: yongz@imau.edu.cn.
Abstract: As the basis of intelligent breeding management and animal husbandry insurance, the identification of individual cattle is important in animal husbandry management. Given the difficulty of data acquisition caused by the non-rigid and lacking cooperation of cattle, this study proposes a method for cattle face image acquisition and processing that can efficiently adapt to the harsh environment of cattle barns. When processing the non-rigid cow face, the method of approximating the cow face to a rigid body is used to establish the cow face image data set., and the cattle face image data set is established. The Three Dimensional(3D) reconstruction method of cattle face uses a 3D image reconstruction method based on multiple perspectives. First, the scale-invariant feature transform algorithm is used to extract the image feature points. The fast library for approximate nearest neighbors algorithm is used to match feature points. The matching results are selected via random sampling consensus. Second, the structure of the motion method is used for the sparse reconstruction of point clouds, and the dense point cloud is then generated using the three-dimensional multi-view stereo vision algorithm. Finally, the Poisson surface reconstruction method is used for surface reconstruction. The results indicate that this method can effectively realize the three-dimensional reconstruction of cattle faces; the reconstructed images have obvious color, clear texture, and complete shape features.
Keywords: 3D Reconstruction, approximate
rigidity, multi-perspective, surface reconstruction
