Volume XLII-2/W7
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 211-217, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-211-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W7, 211-217, 2017
https://doi.org/10.5194/isprs-archives-XLII-2-W7-211-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

  12 Sep 2017

12 Sep 2017

3D SCANNING OF LIVE PIGS SYSTEM AND ITS APPLICATION IN BODY MEASUREMENTS

H. Guo1,2, K. Wang1,2, W. Su1,2, D. H. Zhu1,2, W. L. Liu1, Ch. Xing1, and Z. R. Chen1 H. Guo et al.
  • 1College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China
  • 2Ministry of Agriculture Key Laboratory of Agricultural Information Acquisition Technology, Beijing 100083, China

Keywords: Point clouds, Depth camera, Body measurement, Pigs, 3D Scanning

Abstract. The shape of a live pig is an important indicator of its health and value, whether for breeding or for carcass quality. This paper implements a prototype system for live single pig body surface 3d scanning based on two consumer depth cameras, utilizing the 3d point clouds data. These cameras are calibrated in advance to have a common coordinate system. The live 3D point clouds stream of moving single pig is obtained by two Xtion Pro Live sensors from different viewpoints simultaneously. A novel detection method is proposed and applied to automatically detect the frames containing pigs with the correct posture from the point clouds stream, according to the geometric characteristics of pig’s shape. The proposed method is incorporated in a hybrid scheme, that serves as the preprocessing step in a body measurements framework for pigs. Experimental results show the portability of our scanning system and effectiveness of our detection method. Furthermore, an updated this point cloud preprocessing software for livestock body measurements can be downloaded freely from https://github.com/LiveStockShapeAnalysis to livestock industry, research community and can be used for monitoring livestock growth status.