Cow body weight estimation based on 3D model volume
Aiming at the problems of low accuracy and automation of cow weight estimation,a method of using double view cow point cloud to build a three-dimensional model and predict the weight based on the model was proposed.Firstly,the Kinect camera was used to extract the point cloud of the cow in top and side view.Secondly,the point cloud of the head,neck and back ridge was calculated to fit the straight line angle and automatically filter out the standard posture point cloud suitable for 3D reconstruction.Thirdly,the missing areas were completed by using the adjacent point clouds of the missing point clouds,and then the alignment feature points were extracted and used for the alignment of the point clouds.Finally,the point cloud was mirrored by constructing a symmetrical surface based on the dorsal ridge line,completing the 3D reconstruction of the cow point cloud and finally predicting the cow's weight based on the 3D model volume.The results of the weight estimation experiments on 91 cows showed that the absolute error of weight estimation ranged from-19.23 to+20.04 kg and the relative error ranged from-2.96%to+2.90%.The method achieved a more accurate automatic estimation of cow weight and could provide technical support for accurate dairy farming.
NETL
NSTL
万方数据
