Research On Live Livestock Counting Based On Low-cost Camera

The number of live livestock in farms is an important reference index in daily management of livestock farms,financial audit of animal husbandry,asset evaluation in credit system,regulation and control of market by government and policy formulation.With the development of intelligent animal husbandry,counting live livestock based on computer vision technology has aroused extensive research interest in academic circles.Most of the existing solutions work well in specific experimental environments and configurations.However,at the present stage,some of the farms in China do not have the conditions to install special fixed equipment.Smart phones not only have a high popularity rate,but also can collect rich data,which brings new ideas to the exploration of designing a universal live livestock counting scheme.Therefore,in this context,this paper focuses on the problem of counting live livestock with low-cost cameras using mobile phones as an example.The research results of this paper include the following three aspects:1.We build a 10000 live pig instance segmentation dataset,improve the Mask RCNN network and train the instance segmentation algorithm model.We collect live pig breeding scene images of different breeds,different postures and different growth cycles in three pig farms in Xiangyang,Hubei Province,Zhangzhou,Fujian Province and Ji’an,Jiangxi Province.We performe artificial instance segmentation annotation and data enhancement.Finally,the OA accuracy of the example segmentation model reaches 92%.2.We propose a low-cost camera based live livestock counting process in complex environment.We designed the operation requirements of shooting counting video in the breeding farm environment,and construct the processing framework including instance segmentation,panorama mosaic and de-counting.Finally,the process realizes the live livestock counting in the typical farm environment,and the relative error is about 5%.3.We propose a panoramic mosaic and de-repeat counting method in complex environment of livestock house.For the software mode,we design a panoramic mosaic method of a single livestock house based on the deep learning network SuperGlue.For the hardware mode,we design a panoramic mosaic method of a single livestock house based on EXLAM 80X42 equipment.We verify the feasibility of the two panoramic splicing and deconduplication counting methods through experiments.Through a number of experiments and case studies in real farms of different scales and different breeding environments,the experimental results show that the process proposed in this paper can accurately calculate the number of live livestock,and it is universal.