Multi-target pig tracking algorithm based on joint probability data association and particle filter

Longqing Sun, 1. College of Information and Electrical Engineering, China Agricultural University, Beijing 100083, China, Yiyang Li, 2. University Medical Center Groningen, University of Groningen, Groningen 9713 GZ, Netherlands
2021 International Journal of Agricultural and Biological Engineering  
In order to evaluate the health status of pigs in time, monitor accurately the disease dynamics of live pigs, and reduce the morbidity and mortality of pigs in the existing large-scale farming model, pig detection and tracking technology based on machine vision are used to monitor the behavior of pigs. However, it is challenging to efficiently detect and track pigs with noise caused by occlusion and interaction between targets. In view of the actual breeding conditions of pigs and the
more » ... s of existing behavior monitoring technology of an individual pig, this study proposed a method that used color feature, target centroid and the minimum circumscribed rectangle length-width ratio as the features to build a multi-target tracking algorithm, which based on joint probability data association and particle filter. Experimental results show the proposed algorithm can quickly and accurately track pigs in the video, and it is able to cope with partial occlusions and recover the tracks after temporary loss.
doi:10.25165/j.ijabe.20211404.6105 fatcat:7cvb6ymchrh6tc4oyqnjzo2xwq