Feeding behavior recognition for group-housed pigs with the Faster R-CNN

The feeding behavior of each individual pig is an important indicator to determine whether it is healthy or not. Therefore, automatic behavior recognition for individual pig is one of the core problem in precision pig farming. Video surveillance is a common tool for monitoring animal behaviors. To accurately identify each pig from the video sequences is a prerequisite for individual pig behavior recognition. This paper proposed to use Faster R-CNN to locate and identify individual pigs from a group-housed pen. The head of each pig was also located. An algorithm for associating the head of each pig with its body was designed. On this basis, a behavior recognition algorithm based on feeding area occupation rate was implemented to measure the feeding behavior of pigs. Experiment showed that our algorithm can recognize the feeding behavior of pigs with a precision rate of 99.6% and recall rate of 86.93%.