Beef Cattle Instance Segmentation Using Fully Convolutional Neural Network
This work addresses animal welfare monitoring in beef cattle during winter finishing, but it is incremental as it applies an existing method to a new domain.
The researchers tackled the problem of segmenting individual beef cattle in CCTV footage by developing a fully convolutional neural network for instance segmentation, achieving separate labeling of each animal instance.
We present an instance segmentation algorithm trained and applied to a CCTV recording of beef cattle during a winter finishing period. A fully convolutional network was transformed into an instance segmentation network that learns to label each instance of an animal separately. We introduce a conceptually simple framework that the network uses to output a single prediction for every animal. These results are a contribution towards behaviour analysis in winter finishing beef cattle for early detection of animal welfare-related problems.