Dense Pixel-level Beef Cattle Instance Segmentation Using a Fully Convolutional Network

Aram Ter-Sarkisov, Robert Ross, John Kelleher, Bernadette Earley, Michael Keane

Feb 12, 2018 (modified: Jun 04, 2018) ICLR 2018 Workshop Submission readers: everyone Show Bibtex
  • Abstract: We present an instance segmentation algorithm trained and applied to a video of a group of heifers recorded in a winter finishing feedlot. We transform a fully convolutional class segmentation network into an instance segmentation network that learns to label each instance of a heifer separately. We introduce two new modules that teach the network to output a single prediction for every animal. These results are an early contribution towards behaviour analysis in winter finishing beef cattle for early detection of welfare-related problems, namely lameness.
  • Keywords: deep learning, instance segmentation, precision farming, convolutional neural networks
  • TL;DR: Instance segmentation algorithm to identify beef cattle in a winter finishing feedlot facility