Occlusion-resistant locomotion analysis of piglets using amodal instance segmentation

摘要: Locomotion of piglets is a critical indicator of their growth, health, and welfare status; thus it is of utmost importance to automate the analysis of piglet locomotion, particularly during the early lactation periods. An intersection over unit-(IOU-) and contour-based tracking method is proposed to automate the locomotion analysis for piglets in farrowing pens. In the first step, an anchor-free deep learning network is employed in amodal instance segmentation of individual piglets. Then a novel attention graph convolution-based structure is used to distil element-wise features within the detected piglets. The distilled features are further encoded by a graph convolutional network. In the output features, pixels selected by a selection strategy derive features for a real-value pixel using 4-point nearest neighbor bilinear interpolation. Thus, a higherresolution segmentation is predicted in a coarse-to-fine fashion. In the second step …