Occlusion-Resistant Instance Segmentation of Piglets in Farrowing Pens Using Center Clustering Network

no code implementations • 4 Jun 2022 • Endai Huang, Axiu Mao, Junhui Hou, Yongjian Wu, Weitao Xu, Maria Camila Ceballos, Thomas D. Parsons, Kai Liu

Specifically, CClusnet-Inseg uses each pixel to predict object centers and trace these centers to form masks based on clustering results, which consists of a network for segmentation and center offset vector map, Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm, Centers-to-Mask (C2M), and Remain-Centers-to-Mask (RC2M) algorithms.

Clustering Instance Segmentation +4