Learning Local-Global Multi-Graph Descriptors for RGB-T Object Tracking
Learning Local-Global Multi-Graph Descriptors for RGB-T Object Tracking is a scholarly work, published in 2019 in ''IEEE Transactions on Circuits and Systems for Video Technology''. The main subjects of the publication include RGB color model, graph, nightlight, artificial intelligence, computer vision, biological robustness, minimum bounding box, Multiple object tracking, video tracking, pattern recognition, and computer science. To handle this problem, authors propose a novel and general approach to learn a local-global multi-graph descriptor to suppress background effects for RGB-T tracking.