Low-Rank Affinity Based Local-Driven Multilabel Propagation

Figure 1

An illustration of the proposed approach: local features are extracted from both the training and the testing images to construct a graph. The graph edges are computed according to the adopted low-rank affinity over local features. Labels for the training vertices are derived from the context of matching images with multilabels and are propagated to vertices in the test images via the graph.