Improving tag matrix completion for image annotation and retrieval

Image annotation is a fundamental and challenging task in the field of semantic image retrieval. In this paper, we deal with image annotation via matrix completion. Concretely, we formulate the problem of annotating the tags of an image into a constrained optimization problem, in which the constraint is to keep the consistency with the given initial labels and the objective is to minimize the discrepancy between the correlation in visual content and the correlation in semantic tags. We solve the optimization problem with the linearized alternating direction method. Experimental results on benchmark data demonstrate the effectiveness of our proposals.