Content-free image retrieval using bayesian product rule

Content-free image retrieval uses accumulated user feedback records to retrieve images without analyzing image pixels. We present a Bayesian-based algorithm to analyze user feedback and show that it outperforms a recent maximum entropy content-free algorithm, according to extensive experiments on trademark logo and 3D model datasets. The proposed algorithm also has the advantage of being applicable to both content-free and traditional content-based image retrieval, thus providing a common framework for these two paradigms.