In this paper we formulate image retrieval by text query as a vector space classification problem. This is achieved by creating a high-dimensional visual vocabulary that represents the image documents in great detail. We show how the representation of these image documents enables the application of well known text retrieval techniques such as Rocchio tf-idf and naíve Bayes to the semantic image retrieval problem. We tested these methods on a Corel images subset and achieve state-of-the-art retrieval performance using the proposed methods.
Magalhaes, Joao and Rüger, Stefan (2007). High-dimensional visual vocabularies for image retrieval. In: Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR 07 SIGIR 07, p. 815.