Landmark Recognition: State-of-the-Art Methods in a Large-Scale Scenario

The recognition of landmarks in images can help to manage large image collections and thus is desirable for many image retrieval applications. A practical system has to be scalable with an increasing number of landmarks. For the domain of landmark recognition we investigate state-of-the-art CBIR methods on an image dataset of 900 landmarks. Our experiments show that the kNN classifier outperforms the SVM in a large-scale scenario. The examined visual phrase concept has shown not to be as effective as the classical Bag-of-Words approach although the most landmarks are objects with a relatively fixed composition of their (nearby) parts.