Fast geometric consistency test for real time logo detection

Abstract

In this paper we present a method for logo detection in image collections and streams. The proposed method is based on features, extracted from reference logo images and test images. Extracted features are combined with respect to their similarity in their descriptors' space and afterwards with respect to their geometric consistency on the image plane. The contribution of this paper is a novel method for fast geometric consistency test. Using state of the art fast matching methods, it produces pairs of similar features between the test image and the reference logo image and then examines which pairs are forming a consistent geometry on both the test and the reference logo image. It is noteworthy that the proposed method is scale, rotation and translation invariant. The key advantage of the proposed method is that it exhibits a much lower computational complexity and better performance than the state of the art methods. Experimental results on large scale datasets are presented to support these statements.