UAIC participation at Robot Vision @ 2012 An updated vision

Abstract

In this paper we describe a system that participated in the fourth benchmarking activity ImageCLEF, in the Robot Vision task, for which we approach the task of topological localization without using a temporal continuity of the sequences of images. We provide details for the state-of-the-art methods that were selected: Color Histograms, SIFT (Scale Invariant Feature Transform), ASIFT (Ane SIFT) and RGB- SIFT, Bag-of-Visual-Words strategy inspired from the text retrieval com- munity. We focused on nding the optimal set of features and a deepened analysis was carried out. We oer an analysis of the dierent features, similarity measures and a performance evaluation of combinations of the proposed methods for topological localization. Also, we detail a genetic algorithm that was used for eliminating the false positives results. In the end, we draw several conclusions targeting the advantages of using proper congurations of visual-based appearance descriptors, similarity measures and classiers.