The paper presents a random graph based analysis approach for evaluating descriptors based on pairwise distance distributions on real data. Starting from the Erdos-Rényi model the paper presents results of investigating random geometric graph behaviour in relation with the appearance of the giant component as a basis for choosing descriptors based on their clustering properties. Experimental results prove the existence of the giant component in such graphs, and based on the evaluation of their behaviour the graphs, the corresponding descriptors are compared, and validated in proof-of-concept retrieval tests. © 2012 Springer-Verlag.
CITATION STYLE
Keszler, A., Kovács, L., & Szirányi, T. (2012). The appearance of the giant component in descriptor graphs and its application for descriptor selection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7488 LNCS, pp. 76–81). https://doi.org/10.1007/978-3-642-33247-0_9
Mendeley helps you to discover research relevant for your work.