Fast reciprocal nearest neighbors clustering

Authors:
Roberto J. López-Sastre;Daniel Oñoro-Rubio;Pedro Gil-Jiménez;Saturnino Maldonado-Bascón
Affiliations:
University of Alcalá, Department of Signal Theory and Communications, GRAM, 28805 Alcalá de Henares, Spain;University of Alcalá, Department of Signal Theory and Communications, GRAM, 28805 Alcalá de Henares, Spain;University of Alcalá, Department of Signal Theory and Communications, GRAM, 28805 Alcalá de Henares, Spain;University of Alcalá, Department of Signal Theory and Communications, GRAM, 28805 Alcalá de Henares, Spain
Venue:
Signal Processing
Year:
2012

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Abstract

This paper presents a novel approach for accelerating the popular reciprocal nearest neighbors (RNN) clustering algorithm, i.e. the fast-RNN. We speed up the nearest neighbor chains construction via a novel dynamic slicing strategy for the projection search paradigm. We detail an efficient implementation of the clustering algorithm along with a novel data structure, and present extensive experimental results that illustrate the excellent performance of fast-RNN in low- and high-dimensional spaces. A C++ implementation has been made publicly available.