English

Event Driven Clustering Algorithm

Computer Vision and Pattern Recognition 2026-02-03 v1 Machine Learning

Abstract

This paper introduces a novel asynchronous, event-driven algorithm for real-time detection of small event clusters in event camera data. Like other hierarchical agglomerative clustering algorithms, the algorithm detects the event clusters based on their tempo-spatial distance. However, the algorithm leverages the special asynchronous data structure of event camera, and by a sophisticated, efficient and simple decision-making, enjoys a linear complexity of O(n)O(n) where nn is the events amount. In addition, the run-time of the algorithm is independent with the dimensions of the pixels array.

Keywords

Cite

@article{arxiv.2602.00115,
  title  = {Event Driven Clustering Algorithm},
  author = {David El-Chai Ben-Ezra and Adar Tal and Daniel Brisk},
  journal= {arXiv preprint arXiv:2602.00115},
  year   = {2026}
}

Comments

~10 pages, 2 figures