@inproceedings{ef117fdde43644f7a24679e82517f322,
title = "Efficient, event-driven feature extraction and unsupervised object tracking for embedded applications",
abstract = "Neuromorphic vision sensors offer a low-power, bandwidth efficient way to extract salient visual information from the scene and are a candidate for energy-efficient embedded systems. An algorithm for embedded, event-driven feature extraction and object tracking to leverage such sensors is outlined and demonstrated. Near sensor data sparsification and information extraction is conducted in three distinct steps: memory efficient noise filtering, fast scalable identification of keypoints, and subsequent clustering to identify objects in the scene. The processing flow has demonstrated rates of near 100 fold data reduction, 5 fold improvement of feature extraction throughput, and sustenance of an event processing rate of 212kAEps.",
keywords = "Filtering, Clustering algorithms, Feature extraction, Throughput, Object recognition, Data mining, Object tracking, Event-based vision processing, Unsupervised learning",
author = "Sengupta, {Jonah P.} and Martin Villemur and Andreou, {Andreas G.}",
note = "DBLP License: DBLP's bibliographic metadata records provided through http://dblp.org/ are distributed under a Creative Commons CC0 1.0 Universal Public Domain Dedication. Although the bibliographic metadata records are provided consistent with CC0 1.0 Dedication, the content described by the metadata records is not. Content may be subject to copyright, rights of privacy, rights of publicity and other restrictions.; 2021 55th Annual Conference on Information Sciences and Systems (CISS) ; Conference date: 24-03-2021 Through 26-03-2021",
year = "2021",
month = mar,
day = "26",
doi = "10.1109/CISS50987.2021.9400234",
language = "English",
isbn = "9781665412681",
series = "2021 55th Annual Conference on Information Sciences and Systems (CISS)",
publisher = "IEEE Computer Society",
pages = "1--6",
booktitle = "2021 55th Annual Conference on Information Sciences and Systems, CISS 2021",
address = "United States",
}