{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T18:38:55Z","timestamp":1771958335842,"version":"3.50.1"},"reference-count":21,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T00:00:00Z","timestamp":1707696000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Neurorobot."],"abstract":"<jats:p>Optical identification is often done with spatial or temporal visual pattern recognition and localization. Temporal pattern recognition, depending on the technology, involves a trade-off between communication frequency, range, and accurate tracking. We propose a solution with light-emitting beacons that improves this trade-off by exploiting fast event-based cameras and, for tracking, sparse neuromorphic optical flow computed with spiking neurons. The system is embedded in a simulated drone and evaluated in an asset monitoring use case. It is robust to relative movements and enables simultaneous communication with, and tracking of, multiple moving beacons. Finally, in a hardware lab prototype, we demonstrate for the first time beacon tracking performed simultaneously with state-of-the-art frequency communication in the kHz range.<\/jats:p>","DOI":"10.3389\/fnbot.2024.1290965","type":"journal-article","created":{"date-parts":[[2024,2,12]],"date-time":"2024-02-12T04:30:17Z","timestamp":1707712217000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Dynamic event-based optical identification and communication"],"prefix":"10.3389","volume":"18","author":[{"given":"Axel","family":"von Arnim","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jules","family":"Lecomte","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Naima Elosegui","family":"Borras","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stanis\u0142aw","family":"Wo\u017aniak","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Angeliki","family":"Pantazi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2024,2,12]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2018.8593380","article-title":"\u201cReal-time clustering and multi-target tracking using event-based sensors,\u201d","author":"Barranco","year":"2018","journal-title":"2018 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS)"},{"key":"B2","doi-asserted-by":"publisher","first-page":"1339","DOI":"10.3390\/electronics9091339","article-title":"Optical camera communications: Principles, modulations, potential and challenges","volume":"9","author":"Cahyadi","year":"2020","journal-title":"Electronics"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.1109\/IROS.2013.6696456","article-title":"\u201cLow-latency localization by active led markers tracking using a dynamic vision sensor,\u201d","author":"Censi","year":"2013","journal-title":"2013 IEEE\/RSJ International Conference on Intelligent Robots and Systems, pages"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1109\/SMC.2019.8914078","article-title":"\u201cDeep kalman filter with optical flow for multiple object tracking,\u201d","author":"Chen","year":"2019","journal-title":"2019 IEEE International Conference on Systems, Man and Cybernetics (SMC)"},{"key":"B5","doi-asserted-by":"publisher","first-page":"311","DOI":"10.1109\/TCSVT.2012.2203741","article-title":"Automatic license plate recognition (alpr): a state-of-the-art review","volume":"23","author":"Du","year":"2013","journal-title":"IEEE Trans. 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