@misc{, author = {von Arnim, Axel and Lecomte, Jules and Wozniak, Stanislaw and Elosegui, Naima and Pantazi, Angeliki}, title = {Dynamic Event-based Optical Identification and Communication}, booktitle = {in 2023 IEEE International Conference on Image Processing}, publisher = {IEEE}, journal = {Frontiers in Neurorobotics}, volume = {18}, year = {2024}, month = feb, timestamp = 2024.02.12, organization = {fortiss}, abstract = {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. In an asset monitoring use case, we demonstrate that the system, embedded in a simulated drone, is robust to relative movements and enables simultaneous communication with, and tracking of, multiple moving beacons. Finally, in a hardware lab prototype, we achieve state-of-the-art optical camera communication frequencies in the kHz magnitude.}, issn = {1662-5218}, doi = {10.3389/fnbot.2024.1290965}, keywords = {Neuromorphic Computing, Event-Based Sensing, Optical Camera Communication, Optical Flow}, url = {https://www.frontiersin.org/articles/10.3389/fnbot.2024.1290965}, }