Fast Tracking using Event-based Vision Sensors and Binary Frames
Abstract:
A novel tracking algorithm for high-speed object tracking using event-based Vision (EBV) sensors and binary frame representation is presented. The method transforms sparse event data into binary frames, enabling precise and robust particle tracking at 2 kHz frequency by combining correlation-based matching and center of gravity alignment.
| Zugehörige Institution(en) am KIT | Institut für Industrielle Informationstechnik (IIIT) |
| Publikationstyp | Proceedingsbeitrag |
| Publikationsdatum | 01.06.2025 |
| Sprache | Englisch |
| Identifikator | ISBN: 978-3-910600-06-5 KITopen-ID: 1000189224 |
| Erschienen in | SMSI 2025 Conference - Sensor and Measurement Science International |
| Veranstaltung | Sensor and measurement Science international (SMSI 2025), Nürnberg, Deutschland, 06.05.2025 – 08.05.2025 |
| Verlag | AMA Service GmbH, Von-Münchhausen-Str. 49, 31515 Wunstorf, Germany |
| Seiten | 111–112 |
| Serie | Lectures |
| Schlagwörter | Event Based Vision |
| Nachgewiesen in | Dimensions OpenAlex |