Communication Dans Un Congrès Année : 2024

Simulating Aerial Event-based Environment: Application to Car Detection

Résumé

With the primary goal of enhancing the efficiency of drones for research and rescue missions through the exploitation of neuromorphic sensors and event-based vision, our focus in this work lies in setting up a simulated environment that can be used for synthetic data generation. In particular, we employ Unreal Engine to generate scenes suitable for the case of vehicle perception, followed by a dynamic event-based simulation environment in conjunction with AirSim and v2e tools. The synthetic event data acquired in this simulated environment serves as a crucial resource for training Artificial Intelligence (AI) systems, with a specific focus on car detection using YOLOv7.
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Dates et versions

hal-04497648 , version 1 (10-03-2024)
hal-04497648 , version 2 (08-01-2025)

Identifiants

Citer

Ismail Amessegher, Hajer Fradi, Clémence Liard, Jean-Philippe Diguet, Panagiotis Papadakis, et al.. Simulating Aerial Event-based Environment: Application to Car Detection. European Robotics Forum, Mar 2024, Rimini, Italy. ⟨10.1007/978-3-031-76424-0_26⟩. ⟨hal-04497648v2⟩
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