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Project # 66
Tracking Unmanned Aerial Vehicles using Event Cameras
| Team Lead: | Nick Truong |
| Other Team Members: | |
| Faculty Advisor(s): | William Beksi |
| Department: | CSE |
| Project Type: | REU |
| Title: | Tracking Unmanned Aerial Vehicles using Event Cameras |
| Abstract: | Real-time visual tracking and 3D localization of high-speed targets such as unmanned aerial vehicles (UAVs) remains a significant challenge for a traditional frame-based camera due to motion blur and limited dynamic range. This project utilizes a bio-inspired event camera to overcome these limitations. An event camera offers high temporal resolution and low latency via asynchronous pixel-level brightness sensing. Despite these advantages, progress on this problem is currently hindered by a lack of specialized datasets that support 3D ground-truth localization. We address this gap by constructing a custom ground station featuring a synchronized dual stereo camera rig. This platform integrates stereo event and RGB cameras to record a multimodal dataset of UAVs in diverse outdoor environments. The project introduces the first dual stereo event and RGB UAV dataset to incorporate precise post-processing kinematic and real-time kinematic GPS for centimeter-level 3D localization. Our primary contributions include a hardware architecture for multimodal data collection and the creation of an open-source dataset to facilitate further research on high-speed object tracking and 3D localization. This work supports the development of future passive early warning systems for national security. |
| Poster: | View Poster #66 (PDF) |
| Judges Scoring: | Submit Evaluation (judges only) |