FEMOT: Multi-Object Tracking using Frame and Event Cameras

1. 1Build a dataset combining frame and event camera data
2. 2Run experiments to evaluate the performance of FEMOT under various scenarios
3. 3Configure the FEMOT model to optimize its parameters for improved tracking accuracy
4. 4Test the FEMOT model on a variety of real-world challenges, such as motion blur and low illumination
5. 5Apply the FEMOT approach to applications like autonomous vehicles or surveillance systems

Computer vision engineers and researchers can benefit from this approach to enhance their object tracking systems, especially in applications where conventional RGB cameras fall short

💡 Combining frame and event cameras can provide complementary cues to improve multi-object tracking under extreme scenarios

🚀 Improve multi-object tracking with FEMOT, combining frame and event cameras for better performance in challenging scenarios!