Event driven cameras can be a powerful tool for low-latency estimation of the environment. We seek methods to perform computer vision operations in a low-latency, real-time fashion with events. Real-time cannot be intrinsically guaranteed, as the number of events changes with motion and clutter.
Decoupling the event-driven update of the data representation from the processing, we can achieve extremely high update rate and minimum dependency on the events rate. The most up to date work shows corner detection with few ms delay for high resolution hand-held cameras in cluttered scenarios. Checkout also past work on corner detection and on optical flow.
Threshold-ordinal surface, Harris corner detection.
Glover A., Dinale A., De Souza Rosa L., Bamford S., Bartolozzi C. luvHarris: A Practical Corner Detector for Event-cameras, IEEE Transactions on Pattern Analysis and Machine Intelligence
Mueggler E., Bartolozzi C., Scaramuzza D. Fast event-based corner detection, British Machine Vision Conference 2017 (BMVC 2017)
Vasco V., Glover A., Mueggler E., Scaramuzza D., Natale L., Bartolozzi C. Independent motion detection with event-driven cameras, 2017 18th International Conference on Advanced Robotics (ICAR 2017)
Vasco V., Glover A., Mueggler E., Scaramuzza D., Natale L., Bartolozzi C. Fast event-based Harris corner detection exploiting the advantages of event-driven cameras, IEEE International Conference on Intelligent Robots and Systems