Asynchronous event-based corner detection and matching
This paper introduces an event-based luminance-free method to detect and match corner events from the output of asynchronous event-based neuromorphic retinas. The method relies on the use of spacetime properties of moving edges. Asynchronous event-based neuromorphic retinas are composed of autonomous pixels, each of them asynchronously generating spiking events that encode relative changes in pixels illumination at high temporal resolutions. Corner events are defined as the spatiotemporal locations where the aperture problem can be solved using the intersection of several geometric constraints in events spatiotemporal spaces. A regularization process provides the required constraints, i.e. the motion attributes of the edges with respect to their spatiotemporal locations using local geometric properties of visual events. Experimental results are presented on several real scenes showing the stability and robustness of the detection and matching.
corner detection and matching neuromorphic sensor event-based vision intersection of constraints