Adaptive Attention with a Neuromorphic Hybrid Frame and Event-based Camera

Neuromorphic (brain-inspired) cameras communicate transients in luminance as events, supporting high frame rate, fine temporal resolution, high dynamic range, no motion blur, high signal-to-noise ratio, and power-efficient vision systems. Here, we used a hybrid camera, neuromorphically enhancing frame-based vision with event-driven motion-sensitive adaptive attention. We used spatial-memory and event-driven salient maps to direct a frame camera toward attentive zones. We further implemented a dynamic tolerance mechanism with which attentional zones reallocate, supporting a multiple-object attentional load. Finally, we enhanced our hybrid imaging system using an automatic segmentation performed in fixed time intervals on event-based reconstructed frames, allowing efficient derivation of attentive areas. This hybrid approach demonstrates an efficient coverage of a large field of view.