Embodied Neuromorphic Synergy for Lighting-robust Machine Vision [data]

<p dir="ltr">In this research, inspired by the bio-principles governing the human pupillary control pathway, we devise and implement a novel neuromorphic exposure control (NEC) system. This innovation effectively alleviates the longstanding saturation problem that has plagued real-world intelligent machine vision systems operating under highly dynamic lighting conditions.</p><p dir="ltr">The NEC resolves this challenge at its core by exploiting bio-principles found in peripheral vision to the computation of a novel trilinear event double integral (TEDI). This approach enables accurate connections between events and frames in the physics space for swift irradiance prediction, ultimately facilitating rapid control parameter updates.</p><p dir="ltr">Our experimental results demonstrate the remarkable efficiency, low latency, superior generalization capability, and bio-inspired nature of the NEC in delivering timely and robust neuromorphic synergy for lighting-robust machine vision across a wide range of real-world applications. These applications encompass autonomous driving, mixed-reality, and three-dimensional reconstruction.</p>