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Multi-chip Implementation of a Biomimetic VLSI Vision Sensor Based on the Adelson-Bergen Algorithm

机译:基于Adelson-Bergen算法的仿生VLSI视觉传感器的多芯片实现

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摘要

Biological motion sensors found in the retinas of species ranging from flies to primates are tuned to specific spatio-temporal frequencies to determine the local motion vectors in their visual field and perform complex motion computations. In this study, we present a novel implementation of a silicon retina based on the Adelson-Bergen spatio-temporal energy model of primate cortical cells. By employing a multi-chip strategy, we successfully implemented the model without much sacrifice of the fill factor of the photoreceptors in the front-end chip. In addition, the characterization results proved that this spatio-temporal frequency tuned silicon retina can detect the direction of motion of a sinusoidal input grating down to 10 percent contrast, and over more than a magnitude in velocity. This multi-chip biomimetic vision sensor will allow complex visual motion computations to be performed in real-time.
机译:将从蝇类到灵长类动物的物种视网膜中发现的生物运动传感器调整到特定的时空频率,以确定其视野中的局部运动矢量并执行复杂的运动计算。在这项研究中,我们提出了一种基于灵长类皮质细胞的Adelson-Bergen时空能量模型的硅视网膜的新型实现。通过采用多芯片策略,我们成功实现了该模型,而无需牺牲前端芯片中感光器的填充因子。此外,表征结果证明,这种时空频率调谐的硅视网膜可以检测到正弦输入光栅的运动方向,对比度低至10%,速度超过一个量级。这种多芯片仿生视觉传感器将允许实时执行复杂的视觉运动计算。

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