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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算法的生物摩擦VLSI视觉传感器的多芯片实现

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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:在从恒星到灵长生的物种的视网膜中发现的生物运动传感器被调整为特定的时空频率,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,我们介绍了一种基于灵长类动物皮质细胞的Adelson-yergen时空能量模型的硅视网膜的新颖实现。通过采用多芯片策略,我们成功地实施了模型,而不会牺牲前端芯片中的光感受器的填充因子。另外,表征结果证明,该时空调谐硅视网膜可以检测正弦输入光栅的运动方向下降到10%对比度,并且在速度中超过大量幅度。该多芯片仿真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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