D'Angelo Giulia, Janotte Ella, Schoepe Thorben, O'Keeffe James, Milde Moritz B, Chicca Elisabetta, Bartolozzi Chiara
Event Driven Perception for Robotics, Italian Institute of Technology, iCub Facility, Genoa, Italy.
Faculty of Technology and Center of Cognitive Interaction Technology (CITEC), Bielefeld University, Bielefeld, Germany.
Front Neurosci. 2020 May 8;14:451. doi: 10.3389/fnins.2020.00451. eCollection 2020.
Attentional selectivity tends to follow events considered as interesting stimuli. Indeed, the motion of visual stimuli present in the environment attract our attention and allow us to react and interact with our surroundings. Extracting relevant motion information from the environment presents a challenge with regards to the high information content of the visual input. In this work we propose a novel integration between an eccentric down-sampling of the visual field, taking inspiration from the varying size of receptive fields (RFs) in the mammalian retina, and the Spiking Elementary Motion Detector (sEMD) model. We characterize the system functionality with simulated data and real world data collected with bio-inspired event driven cameras, successfully implementing motion detection along the four cardinal directions and diagonally.
注意力选择性往往会追随被视为有趣刺激的事件。的确,环境中视觉刺激的运动吸引我们的注意力,并使我们能够与周围环境做出反应和互动。鉴于视觉输入的高信息含量,从环境中提取相关运动信息是一项挑战。在这项工作中,我们从哺乳动物视网膜中感受野(RF)大小的变化中汲取灵感,提出了一种视野偏心下采样与脉冲基本运动检测器(sEMD)模型之间的新型集成方法。我们用模拟数据和通过受生物启发的事件驱动相机收集的真实世界数据来表征系统功能,成功实现了沿四个基本方向和对角线的运动检测。