Abstract
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.
| Original language | English |
|---|---|
| Article number | 451 |
| Number of pages | 14 |
| Journal | Frontiers in Neuroscience |
| Volume | 14 |
| DOIs | |
| Publication status | Published - 2020 |
Open Access - Access Right Statement
© 2020 D’Angelo, Janotte, Schoepe, O’Keeffe, Milde, Chicca and Bartolozzi. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.Keywords
- motion detectors
- optical data processing
- robotics