Title: Bio-inspired visual attention process using spiking neural networks controlling a camera

Authors: André Cyr; Frédéric Thériault

Addresses: School of Psychology, University of Ottawa, 75 Laurier Ave E, Ottawa, ON K1N 6N5, Canada ' Department of Computer Science, Cégep du Vieux Montréal, 255 Ontario St E, Montreal, QC H2X 1X6, Canada

Abstract: This study introduces virtual and physical implementations of a bottom-up visual attention mechanism using a spiking neural network (SNN) controlling a camera. The SNN is able to focus simple stimuli of various lengths that appear randomly in the camera's view. This is accomplished with an overt process based on a competitive choice according to a stimulus quadrant location. After focusing a selected stimulus toward the centre of its view, the SNN scans it from one edge to the other. Since the spike train of dedicated neurons reflects the duration of each scan, it allows the extraction of the stimulus length. Upon the completion of a scan, the SNN has the ability to switch to another stimulus. This preliminary work on spatial visual attention intends to be a step toward the study of the concept size learning process in a robotic context.

Keywords: spiking neurons; robotics; overt process; visual attention.

DOI: 10.1504/IJCVR.2019.098006

International Journal of Computational Vision and Robotics, 2019 Vol.9 No.1, pp.39 - 55

Received: 12 Apr 2018
Accepted: 21 May 2018
Published online: 26 Feb 2019 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article