pyDVS: an extensible, real-time Dynamic Vision Sensor emulator using off-the-shelf hardware

Pineda García, Garibaldi, Camilleri, Patrick, Liu, Qian and Furber, Steve (2016) pyDVS: an extensible, real-time Dynamic Vision Sensor emulator using off-the-shelf hardware. 2016 IEEE Symposium Series on Computational Intelligence (SSCI), Athens, Greece, 6-9 December 2016. Published in: 2016 IEEE Symposium Series on Computational Intelligence (SSCI). 1-7. IEEE, Athens, Greece. ISBN 9781509042401

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Abstract

Vision is one of our most important senses, a vast amount of information is perceived through our eyes. Neuroscientists have performed many studies using vision as input to their experiments. Computational neuroscientists have typically used a brightness-to-rate encoding to use images as spike-based visual sources for its natural mapping. Recently, neuromorphic Dynamic Vision Sensors (DVSs) were developed and, while they have excellent capabilities, they remain scarce and relatively expensive. We propose a visual input system inspired by the behaviour of a DVS but using a conventional digital camera as a sensor and a PC to encode the images. By using readily-available components, we believe most scientists would have access to a realistic spiking visual input source. While our primary goal is to provide systems with a live real-time input, we have also been successful in transcoding well established image and video databases into spike train representations. Our main contribution is a DVS emulator framework which can be extended, as we demonstrate by adding local inhibitory behaviour, adaptive thresholds and spike-timing encoding.

Item Type: Conference Proceedings
Additional Information: contact: g.pineda-garcia at sussex.ac.uk
Keywords: cameras;computer vision;image representation;image sensors;video databases;pyDVS;dynamic vision sensor emulator;off-the-shelf hardware;digital camera;image encoding;image database;video database;spike train representation;Niobium;Voltage control;Brightness;Encoding;Receivers;Visualization;Cameras
Schools and Departments: School of Engineering and Informatics > Informatics
Research Centres and Groups: Centre for Computational Neuroscience and Robotics
Subjects: Q Science > QA Mathematics > QA0075 Electronic computers. Computer science
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK6680.5 Digital video. General works
T Technology > TR Photography > TR0250 Cameras
T Technology > TR Photography > TR0624 Applied photography Including artistic, commercial, medical photography, photocopying processes
Depositing User: Garibaldi Pineda Garcia
Date Deposited: 21 Dec 2018 12:31
Last Modified: 21 Dec 2018 14:46
URI: http://sro.sussex.ac.uk/id/eprint/80941

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