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

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.