%A Serrano-Gotarredona,Teresa %A Linares-Barranco,Bernabé %D 2015 %J Frontiers in Neuroscience %C %F %G English %K event-driven vision,Event-Driven Object Recognition,dynamic vision sensor (DVS),address event representation,high speed vision,Frame-free vision %Q %R 10.3389/fnins.2015.00481 %W %L %M %P %7 %8 2015-December-22 %9 Original Research %+ Dr Bernabé Linares-Barranco,Instituto de Microelectrónica de Sevilla (IMSE-CNM), CSIC and Universidad de Sevilla,Sevilla, Spain,bernabe@imse-cnm.csic.es %# %! Poker-DVS and MNIST-DVS %* %< %T Poker-DVS and MNIST-DVS. Their History, How They Were Made, and Other Details %U https://www.frontiersin.org/articles/10.3389/fnins.2015.00481 %V 9 %0 JOURNAL ARTICLE %@ 1662-453X %X This article reports on two databases for event-driven object recognition using a Dynamic Vision Sensor (DVS). The first, which we call Poker-DVS and is being released together with this article, was obtained by browsing specially made poker card decks in front of a DVS camera for 2–4 s. Each card appeared on the screen for about 20–30 ms. The poker pips were tracked and isolated off-line to constitute the 131-recording Poker-DVS database. The second database, which we call MNIST-DVS and which was released in December 2013, consists of a set of 30,000 DVS camera recordings obtained by displaying 10,000 moving symbols from the standard MNIST 70,000-picture database on an LCD monitor for about 2–3 s each. Each of the 10,000 symbols was displayed at three different scales, so that event-driven object recognition algorithms could easily be tested for different object sizes. This article tells the story behind both databases, covering, among other aspects, details of how they work and the reasons for their creation. We provide not only the databases with corresponding scripts, but also the scripts and data used to generate the figures shown in this article (as Supplementary Material).