Instituto de Microelectrónica de Sevilla, IMSE-CNM (CSIC & Univ. of Sevilla), Sevilla, SPAIN.
of a set of 131 poker pip symbols tracked and extracted from 3
separate DVS recordings, while browsing
very quickly poker cards.
A first version with only 40 symbols was used in the ConvNet symbol recognition paper:
J. A. Pérez-Carrasco, et. al, "Mapping from Frame-Driven to Frame-Free Event-Driven Vision Systems by Low-Rate Rate-Coding and Coincidence Processing. Application to Feed-Forward ConvNets," IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 35, No. 11, pp. 2706-2719, Nov. 2013. (video). Doi: http://doi.ieeecomputersociety.org/10.1109/TPAMI.2013.71. See also this nice video provided by T. Delbruck (click).
The DVS used is a high-sensitive DVS described in:
T. Serrano-Gotarredona and B. Linares-Barranco, "A 128x128 1.5% Contrast Sensitivity 0.9% FPN 3us Latency 4mW Asynchronous Frame-Free Dynamic Vision Sensor Using Transimpedance Amplifiers," IEEE J. Solid-State Circuits, vol.48, No. 3, pp. 827-838, March 2013 (available from:
Original DVS recorded files are
128x128 pixel and can be displayed with jAER (available
MatlabTM scripts are provided to track and
extract individual poker pip symbols as they cross the
screen and extract them as 32x32 pixel event streams, each
of which can also be visualized with jAER. The extracted
symbols are readily available (no need to run the MatlabTM scripts).
This database can be downloaded free of charge, provided it is used for non-commercial purposes and the original source is credited in publications and reports.
it go to http://imse-cnm.csic.es/caviar/POKER_DVS.