AUTHOR=Clady Xavier , Maro Jean-Matthieu , Barré Sébastien , Benosman Ryad B. 

TITLE=A Motion-Based Feature for Event-Based Pattern Recognition

JOURNAL=Frontiers in Neuroscience

VOLUME=Volume 10 - 2016

YEAR=2017

URL=https://www.frontiersin.org/journals/neuroscience/articles/10.3389/fnins.2016.00594

DOI=10.3389/fnins.2016.00594

ISSN=1662-453X

ABSTRACT=This paper introduces an event-based luminance-free feature from the output of asynchronous 
event-based neuromorphic retinas. The feature consists in mapping into a matrix, the distribution 
of the optical flow along the contours of the moving objects in the visual scene. Asynchronous 
event-based neuromorphic retinas are composed of autonomous pixels, each of them asynchronously 
generating ''spiking'' events that encode relative changes in pixels' illumination at high temporal 
resolutions. The optical flow is computed at each event, and is integrated locally or globally in a 
speed and direction coordinate frame based grid, using speed-tuned temporal kernels. The latter
ensures that the resulting feature represents equitably the distribution of the normal motion 
along the current moving edges, whatever their respective dynamics. The usefulness and the 
genericness of the proposed feature are demonstrated in pattern recognition applications: local 
corner detection and global gesture recognition.