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Event-Based Attention and Tracking on Neuromorphic Hardware
AbstractWe present a fully event-driven vision and processing system for selective attention and tracking, realized on a neuromorphic processor Loihi interfaced to an event-based Dynamic Vision Sensor DAVIS. The attention mechanism is realized as a recurrent spiking neural network that implements attractor-dynamics of dynamic neural fields. We demonstrate capability of the system to create sustained activation that supports object tracking when distractors are present or when the object slows down or stops, reducing the number of generated events.
Related Material
[pdf] [dataset][bibtex]@InProceedings{Renner_2019_CVPR_Workshops,
author = {Renner, Alpha and Evanusa, Matthew and Sandamirskaya, Yulia},
title = {Event-Based Attention and Tracking on Neuromorphic Hardware},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2019}
}
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