Event-Based Attention and Tracking on Neuromorphic Hardware

Alpha Renner, Matthew Evanusa, Yulia Sandamirskaya

CVPRW 2019 pp. 1709-1716

doi:10.1109/CVPRW.2019.00220 /cvprw/2019/renner2019cvprw-eventbased/

Abstract

We 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.

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Cite

Text

Renner et al. "Event-Based Attention and Tracking on Neuromorphic Hardware." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2019. doi:10.1109/CVPRW.2019.00220

Markdown

[Renner et al. "Event-Based Attention and Tracking on Neuromorphic Hardware." IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2019.](https://mlanthology.org/cvprw/2019/renner2019cvprw-eventbased/) doi:10.1109/CVPRW.2019.00220

BibTeX

@inproceedings{renner2019cvprw-eventbased,
  title     = {{Event-Based Attention and Tracking on Neuromorphic Hardware}},
  author    = {Renner, Alpha and Evanusa, Matthew and Sandamirskaya, Yulia},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year      = {2019},
  pages     = {1709-1716},
  doi       = {10.1109/CVPRW.2019.00220},
  url       = {https://mlanthology.org/cvprw/2019/renner2019cvprw-eventbased/}
}