Charles P. Rizzo, Catherine D. Schuman and James S. Plank

July, 2022

ICONS: International Conference on Neuromorphic Systems

https://dl.acm.org/doi/proceedings/10.1145/3546790

View Article

Abstract

Event-based cameras are cameras with high dynamic range that measure changes in light intensity at each pixel instead of capturing frames like traditional cameras. There are several event-based camera simulation software libraries that can convert videos or collections of frames to a stream of simulated camera events. To the authors’ knowledge, with the exception of vehicle control projects, there are no software libraries that simulate event-based camera activity online during an agent’s training phase on other various control applications. This work introduces ALE_EBC, a software wrapper around the Arcade Learning Environment that converts game frames to simulated event-based camera event streams, allowing agents to be trained on a variety of control-based Atari games through the lens of a neuromorphic camera.

Citation Information

Text

author       C. P. Rizzo and C. D. Schuman and J. S. Plank
title        Event-Based Camera Simulation Wrapper for Arcade Learning Environment
booktitle    International Conference on Neuromorphic Computing Systems (ICONS)
publisher    ACM
pages        1-5
year         2022

Bibtex

@INPROCEEDINGS{rsp:22:ebc,
    author = "C. P. Rizzo and C. D. Schuman and J. S. Plank",
    title = "Event-Based Camera Simulation Wrapper for {A}rcade {L}earning {E}nvironment",
    booktitle = "International Conference on Neuromorphic Computing Systems (ICONS)",
    publisher = "ACM",
    pages = "1-5",
    year = "2022"
}