Frontiers in Neuroscience (Jan 2020)

Sepia, Tarsier, and Chameleon: A Modular C++ Framework for Event-Based Computer Vision

  • Alexandre Marcireau,
  • Sio-Hoi Ieng,
  • Ryad Benosman,
  • Ryad Benosman,
  • Ryad Benosman

DOI
https://doi.org/10.3389/fnins.2019.01338
Journal volume & issue
Vol. 13

Abstract

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This paper introduces an new open-source, header-only and modular C++ framework to facilitate the implementation of event-driven algorithms. The framework relies on three independent components: sepia (file IO), tarsier (algorithms), and chameleon (display). Our benchmarks show that algorithms implemented with tarsier are faster and have a lower latency than identical implementations in other state-of-the-art frameworks, thanks to static polymorphism (compile-time pipeline assembly). The observer pattern used throughout the framework encourages implementations that better reflect the event-driven nature of the algorithms and the way they process events, easing future translation to neuromorphic hardware. The framework integrates drivers to communicate with the DVS, the DAVIS, the Opal Kelly ATIS, and the CCam ATIS.

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