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Related Experiment Videos

On algorithmic rate-coded AER generation.

Alejandro Linares-Barranco1, Gabriel Jimenez-Moreno, Bernabé Linares-Barranco

  • 1Arquitectura y Tecnología de Computadores, ETSI Informática, 41012 Sevilla, Spain. alinares@atc.us.es

IEEE Transactions on Neural Networks
|May 26, 2006
PubMed
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This study converts conventional video frames into event-based representations (Address-Event-Representation or AER) using algorithms. Linear-feedback-shift-register (LFSR) methods offer a real-time solution with well-distributed events.

Area of Science:

  • Computer Vision
  • Neuromorphic Engineering
  • Signal Processing

Background:

  • Conventional video streams use frame-based representations.
  • Spike event-based representations, like Address-Event-Representation (AER), offer efficient data transmission.
  • Bridging these representations is crucial for integrating AER systems with existing video technology.

Purpose of the Study:

  • To develop and evaluate algorithms for converting frame-based video to rate-coded Address-Event-Representation (AER).
  • To assess the real-time feasibility and event distribution quality of proposed conversion methods.
  • To compare algorithmic approaches against naturally generated AER data from VLSI chips.

Main Methods:

  • Algorithmic development for frame-to-event conversion.

Related Experiment Videos

  • Software implementation and testing of various algorithms.
  • Comparative evaluation based on real-time performance and event stream characteristics.
  • Hardware implementation of a selected algorithm using FPGA for real-time demonstration.

    • Main Results:

    • Simple algorithms achieve real-time performance but yield dissimilar event distributions compared to VLSI AER.
    • Sophisticated algorithms produce better event distributions but are not efficient for real-time processing.
    • Linear-feedback-shift-register (LFSR) based methods provide a balance between real-time feasibility and event distribution quality.
    • Software experiments showed processing times between 0.011 and 1.14 ms per pixel.
    • Hardware demonstration achieved 25 frames/sec for 64x64 frames, reaching 10^7 events/sec.

    Conclusions:

    • LFSR-based algorithms present a viable compromise for real-time frame-to-AER conversion.
    • The developed methods can generate AER streams that reasonably approximate naturally produced ones.
    • Real-time hardware implementation validates the practical applicability of the proposed approach.