Poster De Conférence Année : 2025

Impact of frame-based representations for event-based data in the field of gesture recognition

Résumé

Gesture recognition using event-based data represents a promising direction in neuromorphic computing, leveraging the asynchronous nature of dynamic vision sensors (DVS) to overcome limitations of traditional frame-based video processing. However, before developing fully spiking solutions, we aim to understand what is the most appropiate use that can be done of event-spike data in presence of a basic convolutional architecture. This work provides insights on the behavior of different conversion methods such as aggregating frames (time-window, spike-count, n-bis), binary representation or time surfaces. These representations are challenged on accuracy metrics in the framework of gesture recognition.

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Dates et versions

hal-05330405 , version 1 (24-10-2025)

Identifiants

Citer

Róbert-Levente Osváth, Grigoreta Sofia Cojocar, Ioan Marius Bilasco. Impact of frame-based representations for event-based data in the field of gesture recognition. Neuromorphic Computing for Development and Learning Workshop, Sep 2025, Prague (CZ), Czech Republic. Zenodo, 2025, ⟨10.5281/zenodo.15882836⟩. ⟨hal-05330405⟩
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