Frequency Analysis on Neuromorphic Data Using Discrete Fourier Transform | IEEE Conference Publication | IEEE Xplore

Frequency Analysis on Neuromorphic Data Using Discrete Fourier Transform


Abstract:

Event cameras are a relatively new sensor technology on the rise that captures changes in the observed scene. Since the signal is asynchronous and tends to be sparse the ...Show More

Abstract:

Event cameras are a relatively new sensor technology on the rise that captures changes in the observed scene. Since the signal is asynchronous and tends to be sparse the sensor is very power efficient, has a low latency, and has a remarkably high temporal resolution. Processing event-based signals of this kind in an effective way, taking full advantage of the technology, requires new signal processing methodologies. This paper proposes a simple yet powerful method for frequency analysis of event-based data using a Discrete Fourier Transform (DFT). The method is tested and evaluated on data sequences acquired from modulated light emitting diodes and a small UAV captured using an iniVation DVXplorer event camera. We show that the method can be used to detect frequencies that change relatively quickly (from 10 Hz-1 kHz in one second), several different frequencies in the same image at the same time, and to detect the rotation frequency of a drone propeller. This can be useful e.g. in the field of UAV detection.
Date of Conference: 16-19 October 2023
Date Added to IEEE Xplore: 21 November 2023
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Conference Location: Paris, France

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