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New technique quantifies noise in dynamic vision sensors

Researchers have developed a new technique using Detrended Fluctuation Analysis (DFA) to quantify background activity noise in Dynamic Vision Sensors (DVS). This method allows for the characterization of noise and signal without requiring ground truth data, addressing a key challenge in DVS applications. The technique also aids in deriving optimal parameters for denoising filters, with its effectiveness demonstrated on a real-world moving-car dataset. AI

RANK_REASON The cluster contains an academic paper detailing a new method for sensor noise quantification. [lever_c_demoted from research: ic=1 ai=0.7]

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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Evgeny V. Votyakov, Alessandro Artusi ·

    Quantifying Noise of Dynamic Vision Sensor

    arXiv:2404.01948v3 Announce Type: replace Abstract: Dynamic visual sensors (DVS) are characterized by a large amount of background activity (BA) noise, which it is mixed with the original (cleaned) sensor signal. The dynamic nature of the signal and the absence in practical appli…