A causal, density-based event subsampling method preserves classification accuracy better than random, spatial, temporal, event-count, and corner-based baselines in sparse regimes, except when event counts vary widely across videos.
Asynchronous Cor- ner Detection and Tracking for Event Cameras in Real Time
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Making Every Event Count: Balancing Data Efficiency and Accuracy in Event Camera Subsampling
A causal, density-based event subsampling method preserves classification accuracy better than random, spatial, temporal, event-count, and corner-based baselines in sparse regimes, except when event counts vary widely across videos.