SOURCE-LINKED INTELLIGENCE

Real-time Unsupervised Object Discovery from Asynchronous Event Streams

arXiv · AI, language, vision and robotics · article · Aug 27, 2026 · UTC

Event cameras capture pixel-level intensity changes with microsecond resolution to produce highly sparse asynchronous data streams. For visual perception in latency-critical environments, we propose a lightweight, training-free framework for discovery of moving objects based on spatio-temporal clustering. This framework is driven by two core contributions. First, a linear-time Spatio-temporal Probabilistic Event Filter (SPEF) that introduces an adaptive event acceptance threshold to distinguish salient motion structures from background noise. Second, an Event Morton Code Clustering (EMCC) modu

Read original source ↗ Open in workspace

recordType

paper

region

Global