SOURCE-LINKED INTELLIGENCE

Event-Based Motion Estimation via Oriented Distance Fields

arXiv · AI, language, vision and robotics · article · Aug 25, 2026 · UTC

Event-based motion estimation is central to tasks that demand high temporal resolution and robustness to fast motion. Existing methods typically rely on iterative optimization or repeated hypothesis comparison, offsetting the sensor's low-latency advantage. We propose Oriented Distance Field Motion Estimation (ODF Motion Estimation), which replaces this optimization with a single averaging step over a precomputed field of event distance vectors, combined with an adaptive event-count selection strategy and a parameter-free trail filter. On public and self-collected datasets, ODF motion estimati

Read original source ↗ Open in workspace

recordType

paper

region

Global