UEOF

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Authors: Nick Truong, Pritam Karmokar, William J. Beksi
Cited by: 0

Abstract

UEOF is the first synthetic underwater event-based optical flow dataset derived from physically-based ray-traced RGBD sequences. It was constructed using a modern video-to-event pipeline applied to rendered underwater videos. It consists of realistic event data streams with dense ground-truth flow, depth, and camera motion. The dataset is composed of 12 minutes and 51 seconds of data across 13,714 RGB frames. This results in a total of 4.94 billion events across all scenes. UEOF exhibits a high dynamic range of motion with a mean flow magnitude of 6.1 px and a median of 3.6 px. The motion distribution is heavy-tailed. While a majority of pixels undergo moderate displacement (with a 95th percentile of 21.20 px), the dataset also includes significant high-magnitude flow upwards of 80 px.

Fields of Study & Subjects

Advanced Vision and Imaging Video Surveillance and Tracking Methods Robotics and Sensor-Based Localization

Publication details

Publication date
19 February 2026
Language
EN
Document type
Dataset