{"url":"/dataset/luvira","name":"LuViRA","full_name":"Lund University Vision, Radio, and Audio","description_markdown":"The Lund University Vision, Radio, and Audio (LuViRA) positioning dataset consists of 89 trajectories that are recorded in the Lund University Humanities Lab's Motion Capture (Mocap) Studio using a MIR200 robot as the targeted platform. Each trajectory contains data from four different systems, vision, radio, audio and a ground truth system that can provide within 0.5mm localization accuracy. A Motion Capture (Mocap) system in the environment is used as the ground truth system, which provides 3D or 6DoF tracking of a camera, a single antenna and a speaker. These targets are mounted on top of the MIR200 robot and put in motion. 3D positions of the 11 static microphones are also provided.","description_withheld":null,"homepage":"https://github.com/ilaydayaman/LuViRA_Dataset","introduced_date":"2023-02-10","introduced_date_note":null,"introduced_by":{"paper":"/paper/the-luvira-dataset-measurement-description","title":"The LuViRA Dataset: Synchronized Vision, Radio, and Audio Sensors for Indoor Localization","first_author":"Ilayda Yaman","url":null},"license":{"name":"CC-BY-4.0 license","url":null},"modalities":[{"name":"Audio","url":"/datasets/modality/audio"},{"name":"RGB Video","url":"/datasets/modality/rgb-video"}],"tasks":[{"name":"Indoor Localization","url":"/task/indoor-localization","datasets_with_task":"/datasets/task/indoor-localization"}],"languages":[],"variants":["LuViRA"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}