{"url":"/dataset/bpod","name":"BPOD","full_name":null,"description_markdown":"**Brown Pedestrian Odometry Dataset** (**BPOD**) is a dataset for benchmarking visual odometry algorithms in head-mounted pedestrian settings. This dataset was captured using synchronized global and rolling shutter stereo cameras in 12 diverse indoor and outdoor locations on Brown University's campus. Compared to existing datasets, BPOD contains more image blur and self-rotation, which are common in pedestrian odometry but rare elsewhere. Ground-truth trajectories are generated from stick-on markers placed along the pedestrian’s path, and the pedestrian's position is documented using a third-person video.","description_withheld":null,"homepage":"https://doi.org/10.26300/c1n7-7p93","introduced_date":"2021-12-24","introduced_date_note":null,"introduced_by":{"paper":"/paper/benchmarking-pedestrian-odometry-the-brown","title":"Benchmarking Pedestrian Odometry: The Brown Pedestrian Odometry Dataset (BPOD)","first_author":"David Charatan","url":null},"license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Visual Odometry","url":"/task/visual-odometry","datasets_with_task":"/datasets/task/visual-odometry"}],"languages":[],"variants":["BPOD"],"data_loaders":[],"num_papers_in_archive":1,"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."}