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Main Author: Li, Yixin
Format: Recurso digital
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Published: Zenodo 2026
Online Access:https://doi.org/10.5281/zenodo.20355567
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author Li, Yixin
author_facet Li, Yixin
contents <div>This archive contains the manually annotated ground-truth trajectories for the UDMT behavioral recording datasets. The corresponding behavioral videos are provided at Zenodo record 14580256: https://zenodo.org/records/14580256. The annotation files are stored in MOT format and can be matched to the videos according to their dataset/video names.</div> <div> </div> <div>Each annotation file follows the standard MOT-style frame-level format, where each row corresponds to one annotated animal instance in one annotated frame. The annotations provide object identities and bounding-box locations for evaluating multi-animal tracking performance.</div> <div> </div> <div>The manual annotations were generated at fixed frame intervals rather than for every video frame. The annotation interval depends on the dataset name:</div> <div> </div> <div>- Datasets containing "94hz": one annotated frame every 600 frames.</div> <div>- Datasets containing "flies": one annotated frame every 150 frames.</div> <div>- Datasets containing "celegans": one annotated frame every 150 frames.</div> <div>- All other datasets: one annotated frame every 300 frames.</div> <div> </div> <div>The dataset names and video names are designed to correspond directly by filename. </div> <div> </div> <div>These annotations are intended for quantitative evaluation of tracking accuracy and identity consistency in UDMT and related multi-animal tracking methods.</div>
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spellingShingle UDMT dataset: Manual annotations for behavioral recordings used in unsupervised multi-animal tracking
Li, Yixin
<div>This archive contains the manually annotated ground-truth trajectories for the UDMT behavioral recording datasets. The corresponding behavioral videos are provided at Zenodo record 14580256: https://zenodo.org/records/14580256. The annotation files are stored in MOT format and can be matched to the videos according to their dataset/video names.</div> <div> </div> <div>Each annotation file follows the standard MOT-style frame-level format, where each row corresponds to one annotated animal instance in one annotated frame. The annotations provide object identities and bounding-box locations for evaluating multi-animal tracking performance.</div> <div> </div> <div>The manual annotations were generated at fixed frame intervals rather than for every video frame. The annotation interval depends on the dataset name:</div> <div> </div> <div>- Datasets containing "94hz": one annotated frame every 600 frames.</div> <div>- Datasets containing "flies": one annotated frame every 150 frames.</div> <div>- Datasets containing "celegans": one annotated frame every 150 frames.</div> <div>- All other datasets: one annotated frame every 300 frames.</div> <div> </div> <div>The dataset names and video names are designed to correspond directly by filename. </div> <div> </div> <div>These annotations are intended for quantitative evaluation of tracking accuracy and identity consistency in UDMT and related multi-animal tracking methods.</div>
title UDMT dataset: Manual annotations for behavioral recordings used in unsupervised multi-animal tracking
url https://doi.org/10.5281/zenodo.20355567