README.md

metadata

pretty_name: MultiCameraDataset (CHIRLA subset)
license: cc-by-4.0
tags:
  - multi-camera
  - tracking
  - person-reidentification
  - mtmc
configs:
  - config_name: videos
    data_files:
      - split: train_all
        path: data/videos_train_all.parquet
      - split: test_all
        path: data/videos_test_all.parquet

MultiCameraDataset

A trimmed copy of the CHIRLA dataset, kept for building a multi-target multi-camera (MTMC) person tracking pipeline from scratch: raw videos plus full per-frame identity annotations. The Re-ID / tracking benchmark crops and their Parquet manifests from the original release were removed.

Original dataset: bdager/CHIRLA · Paper · Code · Project page. All credit for data collection and annotation goes to the CHIRLA authors. Redistributed under CC BY 4.0; the only modifications are the removal of files and renaming of : to - in file names (Windows compatibility).

Contents

Path	Description
videos/seq_XXX/camera_N_<timestamp>.avi	70 videos (10 sequences × 7 cameras), 1080×720, 30 fps
videos/metadata.parquet	file_name, annotation_path, camera, seq
annotations/seq_XXX/camera_N_<timestamp>.json	Per-frame boxes: {"<frame>": [{"id": int, "BboxP": [x1,y1,x2,y2]}]}
data/videos_{train,test}_all.parquet	Official video-level split (train = seq_004, seq_026)
filename_mapping.csv	Original path (with :) ↔ path in this repo (with -)
docs/	Floor plan with camera positions and a sample view per camera

Notes:

• Frame keys in annotations start at 1.
• Person IDs are consistent across all cameras and all sequences (21 positive IDs).
• Paths inside the Parquet files still contain :; apply path.replace(':', '-') before opening.
• Cameras share a start timestamp per sequence, but frame counts differ by up to 60 frames (2 s).
• Camera views barely overlap; there is no calibration or ground-plane homography.

Out-of-scope use

Do not use this data to surveil, identify, or track real people without their consent. 22 participants do not represent general demographics.

Citation

@article{dominguezdager2026chirla,
  title   = {CHIRLA: Comprehensive High-resolution Identification and Re-identification for Large-scale Analysis},
  author  = {Domínguez-Dager, Bessie and Escalona, Felix and Gomez-Donoso, Francisco and Cazorla, Miguel},
  journal = {Scientific Data},
  volume  = {13},
  pages   = {109},
  year    = {2026},
  doi     = {10.1038/s41597-025-06425-3}
}