---
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](https://huggingface.co/datasets/bdager/CHIRLA) ·
[Paper](https://www.nature.com/articles/s41597-025-06425-3) · [Code](https://github.com/bdager/CHIRLA) ·
[Project page](https://bdager.github.io/CHIRLA/). 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

```bibtex
@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}
}
```