MBARI-org/DeepSea-MOT

DeepSea MOT

DeepSea MOT is a benchmark dataset for multi-object tracking on deep-sea video.

Dataset Description

DeepSea MOT consists of 4 video sequences (2 midwater, 2 benthic) with a total of 2,400 frames and 57,376 annotated objects comprising 188 tracks. The videos were captured by the Monterey Bay Aquarium Research Institute (MBARI) using remotely operated vehicles (ROVs) Doc Ricketts and Ventana in deep-sea environments, showcasing a variety of marine species and underwater scenes.

• Paper: https://arxiv.org/abs/TBD
• Workflow: https://docs.mbari.org/benchmark_eval/

File Structure

The dataset is organized as follows:

data/
├── vidseq_names.txt          # TrackEval sequence names file
├── BD/                       # Benthic Difficult sequence
│   ├── BD.mov                # Source video file
│   ├── gt.txt                # MOT Challenge format ground truth
│   ├── seqinfo.ini           # TrackEval sequence information
│   ├── images/               # Frame images (JPG format)
│   │   ├── BD_001.jpg
│   │   ├── BD_002.jpg
│   │   └── ...
│   ├── labels/               # YOLO-formatted annotation files (TXT)
│   └── xml/                  # Pascal VOC annotation files (from RectLabel)
├── BS/                       # Benthic Simple sequence
│   ├── BS.mov
│   ├── gt.txt
│   ├── seqinfo.ini
│   ├── images/
│   ├── labels/
│   └── xml/
├── MWD/                      # Midwater Difficult sequence
│   ├── MWD.mov
│   ├── gt.txt
│   ├── seqinfo.ini
│   ├── images/
│   ├── labels/
│   └── xml/
└── MWS/                      # Midwater Simple sequence
    ├── MWS.mov
    ├── gt.txt
    ├── seqinfo.ini
    ├── images/
    ├── labels/
    └── xml/

Each sequence directory contains:

• Source video (.mov): Original ROV footage
• Ground truth (gt.txt): MOT Challenge format annotations for tracking evaluation
• Sequence info (seqinfo.ini): Metadata file for TrackEval compatibility
• Images (images/): Individual frame extractions in JPG format
• YOLO labels (labels/): Object detection annotations in YOLO format (TXT files)
• Pascal VOC (xml/): Object detection annotations in Pascal VOC format (generated via RectLabel)

Additional Information

Dataset Curators

Authors of [1]:

• Kevin Barnard
• Elaine Liu
• Kristine Walz
• Brian Schlining
• Nancy Jacobsen Stout
• Lonny Lundsten

Citation Information

@article{barnard2025deepseamot,
    author = {Barnard, Kevin and Liu, Elaine and Walz, Kristine and Schlining, Brian and Stout, Nancy Jacobsen and Lundsten, Lonny},
    title = { {DeepSea MOT}: A benchmark dataset for multi-object tracking on deep-sea video},
    year = {2025},
    journal = {arXiv preprint arXiv:2501.XXXXX},
    doi = {10.48550/arXiv.2501.XXXXX},
}