|
|
--- |
|
|
license: apache-2.0 |
|
|
tags: |
|
|
- egocentric |
|
|
- exotenric |
|
|
- surgery |
|
|
- or |
|
|
- scene-graph |
|
|
- activity-understanding |
|
|
- gaze |
|
|
- hand |
|
|
--- |
|
|
# EgoExOR-HQ: An Ego-Exo-Centric Operating Room Dataset for Surgical Activity Understanding |
|
|
|
|
|
[](https://huggingface.co/datasets/TUM/EgoExOR) |
|
|
[](https://github.com/ardamamur/EgoExOR) |
|
|
[](https://neurips.cc/) |
|
|
|
|
|
**EgoExOR-HQ** — This repository hosts the **enriched high-quality release** of the EgoExOR dataset. For scene graph generation code, benchmarks, and pretrained models, see the [main EgoExOR repository](https://github.com/ardamamur/EgoExOR). |
|
|
|
|
|
**Authors:** Ege Özsoy, Arda Mamur, Felix Tristram, Chantal Pellegrini, Magdalena Wysocki, Benjamin Busam, Nassir Navab |
|
|
|
|
|
## ✨ What's New in EgoExOR-HQ |
|
|
|
|
|
This release adds: |
|
|
- **High-quality images** — 1344×1344 resolution (instead of 336×336) |
|
|
- **Raw depth images** — From external RGB-D cameras (instead of pre-merged point clouds), so you can build merged or per-camera point clouds for your use case |
|
|
- **Per-device audios** — Separate audio streams per microphone |
|
|
|
|
|
## Overview |
|
|
|
|
|
Operating rooms (ORs) demand precise coordination among surgeons, nurses, and equipment in a fast-paced, occlusion-heavy environment, necessitating advanced perception models to enhance safety and efficiency. Existing datasets either provide partial egocentric views or sparse exocentric multi-view context, but do not explore the comprehensive combination of both. |
|
|
|
|
|
We introduce **EgoExOR**, the first OR dataset and accompanying benchmark to fuse first-person and third-person perspectives. Spanning 94 minutes (84,553 frames at 15 FPS) of two emulated spine procedures—*Ultrasound-Guided Needle Insertion* and *Minimally Invasive Spine Surgery*—EgoExOR integrates: |
|
|
|
|
|
- **Egocentric:** RGB, gaze, hand tracking, audio from wearable glasses |
|
|
- **Exocentric:** RGB and depth from RGB-D cameras, ultrasound imagery |
|
|
- **Annotations:** 36 entities, 22 relations (568,235 triplets) for scene graph generation |
|
|
|
|
|
This dataset sets a new foundation for OR perception, offering a rich, multimodal resource for next-generation clinical perception. |
|
|
|
|
|
## 🌟 Key Features |
|
|
|
|
|
- **Multiple modalities** — RGB video, audio (full waveform + per-frame snippets, per-device), eye gaze, hand tracking, raw depth, and scene graph annotations |
|
|
- **Time-synchronized streams** — All modalities aligned on a common timeline for precise cross-modal correlation |
|
|
- **High-resolution RGB** — 1344×1344 frames for fine-grained visual analysis |
|
|
- **Raw depth** — Build custom point clouds or depth-based models; depth from external RGB-D cameras only |
|
|
- **Per-device audio** — Separate microphone streams for spatial or multi-channel audio processing |
|
|
|
|
|
## 📂 Dataset Structure |
|
|
|
|
|
The dataset is distributed as **phase-level HDF5 files** for efficient download: |
|
|
|
|
|
| File | Description | |
|
|
|------|-------------| |
|
|
| `miss_1.h5` | MISS procedure, phase 1 | |
|
|
| `miss_2.h5` | MISS procedure, phase 2 | |
|
|
| `miss_3.h5` | MISS procedure, phase 3 | |
|
|
| `miss_4.h5` | MISS procedure, phase 4 | |
|
|
|
|
|
To obtain a single merged file (including splits), use the merge utility from the [main EgoExOR repository](https://github.com/ardamamur/EgoExOR) (see `data/README.md`). |
|
|
|
|
|
### HDF5 Schema |
|
|
|
|
|
``` |
|
|
/metadata |
|
|
/vocabulary/entity — Entity names and IDs (instruments, anatomy, etc.) |
|
|
/vocabulary/relation — Relation names and IDs (holding, cutting, etc.) |
|
|
/sources/sources — Camera/source names and IDs (head_surgeon, external_1, etc.) |
|
|
/dataset — version, creation_date, title |
|
|
|
|
|
/procedures/{procedure}/phases/{phase}/takes/{take}/ |
|
|
/sources — source_count, source_0, source_1, … (camera roles) |
|
|
/frames/rgb — (num_frames, num_cameras, H, W, 3) uint8 — 1344×1344 |
|
|
/eye_gaze/coordinates — (num_frames, num_ego_cameras, 3) float32 — gaze 2D + camera ID |
|
|
/eye_gaze_depth/values — (num_frames, num_ego_cameras) float32 |
|
|
/hand_tracking/positions — (num_frames, num_ego_cameras, 17) float32 |
|
|
/audio/waveform — Full stereo waveform |
|
|
/audio/snippets — 1-second snippets aligned to frames |
|
|
/audio/per_device/ — Per-microphone waveform and snippets |
|
|
/point_cloud/depth/values — Raw depth images (external cameras; others zero-filled) |
|
|
/point_cloud/merged/ — Not populated; use raw depth to build point clouds yourself |
|
|
/annotations/ — Scene graph annotations (frame_idx, rel_annotations, scene_graph) |
|
|
|
|
|
/splits |
|
|
train, validation, test — Split tables (procedure, phase, take, frame_id) |
|
|
``` |
|
|
|
|
|
**Note:** Camera/source IDs in `eye_gaze/coordinates` map to `metadata/sources` for correct source names. |
|
|
|
|
|
## ⚙️ Efficiency and Usability |
|
|
|
|
|
- **HDF5** — Hierarchical structure, partial loading, gzip compression |
|
|
- **Chunking** — Efficient access to frame ranges for sequence-based training |
|
|
- **Logical layout** — `procedures → phases → takes → modality` for easy navigation |
|
|
|
|
|
## 📜 License |
|
|
|
|
|
Released under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0). Free for academic and commercial use with attribution. |
|
|
|
|
|
## 📚 Citation |
|
|
|
|
|
```bibtex |
|
|
@misc{özsoy2025egoexoregoexocentricoperatingroom, |
|
|
title={EgoExOR: An Ego-Exo-Centric Operating Room Dataset for Surgical Activity Understanding}, |
|
|
author={Ege Özsoy and Arda Mamur and Felix Tristram and Chantal Pellegrini and Magdalena Wysocki and Benjamin Busam and Nassir Navab}, |
|
|
year={2025}, |
|
|
eprint={2505.24287}, |
|
|
archivePrefix={arXiv}, |
|
|
primaryClass={cs.CV}, |
|
|
url={https://arxiv.org/abs/2505.24287}, |
|
|
} |
|
|
``` |
|
|
|
|
|
## 🔗 Related Resources |
|
|
|
|
|
- **Original EgoExOR (v1)** — [ardamamur/EgoExOR](https://huggingface.co/datasets/ardamamur/EgoExOR) — 336×336 images, pre-merged point clouds, merged audio |
|
|
- **Code, benchmarks, pretrained model** — [github.com/ardamamur/EgoExOR](https://github.com/ardamamur/EgoExOR) |
|
|
|
|
|
--- |
|
|
**Dataset:** [TUM/EgoExOR](https://huggingface.co/datasets/TUM/EgoExOR) · **Last Updated:** February 2025 |
