This repository contains code designed to facilitate the evaluation of depth-related metrics for Intel RealSense stereo cameras and Stereolabs ZED cameras. These metrics are crucial for assessing the accuracy and performance of stereo camera systems in tasks such as 3D reconstruction, object detection, and depth estimation. This repository was used for the following paper: Comparative evaluation of three commercially available markerless depth sensors for close-range use in surgical simulation.
For a more detailed description, including evaluation setup and additional results, we refer you to our associated paper.
Purpose Minimally invasive surgeries have restricted surgical ports, demanding a high skill level from the surgeon. Surgical simulation potentially reduces this steep learning curve and additionally provides quantitative feedback. Markerless depth sensors show great promise for quantification, but most such sensors are not designed for accurate reconstruction of complex anatomical forms in close-range.
Methods
This work compares three commercially available depth sensors, namely the Intel
Results The Intel cameras show sub-mm accuracy in most static environments.
The
Conclusion If a high temporal resolution is needed and lower spatial resolution is acceptable, the Zed-Mini is the best choice, whereas the Intel
├── LICENSE
├── README.md <- The top-level README for developers using this project.
├── src <- Source code of the project.
│ ├── notebooks <- Example Jupyter notebooks how to use the metrics and data loading functions.
│ ├── inout <- Helper function to read and load images and depth values from .bag and .svo files
│ └── metrics <- Metrics definitions
@article{Burger2023,
title = {Comparative evaluation of three commercially available markerless depth sensors for close-range use in surgical simulation},
volume = {18},
ISSN = {1861-6429},
url = {http://dx.doi.org/10.1007/s11548-023-02887-1},
DOI = {10.1007/s11548-023-02887-1},
number = {6},
journal = {International Journal of Computer Assisted Radiology and Surgery},
publisher = {Springer Science and Business Media LLC},
author = {Burger, Lukas and Sharan, Lalith and Karl, Roger and Wang, Christina and Karck, Matthias and De Simone, Raffaele and Wolf, Ivo and Romano, Gabriele and Engelhardt, Sandy},
year = {2023},
month = may,
pages = {1109–1118}
}