This is the code for the 2021 3DV paper ESL: Event-based Structured Light by Manasi Muglikar, Guillermo Gallego, and Davide Scaramuzza.
A pdf of the paper is available here. If you use this code in an academic context, please cite the following work:
@InProceedings{Muglikar213DV,
author = {Manasi Muglikar and Guillermo Gallego and Davide Scaramuzza},
title = {ESL: Event-based Structured Light},
booktitle = {{IEEE} International Conference on 3D Vision.(3DV)},
month = {Dec},
year = {2021}
} conda create -y -n ESL python=3.
conda activate ESL
conda install numba
conda install -y -c anaconda numpy scipy
conda install -y -c conda-forge h5py opencv tqdm matplotlib pyyaml pylops
conda install -c open3d-admin -c conda-forge open3d
The recordings are available in numpy file format here.
You can downlaoad the city_of_lights events file from here.
Please unzip it and ensure the data is organized as follows:
-dataset
calib.yaml
-city_of_lights/
-scans_np/
-cam_ts00000.npy
.
.
.
-cam_ts00060.npyThe numpy file refers to the camera time map for each projector scan.
The time map is normalized in the range [0, 1].
The time map for the city_of_lights looks as follows:
The calibration file for our setup, data/calib.yaml, follows the OpenCV yaml format.
To compute depth from the numpy files use the script below:
python python/compute_depth.py -object_dir=dataset/static/city_of_lights/ -calib=dataset/calib.yaml -num_scans 1The estimated depth will be saved as numpy files in the depth_dir/esl_dir subfolder of the dataset directory.
The estimated depth for the city_of_lights dataset can be visualized using the visualization script visualize_depth.py:
We evaluate the performance for static sequences using two metrics with respect to ground truth: root mean square error (RMSE) and Fill-Rate (i.e., completion).
python python/evaluate.py -object_dir=dataset/static/city_of_lightsThe output should look as follows:
Average scene depth: 105.47189659236103
============================Stats=============================
========== ESL stats ==============
Fill rate: 0.9178120881189983
RMSE: 1.160292387864739
=======================================================================