EasySFM

A simple Structure-from-motion project for ETH P3DV (Photogrammetry and 3D Vision) course

C++ version passed

Environment: Linux (Ubuntu 16.04)

How to use

1. Install dependent 3rd libraries

OpenCV(>=3) with contrib,PCL(>=1.7), Eigen3, Ceres

2. Compile

cd cpp_code
mkdir build
cd build
cmake ..
make 

3. Run

cd ..
# Fountain Demo
sh script/run_fountain_small.sh
# If you'd like to use your own data or change some vital parameters, configure the run_xxx.sh file

4. Dataset preparation

A toy dataset (fountain) can be found in test_data folder.

You can also download some datasets from SFM Datasets (COLMAP).

More datasets are availiable at Photogrammetry datasets.

You can also take some photo yourself and then calibrate them.

The calibration file should have the following format:

K.txt

f1 0 c1
0 f2 c2
0 0 1

distort.txt (not neccessary)

k1 k2 p1 p2

5. Configure shell file

The following contents is an example of the shell file in script folder. You can play with different parameter settings here.

#run_fountain_small.sh

#data path
image_folder=../test_data/images;
image_list=../test_data/image_list.txt;
calib_k_file=../test_data/k/K.txt;
calib_distort_file=none; # not neccessary, if not provided, just set it as none
output_file=../test_data/output/sfm_sparse_point_cloud_fountain.ply;

#processing parameters
feature_type=S;                 # S for SURF an O for ORB
feature_parameter=300;          # For SURF, this is the minHessian, for ORB, this is the max number of features [int]
repro_dis_ransac=1.0;           # The initial value of reprojection distance threshold for RANSAC (Initialization 5points and PnP)
find_init_frames=1;             # Find best frame pairs for initialization or not (1: find pair, 0: just use the first two frames for initialization)
ba_calib_change_tolerance=0;    # How much can the calib matrix change when doing BA
ba_frequency=4;                 # Do Bundle Adjustment for each X frame

#display parameters
launch_viewer=1;                # Open the real-time viewer (2: display all the processing details, 1: display neccessary details, 0: only dispaly the final result)
view_sphere=0;                  # render the point as sphere during visualization (sphere 1, point 0)

# Debug mode
#gdb --args \  
./bin/sfm ${image_folder} ${image_list} ${calib_k_file} ${calib_distort_file} ${output_file} \
${feature_type} ${feature_parameter} ${repro_dis_ransac} ${find_init_frames} ${ba_calib_change_tolerance} ${ba_frequency} \
${launch_viewer} ${view_sphere}  

TO DO List

• add sequential mode (visual slam)
• add multiple-camera mode (different intrinsic elements)
• add semantic label using deep learning
• add multi-view stereo dense reconstruction
• try more robust outlier filter
• improve the efficieny of bundle adjustment
• multithreading computing using CUDA
• write a GUI for the software using QT

About

Author: Yue Pan @ ETH Zurich D-BAUG