Structure from Motion

Structure from Motion (SFM) from scratch, using Numpy and OpenCV.

In this repository, we provide

1. Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

1.1. Prerequisites

To run tutorials, you need to have following libraries installed:

Numpy >= 1.13.1
OpenCV 3
Meshlab

Furthermore, to run SFM python script, you also need:

OpenCV Contrib

1.2. Data

Please download the standard data benchmarks from here

After downloading, you should have the following directory structure

data/
    fountain-P11/ 
        images/
            0001.jpg
            ...
            0011.jpg
        gt_dense_cameras/
            0000.jpg.camera
            ...
            0011.jpg.camera
    Herz-Jesus-P8/
        ...
    Castle-P19/
        ...
    ...

2. Demo/Quick Start

2.1. Tutorial Notebook

Tutorials are in tutorial/ directory. Furthermore, they’re divided in following sections

  1. Chapter 1: Prerequisites
  2. Chapter 2: Epipolar Geometry
  3. Chapter 3: 3D Scene Estimations
  4. Chapter 4: Putting It Together: Part I

2.2. SFM Script

  1. Go to script/ directory 
     cd script
  2. Run featmatch.py to generate feature keypoints, descriptors and matches 
     python featmatch.py

    All arguments are shown below:

     usage: featmatch.py [-h] [--data_dir DATA_DIR] [--ext EXT] [--out_dir OUT_DIR]
                     [--features FEATURES] [--print_every PRINT_EVERY]
                     [--save_results SAVE_RESULTS]

 optional arguments:
 -h, --help            show this help message and exit

 --data_dir  directory containing images (default: ../data/fountain-P11/images/)
 --ext   comma seperated string of allowed image extensions (default: jpg,png)
 --out_dir   root directory to store results in (default: ../data/fountain-P11)

 --features  [SIFT|SURF] Feature algorithm to use (default: SURF)
 --matcher   [BFMatcher|FlannBasedMatcher] Matching algorithm to use (default: BFMatcher)
 --cross_check   [True|False] Whether to cross check feature matching or not (default: True)

 --print_every   [1,+inf] print progress every print_every seconds, -1 to disable (default: 1)
 --save_results  [True|False] whether to save images with keypoints drawn on them (default: False)
  3. Run sfm.py to generate point cloud: 
     python sfm.py --data-dir <path-to-data-directory>

    All arguments are shown below

     usage: sfm.py [-h] [--data_dir DATA_DIR] [--dataset DATASET] [--ext EXT]
           [--out_dir OUT_DIR] [--features FEATURES] [--matcher MATCHER]
           [--cross_check CROSS_CHECK] [--calibration_mat CALIBRATION_MAT]
           [--fund_method FUND_METHOD] [--outlier_thres OUTLIER_THRES]
           [--fund_prob FUND_PROB] [--pnp_method PNP_METHOD]
           [--pnp_prob PNP_PROB] [--allow_duplicates ALLOW_DUPLICATES]
           [--color_policy COLOR_POLICY] [--plot_error PLOT_ERROR]
           [--verbose VERBOSE]

 optional arguments:
 -h, --help            show this help message and exit
    
 --data_dir  root directory containing input data (default: ../data/)
 --dataset   name of dataset (default: fountain-P11)
 --ext   comma seperated string of allowed image extensions (default: jpg,png)
 --out_dir   root directory to store results in (default: ../results/)

 --features  [SIFT|SURF] Feature algorithm to use (default: SURF)
 --matcher   [BFMatcher|FlannBasedMatcher] Matching algorithm to use (default: BFMatcher)
 --calibration_mat   [benchmark|lg_g3] Type of intrinsic camera to use (default: benchmark)
    
 --fund_method   [FM_RANSAC | FM_8POINT] Method to estimate fundamental matrix (default: FM_RANSAC)
 --outlier_thres     Threshold value of outlier to be used in fundamental matrix estimation (default: 0.9)
 --fund_prob     [0, 1] Confidence in fundamental matrix estimation required(default: 0.9)

 --pnp_method    [SOLVEPNP_DLS | SOLVEPNP_EPNP | ...] Method used for PnP estimation (default: SOLVEPNP_DLS)
 --pnp_prob  [0, 1] Confidence in PnP estimation required (default: 0.99)

3. Results

3.1. Fountain P11

3.2. Herz Jesus P8

3.3. Entry P10

Authors