vision_kit

A computer vision kit for algorithm verification. Far from stable.

Required

• OpenCV 3.1.0
• Eigen3

Modules

1. Base

Some universal functions and some definitions.

2. Optical Flow

Algorithms for Optical flow

• Pyramidal Lucas-Kanada Algorithm

3. Epipolar Geometry

Function about Fundamental Matrix. There are two methods to find the fundamental matrix

• 8-Points Algorithm. Normalized 8-point algorithm

• RANSAC. Self-adaptive sample by the inliers number of current best model. Solve the fundamental matrix by 8-Points algorithm.

4. Image patch Alignment

Use Inverse Compositional and Efficient Second-order Minimization algorithm to align image patch in reference image to patch in current image. The model contains:

• pixel 2D drift (IV) $$I_c(\mathbf x + \mathbf u) = I_r(\mathbf x)$$

• pixel 2D drift with bias(illumination or exposure differences) (IV, ESM) $$I_c(\mathbf x + \mathbf u) = I_r(\mathbf x) + \beta$$

Usage

First of all, build the code.

mkdir build && cd build
cmake ..
make -j

Then run the demos

# Base
./test_base ../data/desk1.png ../data/desk2.png

# Optical Flow
./test_opticalflow ../data/floor1.png ../data/floor2.png

# Epipolar Geometry
./test_fundamental ../data/desk1.png ../data/desk2.png

# Image Alignment
./test_align2D ../data/floor1.png ../data/floor2.png
./test_align1D ../data/floor1.png ../data/floor2.png