This mini-project is an exhaustive comparison between different keypoint detectors and descriptors present in C++ OpenCV library. The matching is performed on a suquence from KITTI DATASET. Below are the results and observation from my implementation.

The starter code is taken from Udacity Sensor Fusion github.

HARRIS: Scattered points. Relatively less than others. SHI-TOMASI: Points more present on the windshield area and few on the edge of the bumper. FAST: Windshield area more scattered than Shi Tomasi but overall similar. More points are outside the car. BRISK: Distribution is similar to Shi Tomasi and Fast. ORB: More points on the right side of the windshield. No points on the bumper. AKAZE: Points are outside the car but it has detected points on the car as well. SIFT: Very similar to SHI-TOMASI more points on the edge of the car.

1. FAST Detector + BRIEF Desc extractor
2. FAST Detector + BRISK Desc extractor
3. ORB Detector + BRIEF Desc extractor

1. cmake >= 2.8

• All OSes: click here for installation instructions

2. make >= 4.1 (Linux, Mac), 3.81 (Windows)

• Linux: make is installed by default on most Linux distros
• Mac: install Xcode command line tools to get make
• Windows: Click here for installation instructions

3. OpenCV >= 4.1

• All OSes: refer to the official instructions
• This must be compiled from source using the -D OPENCV_ENABLE_NONFREE=ON cmake flag for testing the SIFT and SURF detectors. If using homebrew: $> brew install --build-from-source opencv will install required dependencies and compile opencv with the opencv_contrib module by default (no need to set -DOPENCV_ENABLE_NONFREE=ON manually).
• The OpenCV 4.1.0 source code can be found here

4. gcc/g++ >= 5.4

• Linux: gcc / g++ is installed by default on most Linux distros
• Mac: same deal as make - install Xcode command line tools
• Windows: recommend using either MinGW-w64 or Microsoft's VCPKG, a C++ package manager. VCPKG maintains its own binary distributions of OpenCV and many other packages. To see what packages are available, type vcpkg search at the command prompt. For example, once you've VCPKG installed, you can install OpenCV 4.1 with the command:

c:\vcpkg> vcpkg install opencv4[nonfree,contrib]:x64-windows

Then, add C:\vcpkg\installed\x64-windows\bin and C:\vcpkg\installed\x64-windows\debug\bin to your user's PATH variable. Also, set the CMake Toolchain File to c:\vcpkg\scripts\buildsystems\vcpkg.cmake.

1. Clone this repo.
2. Make a build directory in the top level directory: mkdir build && cd build
3. Compile: cmake .. && make
4. Run it: ./2D_feature_tracking.