Project - 2D Feature Tracking

Feature tracking part and various detector / descriptor combinations were tested to see which ones perform best. This project consists of four parts:

• First ,loading images, setting up data structures and putting everything into a ring buffer to optimize memory load.
• Second ,integrating several keypoint detectors such as HARRIS, FAST, BRISK and SIFT and comparing them with regard to number of keypoints and speed.
• Third ,descriptor extraction and matching using brute force and also the FLANN approach.
• Finally , Testing the various algorithms in different combinations and compare them with regard to some performance measures.

Dependencies for Running Locally

• cmake >= 2.8
  • All OSes: click here for installation instructions
• 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
• OpenCV >= 4.1
  • This must be compiled from source using the -D OPENCV_ENABLE_NONFREE=ON cmake flag for testing the SIFT and SURF detectors.
  • The OpenCV 4.1.0 source code can be found here
• 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 MinGW

Basic Build Instructions

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.