README.txt

- Application: Motion Estimation
Motion is estimated by drawing the optical flow within two videos of moving cars 
(https://www.youtube.com/watch?v=Y1jTEyb3wiI)(https://www.bogotobogo.com/python/OpenCV_Python/images/mean_shift_tracking/slow_traffic_small.mp4) 

using three different approaches:
1. FAST keypoint detector algorithm with the pyramid implementation of the Lucas-Kanade (KLT) 
algorithm (Optical flow. OpenCV. (n.d.). Retrieved November 7, 2021, from https://docs.opencv.org/3.4.15/d4/dee/tutorial_optical_flow.html).
2. FAST keypoint detector with the FREAK keypoint descriptor (descriptor matching).
3. FAST keypoint detector with the LUCID keypoint descriptor (descriptor matching).

- Steps to run KLTOpticalFlow_Gray:

1. Open the Code:Blocks IDE
2. Go to File --> Open KLTOpticalFlow_Gray.cbp file.
Note: "KLT_Gray_Arrow.cbp" is the same code but it outputs the optical flow using arrows.
Note: "slow_traffic_small.mp4" was also used to compare results. To use it, change the VideoCapture object name in the code.
3. Press the "build and run" button.
4. A console screen and a windows will appear showing the optical flow obtained from the pyramid implementation of the KLT algorithm.
5. Exit the program by pressing ESC.

- Steps to run FAST_FREAK:

1. Open the Code:Blocks IDE
2. Go to File --> Open FAST_FREAK.cbp file.
Note: "slow_traffic_small.mp4" was also used to compare results. To use it, change the VideoCapture object name in the code.
3. Press the "build and run" button.
4. A console screen and a windows will appear showing the optical flow obtained from using FAST + FREAK algorithms.
5. Exit the program by pressing ESC.

- Steps to run FAST_LUCID:

1. Open the Code:Blocks IDE
2. Go to File --> Open FAST_LUCID.cbp file.
Note: "slow_traffic_small.mp4" was also used to compare results. To use it, change the VideoCapture object name in the code.
3. Press the "build and run" button.
4. A console screen and a windows will appear showing the optical flow obtained from using FAST + LUCID algorithms.
5. Exit the program by pressing ESC.