/monocular_invehicle_visual_odometry

This code uses the images of an in-vehicle dashcam to estimate the position of the car in a series of consecutive images. It uses the FAST keypoint detection algorithm combined with the opticalFlowLK keypoint matching algorithm.

Primary LanguagePython

Check the documentation.pdf to see what this is about!

make sure you have packages:

numpy
opencv (3)!
matplotlib
scipy
mpl_toolkits
math
os


then just go and run: python get_positions.py
f.py contains all the helper functions doing the dirty work.

I work on an Ubuntu 15.10


The script:

Reads in the images
Findes the keypoints
matches the keypoints
estimates the Rotation and Translation
Visualises the result

creates an ./output/ folder with the results


OUTPUT:
./kps/          - the keypoints found in the images
./matches/      - the visualisation of the flow of the keypoints between consecutive images
./result/       - the 2D mapping and the 3D- coordinate plot
./logfile.txt   - the indivdicual rotation and translation of each step and information if the sanity check was negative.