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This Independent Study was designed to track and gather data from a aerial video. It stitches the images together using RANSAC and estimates the viewport of the camera over the images. It then projects the recorded data onto the stitched image and uses the GPS locations to trianglulate the target's location in UTM format using euclidean distance.

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hobbitsyfeet/UofLStudy

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UofLStudy

This is the github repository for Justin Petluk's Independent study at University of Lethbridge. (2019)

This program will use a modified Tracktor to create a semi-automatic processing tool to track individuals in the video. This program extends this tracking and maps the pixel coordinates to GPS locations when used in a remote-sensing manner. More details will be released in the future.

How to install:

Uses python3 (currently developed for python 3.6+ but should work with other versions of python3).
Tested on
Python 3.7.2
Python 3.6.7

After cloning the repository into a directory, decide whether you want to create a virtual environment (This is preferable). Instructions can be found here:

 https://docs.python.org/3/library/venv.html

Install requirments, this can be done by using pip3:

   pip3 install -r requirements.txt

Screenshot Screenshot Screenshot


Tracktor's information

Github: https://github.com/vivekhsridhar/tracktor

Cite: https://zenodo.org/record/1134016

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This Independent Study was designed to track and gather data from a aerial video. It stitches the images together using RANSAC and estimates the viewport of the camera over the images. It then projects the recorded data onto the stitched image and uses the GPS locations to trianglulate the target's location in UTM format using euclidean distance.

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