/Graduation-Project

A simple project to detect events in football matches using opencv and a simple NN model.

Primary LanguagePython

#GP

title : online detection of key events in football matches

summary

  • we removed crowd and detected playground using image processing techinques
  • we detected the ball using its geometric features
  • we detected the players using opencv's HOG classifier (terrible accuracy)
  • we tracked the detected players using opencv's tracker and the "MIL" algorithm (great accuracy)
  • we extracted key points using SURF and cluster the desciptors using SOM
  • the vectors in the SOM form a kind of a visual language that allows us to make a bag of features for each image
  • the used SOM had a 50x50 structre so we had 2500 "words"
  • we collected a data set of 52000 images and labeled them
  • we trained five backpropagation NN each to be abel to tell whether a certain event has occured or not untill each network had an accuracy of at least 80%
  • we trained another network which takes the output of the previous 5 networks as input and outputs the correct label until its accuracy on testing data was 93%
  • experimentation using PCA showed that we can achieve the same accuracy if we project each image representation (the 2500 vector from SOM) on a 140+ dimentional space
guidlines for GP team
  • don't push unless the whole project works correctly on your machine
  • don't add external library files in the project .
  • if you use an extenal library modify this document and add its name/link to the dependecies section along with a link/tutorial on how to install and use it
  • media resources(images/videos) should be added in the drive folder (link below) with BOTH
    • a note in the commit message
    • and a comment in the code where it's used
  • try to be as organised as possible
  • write clear and clean code with comments
  • if you choose to use an external library ,compare alternatives and choose the best in terms of quality and community support

note

dependencies/links: