Implementation of Machine learning algorithms to detect a goal in basketball games.

• Naive classifier
• Logistic regression
• SVM
• Multiple layer perceptron
• CNN

Our dataset is four basketball videos containing about 400, 000 frames.

Basically, we label each frame as goal(1) or not goal(0). A frame is labeled as goal if from the time when the bottom of the basketball touches the loop to the time when the top of the ball is leaving the nets.

Label, cut, and randomly shuffle the frames. See details in preprocess.

For naive classifier, LR, SVM, we use HoG to extract features.

A ROC curve is used for evaluation.