In my previous work, I used pre-trained Yolov3 model to detect and used SORT (simple online and realtime tracking) to track football players from video. Then I used OpenCV’s getPerspectiveTransform function to convert the video to bird’s-eye view.
One of the problems of this work is that the model cannot tell the difference between teams. It will be good if the program is able to identify players’ team instead of just detecting ‘person’. To further improve this, I wish to include a function which tells the difference based on the colors of players’ jersey.
Two approaches I can think of now to this problem.
I decided to try approach 2 using OpenCV.
The stationary football video is downloaded from here.
“T. D’Orazio, M.Leo, N. Mosca, P.Spagnolo, P.L.Mazzeo A Semi-Automatic System for Ground Truth Generation of Soccer Video Sequences, 6th IEEE International Conference on Advanced Video and Signal Surveillance, Genoa, Italy September 2–4 2009”
#deep-learning #artificial-intelligence #sports #data-science #machine-learning #deep learning
Football players tracking — identifying players’ team based on their jersey colors using OpenCV Detect, track, determine players’ team and convert it to bird’s-eye view using Yolov3, SORT.