Our goal is to combine the saliency detector with mean-shift tracking to automatically track all the players on a soccer field. The proto-objects identified by the saliency detector will serve as input to the mean-shift tracker. Specifically, we will focus on a video sequence from the Alfheim dataset, which can be freely obtained from http://home.ifi.uio.no/paalh/dataset/alfheim/.
The reason for combining the two algorithms (saliency map and mean-shift tracking), is to maintain correspondence information between objects in different frames as well as to remove some false positives and improve the accuracy of detected objects.
The hard work is done by the previously introduced MultiObjectTracker ...
