Predicting Pedestrian Counts in Crowded Scenes With Rich and High Dimensional Fe

Estimating the number of pedestrians in surveillanceimages and videos has important applications in intelligenttransportation systems. This problem is particularly challengingwhen the scenes are densely crowded, in which the techniques oftracking a single pedestria