1. A method of detecting human objects in a video, comprising: determining pixels of a video image are foreground pixels, the group of foreground pixels constituting a foreground blob set of one or more foreground blobs; for each of N locations within the video image, where N is an integer, comparing a corresponding predetermined shape with the foreground blob set to obtain a corresponding probability of a human at the location, thereby obtaining N probabilities corresponding to the N locations; using the N probabilities, determining X humans are represented by the foreground blob set, where X is whole number; using the determination of the representation of X humans, determining a crowd density within a first area of the real world; comparing the crowd density to a threshold; and providing at least one of a report, an alarm, and an event detection when the crowd density exceeds the threshold, wherein a size of the corresponding predetermined shape for each of the N locations is determined in response to calibration of a video system, wherein the video system is used to obtain the video image.