1. A method of detecting human objects with a video system, comprising: obtaining a first video image from a first video camera; obtaining a second video image from a second video camera; determining pixels of the first video image are first foreground pixels and a group of the first foreground pixels constitute a first foreground blob set of one or more first foreground blobs; for each of plural locations within the first video image, comparing a corresponding predetermined shape with the first foreground blob set to obtain a corresponding first probability of a human at the corresponding location, thereby obtaining plural first probabilities associated with the first video image corresponding to the plural locations within the first video image; determining pixels of the second video image are second foreground pixels and a group of the second foreground pixels constitute a second foreground blob set of one or more second foreground blobs; for each of plural locations within the second video image, comparing a corresponding predetermined shape with the second foreground blob set to obtain a corresponding second probability of a human at the corresponding location, thereby obtaining plural second probabilities associated with the second video image corresponding to the plural locations within the second video image; using the plural first probabilities associated with the first video image and the plural second probabilities associated with the second video image, determining X humans are represented by the first foreground blob set and the second foreground blob set, where X is a whole number; and providing at least one of a report, an alarm, and an event detection using the determination of the representation of X humans, wherein a size of the corresponding predetermined shapes for each of the plural locations within the first video image and each of the plural locations within the second video image is determined in response to calibration of the video system.