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People Tracking  This example shows how to detect and track
people in a video sequence with a stationary background using
the following process: 1) Use the first few frames of the video
to estimate the background image. 2) Separate the pixels that
represent the people from the pixels that represent the
background. 3) Group pixels that represent individual people
together and calculate the appropriate bounding box for each
person. 4) Match the people in the current frame with those in
the previous frame by comparing the bounding boxes between
frames.  Example Model  The following figure shows the People
Tracking example model:  Segmentation Subsystem  In the
Segmentation subsystem, the Autothreshold block uses the
difference in pixel values between the normalized input image
and the background image to determine which pixels correspond to
the moving objects in the scene.  Detection Subsystem  In the
Detection subsystem, the Close block merges object