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The following table contains the requirements for cameras used by the queue detection tool:

Camera

  • Resolution: 360 х 288 (CIF1) to 720 х 576 (CIF4) pixels; lager images are scaled down to CIF4.
  • Frames per second: 6 or more
  • Color: color or greyscale.
  • No camera jitter is allowed.

Illumination:

  • Best recognition results are achieved under moderate illumination. If the scene is under- or over-illuminated, the recognition accuracy may drop down.
  • Sharp changes in illumination may lead to improper operation of analytics.

Scene and viewing angle:

  • Vertically downward position is the best for the purpose.  The closer to vertical, the more accurate counting.
  • Camera FOV dimensions: min. 3 x 3m (6 x 6 humans), optimal 4 x 4m (8 x 8x humans), max. 8 x 8m (16 x 16 humans).
  • The background must be primarily static and not undergo sudden changes.
  • Reflective surfaces and harsh shadows from moving objects can affect the quality of analytics.
  • Leafage, TV screens or any periodic object movement in the background may cause analytics glitches.

Images of objects within the scene:

  • Image quality: the image must be clear and sharp with no visible compression artifacts.
  • Dimensions of a human in scene: bounding rectangle has to occupy 0.25 to 10 percent of the frame area.
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