Camera requirements for Queue detection

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

Camera	Resolution: 720 х 576 (CIF4), 360 х 288 (CIF1) is also allowed to use. Increasing the resolution above CIF4 does not improve the operating quality of the recognition algorithm. 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 camera angle	Vertically downward position of the camera is the best for the purpose. The closer to vertical, the more accurate the estimation. Camera FOV dimensions: minimum 3x3 m (6x6 humans), optimal 4x4 m (8x8 humans), maximum 8x8 m (16x16 humans). The background should be primarily static and should not undergo sudden changes. Reflective surfaces and harsh shadows from moving objects can affect the quality of analytics. Analytics may not work correctly if there are periodic movements of the background objects in the camera FOV (leafage, TV screens, etc.).
Images of objects	Image quality: the image should be clear, with no visible compression artifacts. Dimensions of a human in scene: bounding rectangle has to occupy from 0,25% to 10% of the frame area.

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