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
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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
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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.)
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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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