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)
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to 720 х 576 (CIF4) pixels; lager images are scaled down to CIF4.- 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
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.- No camera jitter is allowed
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.: | - Best recognition results are achieved under moderate illumination. If the scene is under- or over-illuminated, the recognition accuracy may drop down
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.- Sharp changes in illumination may lead to improper operation of analytics
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. viewing : | - Vertically downward position of the camera is the best for the purpose.
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- The closer to vertical, the more accurate
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counting.- the estimation
- Camera FOV dimensions:
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min. 3 x 3m (6 x 6 - minimum 3x3 m (6x6 humans), optimal
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4 x 4m (8 x 8x max. 8 x 8m (16 x 16 - maximum 8x8 m (16x16 humans)
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. must - should be primarily static and should not undergo sudden changes
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.- Reflective surfaces and harsh shadows from moving objects can affect the quality of analytics
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.Leafage, TV screens or any periodic object movement in the background may cause analytics glitches.- 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 |
within the scene: must and sharp - , with no visible compression artifacts
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.- Dimensions of a human in scene: bounding rectangle has to occupy from 0.
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25 10 percent .
