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.
- 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 |
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).
- The background
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must - should be primarily static and should not undergo sudden changes.
- 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.
- Dimensions of a human in scene: bounding rectangle has to occupy from 0
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.25 to 10 percent - ,25% to 10% of the frame area.
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