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.
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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 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.
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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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