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1. Go to the Additional settings tab on the settings panel of the Neurotracker object.
   
   

2. In the Recognition threshold [0, 100] field, specify the neurocounter sensitivity—an integer value in the range from 0 to 100.

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   title Note
   The neurotracker sensitivity is determined experimentally. The lower the sensitivity, the higher the probability of false alarms. The higher the sensitivity, the lower the probability of false alarms, however, some useful tracks can be skipped (see Examples of configuring neural tracker for solving typical tasks).

3. In the Frames processed per second [0.016, 100] field, specify the number of frames processed per second by the neural network in the range from 0.016 to 100. For all other frames interpolation will be performed—finding intermediate values by the available discrete set of its known values. The greater the value of the parameter, the more accurate the detection tool operation, but the higher the load on the processor.
   

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   title Note
   The recommended value is at least 6 FPS. For fast moving objects (running person, vehicle)—at least 12 FPS (see Examples of configuring neural tracker for solving typical tasks).

4. In the Minimum number of triggering [2, 100] field, specify the minimum number of neurotracker triggers required to display the object track. The higher the value of this parameter, the longer it takes from the object detection moment to the display of its track. A low value of this parameter can lead to false positives. The default value is 6. The value range is 2-100. The entered value that is greater than the maximum value or less than the minimum value from the specified range, is automatically adjusted to the maximum or minimum value, respectively.

5. In the Track hold time (s) field, specify the time in seconds after which the object track is considered lost in the range from 0.3 to 1000. This parameter is useful in situations where one object in the frame temporarily overlaps another. For example, when a large vehicle completely overlaps a small one.

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   title Note
   If an object (track) is close to the frame boundary, then approximately half the time specified in the Track hold time (s) field must elapse from the moment the object disappears from the frame until its track is deleted.

6. Set the Scanning mode checkbox to detect small objects. If you enable this mode, the load on the system increases. So we recommend specifying a small number of frames processed per second in the Frames processed per second [0.016, 100] field. By default, the checkbox is clear. For more information on the scanning mode, see Configuring the Scanning mode.
7. If necessary, specify the class of the detected object in the Target classes field. If you want to display tracks of several classes, specify them separated by a comma with a space. For example, 1, 10.
   The numerical values of classes for the embedded neural networks: 1—Human/Human (top view), 10—Vehicle.
   

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   title Note
   If you leave the field blank, the tracks of all available classes from the neural network will be displayed (Object type, Neural network file). If you specify a class/classes from the neural network, the tracks of the specified class/classes will be displayed (Object type, Neural network file). If you specify a class/classes from the neural network and a class/classes missing from the neural network, the tracks of a class/classes from the neural network will be displayed (Object type, Neural network file). If you specify a class/classes missing from the neural network, the tracks of all available classes from the neural network will be displayed (Object type, Neural network file).

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