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1. Standard. The following objects can be classified: a human, a vehicle, an other object (see Cross line detector configuration and Motion in the Area detector configuration).
2. Advanced. The following objects can be classified: a human, a group of humans, a vehicle, noise, an object carried into the area, an object carried out of the area, an other object (see the CAM_VMDA_DETECTOR section of the Programming Guide).
3. Neural filter — a neural network-based classification. Any objects can be classified to a high precision. The neural network is trained individually for each use case.

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In most cases, one neural networks model is enough for the standard objects classification (e.g. a human / a vehicle). However, for the non-standard tasks with multiple object classes, more than one model may be required:

• if there are different classification tasks: for example, for some cameras the human/vehicle object classification is required, and for other cameras, the vehicle type (passenger car/freight vehicle) classification is required;
• if different conditions apply to different cameras, and the tracker will work better if each neural network is trained to work under different conditions: for example, the task is to protect the factory perimeter (only the human and vehicle detection is required) and the factory workshop (only the people in special work clothes detection is required).

Prior to configuring the neural filter, it is necessary to contact the AxxonSoft technical support and request the model files of the trained neural networks. Technical support specialists will request the data necessary for the preparation of models, and then provide you with the *.ann files for each model of the neural network. These files should be distributed among all the servers where the neural filter will be used.

The neural filter is configured in the following way:

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