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x32: (x32)\FRS
x64: (x64)\FRS

The key defines on determines how many CPU cores the face recognition module will operate (firserver.run process). All cores are in use by default.

х32: (х32)\FRS
x64: (х64)\FRS

The key determines how many CPU cores will be used for face search:

0—the number of cores specified in the CpuCoreCount key. The cores are used sequentially. Each core is assigned its own recognition instance.

1—only 1 fixed core is used

2—only 2 fixed cores are used

and so on

The key sets the timeout upon which Face Server ‘loses’ the face if there is no new data about it.

Sets the parameters of generating and attaching face biometrics in the detection tool:

1 – Face detection tools generate and attach face biometrics to the photo. 

0 – Face detection tools do not generate face biometrics - the face is only captured.

Note. Face recognition Server that performs search in the user database checks up whether it has attached biometrics when it gets a face photo. If yes, then biometrics are not further generated for search in the database - data attached to the photo is in use. If no, then recognition Server generates biometrics itself using the photo. 

Specifies what data will be stored in the database when using the Face recognition Server:

1 - all captured faces.
0 - only the faces about which there are recognition results.

The key is in use in order to avoid the database overflow.

Note. Starting from version 7.0, to minimize the amount of information stored in the database, it is recommended to use the UseFaceDB key.

The key is used to configure the face detection tool – it sets time on the expiry of which the face is considered lost.

For instance, if timeUntilLost = 1 and a man covers his face with the hands in front of the camera and then shows it again, then the face detection tool does not capture it as it considers that the face was lost for the time it was covered.

The key sets the storage mode for metadata, images and vectors of captured and reference faces.

0 - metadata, images and vectors are stored only in the database.

1 - metadata, images and vectors are stored in the database, and images and vectors are also stored in a folder on disk. The path to the folder is set by the FaceDB parameter (you can specify both local and network folders).

2 - metadata is stored in the database, and images and vectors are stored only in a folder on disk. The path to the folder is set by the FaceDB parameter (you can specify both local and network folders).

Note 1. Metadata is stored in the database in the Hits table, regardless of the value of the UseFaceDB key.

Note 2. Images of reference faces are stored in the <Intellect software installation directory>\Bmp\Person folder, regardless of the UseFaceDB key value.

Note 3. Starting from Face Intellect version 7.1.0.1161 only the UseFaceDB = 2 mode is supported, which is set automatically when Face Intellect starts if a mode other than this is detected.

The key is used if the the UseFaceDB parameter value is 1 or 2 (see above). The key sets the size of free disk space in megabytes. Once the specified size is reached, the old images, vectors and metadata of captured faces will be deleted. The cleanup is performed on a loop in portions equivalent to 1000 megabytes.

CpuCoreCountAddPerson

The key defines the number of CPU cores where the vectors of persons are generated when adding a reference face to the database.

0 - vectors are generated on the number of cores specified in the CpuCoreCount key. The cores are used successively. Recognition sample is bound to each core.

1 - only 1 fixed core (different from those specified in CpuCoreCount) is in use when adding a reference face to the database.

2 - only 2 fixed cores (different from those specified in CpuCoreCount) are in use when adding a reference face to the database.

Face.HardwareCPU

The key defines the order of binding streams to CPU cores when generating vectors of persons.

no value or 0 - streams are bound randomly to CPU cores.
1 - streams are bound successively to CPU cores depending on their total number.
2 - streams are bound to first cores of each CPU.

Mechanism of displaying faces. When a new mechanism of displaying is enabled, the photo in the list of captured faces is not duplicated - it is updated in the same cell while the tracker "sees" it.  

0 - new mechanism of displaying faces. 

1 - old mechanism of displaying faces. 

The key enables saving the last recognized face and all its necessary data to a file. This image file can be sent directly to the recognition server via the iidk_client utility.

0 - General operation mode.

1 - When the face is captured, the captureFrame (cam_N) .log file is created (where N is the camera number that captured the face) in the <Intellect Installer directory>\Modules64\Firserver folder\. This file will contain the last recognized face and all its necessary data. This image file can be sent directly to the recognition server via the iidk_client utility.

Note. The file is overwritten every time a new face is captured.

The key restricts resolution (width) of the photo when adding it to the faces database.

Set greater value to the key if the following message appears when adding a face to DB: "Adding error. The face was not added. Insufficient image quality to add".

The key restricts resolution (height) of the photo when adding it to the faces database.

The key allows to select the face detection mode:

1 − V1,

2 − V2,

3 − V3.

The key enables selecting the face recognition and search algorithm.

0 – less resource intensive algorithm is in use

1 – more resource intensive algorithm is in use 

Important! Biometric vectors received using this algorithm cannot be used with alternative one. For proper operation of Face Intellect after changing this parameter biometric vectors are to be converted as described in  Switching between the face recognition modules section. 

An alternative algorithm for filtering false triggerings of the tracker. This key is in use if Tevian.GlobalTrackingDetectionFilter=0 and Tevian.DetectionFilterValue > 0 (see the corresponding parameters below). 

0 - ALG1

1 - ALG2

Note. It is not recommended to change this parameter without consulting with AxxonSoft technical support.

Configuring alternative algorithm filtering. It is in use if the value of Tevian.GlobalTrackingDetectionFilter is more than 0 (see the corresponding parameter below).

Note. It is not recommended to change this parameter without consulting with AxxonSoft technical support.

Activates an additional check to filter out false triggerings of the tracker. If faces in masks are not recognized, it is recommended to disable this check, however, this can cause false triggerings of the tracker.

0 - disabled

1 - enabled.

Note. It is not recommended to change this parameter without first consulting with AxxonSoft technical support.

Face detection operation mode (identification). The recommended parameter value is 0.

0 - ALG1

1 - ALG2

Note. It is not recommended to change this parameter without consulting with AxxonSoft technical support.

This parameter affects the detector captioning capacity. If there is a great value, the tracks can rend.

Note. It is not recommended to change this parameter without consulting Tevian.

Face detector confidence threshold (do not confuse with face quality).

Note. It is not recommended to change this parameter without consulting with AxxonSoft technical support.

The key enables selecting the algorithm for recognition and face search.

0 - ALG1 less resource-intensive algorithm is in use.

1 - ALG2 identification of the higher quality, but more resource-intensive.

2 - PRECISE the highest quality of recognition, but the most resource-intensive. This algorithm is recommended if significantly less time is spent on face recognition than on detection (if there are few people in the frame).

Important! Since the biometric vectors received by one algorithm cannot be used by another, then after changing the algorithm, the biometric vectors are automatically recreated. The biometric vectors can also be recreated manually (see Switching between the face recognition modules and SDK versions).

Specifies the number of seconds to accumulate the best frames of a track for recognition. The increase in time makes it possible to average out the recognized face characteristics, but it can result in the poorer accuracy of the face characteristics recognition.

Note. For example, if the 1 second value is set, the average error in determining the age will be 2-3 years, and if the 5 seconds value is set, it will be 3-4 years.

Time since the last recognition after which the track is considered ended.

Note. It is not recommended to change this parameter without consulting with AxxonSoft technical support.

Sets the sensitivity of the closed eyes recognition. The higher the value, the less sensitive the closed eyes detector.

Specifies which frames will be recognized.

0 − only the best frame defined by Tevian will be recognized.

1 − all frames will be recognized, as a result the quality of recognition increases, but the CPU load increases, too

Activates the Eyes closed event generation when closed eyes are detected.

IsProcessObject

Enables the launch of each Face Recognition Server in a separate process.

0 - all Face Recognition Servers launch in the same process.

1 - each Face Recognition Server is launched in a separate process.

Enables ignoring threads affinity to kernels inside firserver.run.

0 - ignoring threads affinity to kernels is disabled.

1 - ignoring threads affinity to kernels is enabled. The key is used in conjunction with the IsProcessObject=0 key.

ResizeWidth

Sets the video resolution that is sent from cameras to all Face Detection modules.

Actually, the width of the video image is set, and the height is adjusted automatically based on the aspect ratio of the original video. For example, if the original video has a resolution of 2560x1920, then if you set the value to 960, then the video will be converted to a resolution of 960x720.

If the value is set to 0, then the video image will be received in its original resolution.

SaveThermalJson

Enables saving all json and images received from the thermal camera during face recognition to the folder. The data from the camera will be saved at the following address:

• In case of face recognition: <Intellect installation directory>\Modules64\Firserver\ThermalImages\{Face detection tool ID}
• In case the face is not recognized: <Intellect installation directory>\Modules64\Firserver\ThermalImages\{Face detection tool ID}\NoFaces

0 - data from the thermal camera is not saved to the folders

1 - data from the thermal camera is saved to the folders

ForceProcessWholeImage

The key is used in case the Combined work with thermal camera and Get photo from thermal camera checkboxes are set on the settings panel of the Face Recognition Server object.

Enables the face search throughout the entire frame if a face was not previously recognized due to incorrect coordinates of the face frame received from the thermal camera.

Details on this mode:

• The number of recognitions and the system load will increase.
• The negative face images will be displayed in the Face recognition and search interface module.
• The same temperature will be indicated for all recognized faces in the frame.

0 - Unrecognized faces are ignored.

1 - Enables the face search throughout the entire frame if a face was not previously recognized.

Update.CpuCoreCount

Sets the number of threads on which the biometric vectors are re-generated when switching between different face recognition modules or SDK versions.

x32: (х32)\DetectorExt\BARCODE_DETECTOR

x64: (х64)\DetectorExt\BARCODE_DETECTOR

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Barcode Detection: External Detector - BARCODE_DETECTOR.1

x32: (х32)\DetectorExt\BASE_POSE_DETECTOR

x64: (х64)\DetectorExt\BASE_POSE_DETECTOR

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Pose Detection: External Detector - BASE_POSE_DETECTOR.1

x32: (х32)\DetectorExt\CONVEYOR_BELT_DETECTOR

x64: (х64)\DetectorExt\CONVEYOR_BELT_DETECTOR

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Conveyor Belt Detection: External Detector - CONVEYOR_BELT_DETECTOR.1

x32: (х32)\DetectorExt\CROWD_COUNTER

x64: (х64)\DetectorExt\CROWD_COUNTER

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Detection of moving against crowd flow: External Detector - CROWD_COUNTER.1

x32: (х32)\DetectorExt\CROWD_COUNTER_TVN

x64: (х64)\DetectorExt\CROWD_COUNTER_TVN

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Crowd detection (TVN): External Detector - CROWD_COUNTER_TVN.1

x32: (х32)\DetectorExt\EQUIPMENT_DETECTOR

x64: (х64)\DetectorExt\EQUIPMENT_DETECTOR

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Equipment detection (PPE): External Detector - EQUIPMENT_DETECTOR.1

x32: (х32)\DetectorExt\FIRE_DETECTOR

x64: (х64)\DetectorExt\FIRE_DETECTOR

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Fire detection: External Detector - FIRE_DETECTOR.1

x32: (х32)\DetectorExt\FLUID_DETECTOR

x64: (х64)\DetectorExt\FLUID_DETECTOR

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Fluid level detection: External Detector - FLUID_DETECTOR.1

x32: (х32)\DetectorExt\GLOW_DETECTOR

x64: (х64)\DetectorExt\GLOW_DETECTOR

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Detection of light indication control: External Detector - GLOW_DETECTOR.1

x32: (х32)\DetectorExt\HEAT_ZONE_DETECTOR

x64: (х64)\DetectorExt\HEAT_ZONE_DETECTOR

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Heat map detection: External Detector - HEAT_ZONE_DETECTOR.1

x32: (x32)\DetectorExt\HeatZoneDetector

x64: (x64)\DetectorExt\HeatZoneDetector

Sets the data collection frequency (sec) for heat zone detection tool.

x32: (x32)\DetectorExt\HeatZoneDetector

x64: (x64)\DetectorExt\HeatZoneDetector

Sets the data update frequency (sec) from heat zone detection tool in the Debug window in seconds.

x32: (х32)\DetectorExt\NEURO_COUNTER

x64: (х64)\DetectorExt\NEURO_COUNTER

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Neurocounter: External Detector - NEURO_COUNTER.1

x32: (х32)\DetectorExt\NEURO_TRACKER

x64: (х64)\DetectorExt\NEURO_TRACKER

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Neurotracker: External Detector - NEURO_TRACKER.1

x32: (х32)\DetectorExt\OCCUPANCY_COUNTER

x64: (х64)\DetectorExt\OCCUPANCY_COUNTER

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Queue length detection: External Detector - OCCUPANCY_COUNTER.1

x32: (х32)\DetectorExt\PEOPLE_COUNTER

x64: (х64)\DetectorExt\PEOPLE_COUNTER

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the People counter detection: External Detector - PEOPLE_COUNTER.1

x32: (х32)\DetectorExt\SMOKE_DETECTOR

x64: (х64)\DetectorExt\SMOKE_DETECTOR

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Smoke detection: External Detector - SMOKE_DETECTOR.1

x32: (х32)\DetectorExt\STOPPED_CAR_DETECTOR

x64: (х64)\DetectorExt\STOPPED_CAR_DETECTOR

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Stopped vehicle detection: External Detector - STOPPED_CAR_DETECTOR.1

x32: (х32)\DetectorExt\SWEETHEARTING_DETECTOR

x64: (х64)\DetectorExt\SWEETHEARTING_DETECTOR

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Sweethearting at checkout detection: External Detector - SWEETHEARTING_DETECTOR.1

x32: (х32)\DetectorExt\TRAFFIC_LIGHTS

x64: (х64)\DetectorExt\TRAFFIC_LIGHTS

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Traffic lights detection: External Detector - TRAFFIC_LIGHTS.1

x32: (х32)\DetectorExt\TRAIN_DETECTOR

x64: (х64)\DetectorExt\TRAIN_DETECTOR

Activates the start of the detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. Example of a separate process for the Train detection: External Detector - TRAIN_DETECTOR.1

x32: (х32)\DetectorExt\VIDEO_INTELLECT_INTERNAL_DETECTOR

x64: (х64)\DetectorExt\VIDEO_INTELLECT_INTERNAL_DETECTOR

Activates the start of the VideoIntellect detection tool in a separate process:

0—detection tool is started in one common External Detector process, all messages and reactions from this detection tool go to the common process

1—detection tool is started in a separate External Detector - Detector type.Detector Id process, all messages and reactions from this detection tool go to the separate process. If there are sub-tools, their messages go to the parent process. 

Examples of separate processes for the VideoIntellect detection tools:

VideoIntellect embedded detector: External Detector - VIDEO_INTELLECT_INTERNAL_DETECTOR.1
VideoIntellect detection of movement in prohibited area: External Detector - VI_FORBIDDEN_DETECTOR.1
VideoIntellect detection of prohibited direction: External Detector - VI_DIRECTION_DETECTOR.1
VideoIntellect detection of crowd: External Detector - VI_CROWD_DETECTOR.1
VideoIntellect abandoned objects detection: External Detector - VI_ABANDONED_DETECTOR.1
VideoIntellect detection of camera state: External Detector - VI_FAULTER_DETECTOR.1
VideoIntellect abandoned objects street detection: External Detector - VI_ABANDONED_STREET_DETECTOR.1

Hides the VideoIntellect detector objects from the Intellect objects tree

0—the VideoIntellect detector objects are hidden

><0—the VideoIntellect detector objects are displayed

The key sets the time in seconds which defines the time the object stays in the zone, after which the NeuroTracker VMDA detection tools with the Staying in the area for more than 10 sec detector type, created under the Neurotracker object, are triggered. If this key is not specified, then it is considered equal to the LongInZoneTimeout key value (see Intellect Enterprise base version)