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Face Recognition

The Flussonic Watcher system can recognize human faces. This feature is used to solve various problems:

  • Arranging access without card swiping in an access control system
  • Employee time&attendance tracking
  • Accounting for incoming/outgoing traffic of people
  • Automatic identification or verification of persons when performing various actions

Before you proceed to settings:

  1. Update Flussonic Watcher to the latest version.
  2. Prepare hardware and software for the Flussonic server that will carry out face recognition.
  3. Check the video image parameters for compliance with the recommendations (see below).

Content:

A general requirement for a video image for face recognition is the ability to recognize the face with human eyes. In other words, if you do not perceive the face in the video, then Watcher will not be able to recognize it either.

Stable face recognition is guaranteed with the following video image characteristics:

Requirements for camera installation

  1. No more than +/- 20° vertical and horizontal deviation from a right-angle (90°) view into the camera, i.e. camera should be installed at a height of no more than 2 m.
  2. The shutter speed is not more than 1/100 (for example, the face is blurred when moving at a shutter speed of 1/25).
  3. Frame resolution at least 1280x720.
  4. The face height should be at least 1/6 of the frame height at the minimum allowed resolution of 1280x720. For higher resolutions, the face size may be smaller in proportion to the increase in frame size. In other words, resolution should be 500 pixels per 1 m, i.e. the distance between the pupils must be at least 50-60 pixels.
  5. Lighting not less than 150 lux with face evenly illuminated.
Example proper camera position
Example bad camera position

However, if your video image does not meet these guidelines, you can check to see if recognition will work. If the face recognition quality turns out to be unsatisfactory, we may consider the module modification to suit your conditions. Please contact our technical support team by following these instructions. Technical support team member will request the necessary information (for example, access to the stream you use for recognition) and will let you know if the improvements are possible and when we will implement them.

Turning on face detection on a video camera

Enabling video analytics on the server

Enable the video analytics plugin. To do so, open the /etc/flussonic/flussonic.conf file and add following line in it:

plugin vision {
  jpeg_vector_helper true;
}

Turning on face detection on a video camera

Note

The recognition settings may not be available if you have selected a non-adjustable preset.

To start faces detection and recognition:

  1. In the Watcher UI, go to Cameras. Find the camera in the list and open its settings by clicking the icon in the upper right corner of the player.

  2. Check the Enable recognition box.

    ANPR

  3. Select Recognize faces in the drop-down list that appears when you check the box.

  4. Select the period to store precise thumbnails for, if necessary. Please refer to Camera settings for details on precise thumbnails.

  5. By default, the recognition system searches for faces over all the camera field of view. You can select specific area(s) to detect faces in by clicking Set up the detection zone. This settings may help you to reduce false detections.

    ANPR

    Note

    The recognition settings may not be available if a non-adjustable preset is selected. In this case, select or create the preset with the settings you need.

  6. Open the file /etc/flussonic/flussonic.conf and the settings of the camera add the vision option, specifying the faces algorithm and GPU number:

stream face-detection-test {
  url fake://fake;
  auth auth://vsaas;
  vision alg=faces gpu=0;
...
}
  • gpu (required) – GPU number. You can use the nvidia-smi tool to find out which number is assigned to your GPU.

Reload the configuration with service flussonic reload so that the changes made to the file take effect.

Face detection

The face detection mode is useful if you need to:

  • Eliminate false triggering of the motion detector on foliage, animals, or other moving objects.
  • Accumulate a person database, which can later be used to divide people into lists.
  • Get statistical information about the passages of unique faces under the camera.

After turning on face recognition on the camera, all recognized faces will fall into the Face detector tab in the Events section, and the following information will be displayed: a photo of the face at the time of recognition, the date and time of recognition, the name of the person (if added to any list), and the ability to uploading a screenshot or video with the process of passing a person under the camera.

Face recognition

Face lists

To implement the tasks of identification and verification, when you need to answer the questions "Who is this?" and “Is this him?”, lists of faces are needed. They allow you to set the names found in the image to the appropriate names and identifiers and use them in other systems (for example, when integrating with access control systems, when you want to allow only employees of a particular office to enter the door).

To view the current lists of persons, go to the Events -> Face detector section and click the Person lists button.

The lists of persons that were created earlier will be opened, as well as a list of persons found on the video that do not belong to any list.

Face recognition

To view the list of persons and information about persons in it, click the list and then select the person you are interested in.

Face recognition

To add a new list, click "Lists" - Create, enter its name and indicate which cameras will search for persons on this list. One camera can serve only one list of faces.

Face recognition

After the list is created, you can add persons. To do this, go to the persons list and click "Persons" - Create.

In the form that opens, enter the name of the person, upload their reference photo, which will be used to compare it with all people passing by, then specify which list of people the person will belong to, and also add an arbitrary note.

Please pay attention to the External ID field which is used for integration with Access Control System or other third party system. At such integrations, Watcher usually have to transmit message about the person it has recognized. However, person databases in Watcher and external system are not related whatsoever. This is why you should enter the external ID of each person i.e. the ID person has in the external database. This will help the external system to understand which person the message from Watcher is related to and proceed with granting/denying access according to its internal logic or performing other actions.

Face recognition

In addition, you can edit information about an unidentified person that was seen by the camera. To do this, open the list of unidentified persons, find the photo from the camera of the person you are looking for and click Edit. After that, enter the information on the person - name, note, and the list of persons.

Face recognition

Now you have added the list and added several persons to it. As the persons pass under the camera, events about their passages will appear in the system on the Events -> Face detector tab. If a known person (from a list) passed under the camera, then the person’s name will be indicated in the event, and if the person was not in any list, then it will be automatically created in the list of unidentified persons and an identifier will be assigned to them.

You can search through the list of events, for example, to find a list of all events of the passage of a person with a given name before the camera. This list can be exported to CSV and analyzed using third-party tools.