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To configure the basic face Face detection tool, do the following:

1. Select the Face detection object. 
   

2. If you require using need to use this detection tool for real-time facial face recognition, set the corresponding parameter to Yes (1, seeConfiguring real-time facial recognition).

3. If you need to enable recording of record metadata, select Yes from the Record objects tracking list (2).
4. If a the camera supports multistreaming, select the stream for which detection is needed (3). For the correct operation of the Face detection, it is recommended to use a High-quality video stream.
5. If you want need to use this facial face recognition tool in real-time in parallel together with FaceCube Recognition Server (see Configuring FaceCube integration), set Yes for the Real-time recognition on external service parameter (4).

6. If you need to save age and gender information for each recognized captured face, select Yes in the corresponding field (1, see Facial recognition and search). 

   
7. When using wide angle dual lens XingYun devicesIf you use a bi-spherical XingYun lens, the detector will analyze two 180^° spherical images by default (see Configuring fisheye cameras). This may decrease recognition quality. To de-warp dewarp the image before detection, select Yes for the Camera transform parameter (2). This parameter works as well is relevant for other types of image transformation as well. 
8. Select a processing resource for decoding video streams (3). When you select a GPU, a stand-alone graphics card takes priority (when decoding with NVIDIA NVDEC chips). If there 's is no appropriate GPU, the decoding will use the Intel Quick Sync Video technology. Otherwise, CPU resources will be used for decoding.
9. Set the time (in milliseconds) between face search operations in a video frame in the Faсe detection period (msec) field (4). Acceptable values range : is [1; 10000]. Increasing this value decreases the Server load, but can result in some faces being missedundetected. 
10. If you plan to apply the masks detection tool, set Yes for the Face mask detection parameter (5, see Configuring masks detection).
11. In some cases, the detection tool may take mistake other object for a face. To Select Yes in the Filter false alarms field (6) to filter out non-facial face objects, select Yes in the Filter false alarms field while calculating the vector model of a face and its recording into the metadata DB (6). If the filtering is on, false results will appear in the detection feed, but will be ignored during searches in Archivethe archive.

12. Analyzed framed are scaled down to a specified resolution (7, 1280 1920 pixels on the longer side). This is how it works:

    1. If the longer side of the source image exceeds the value specified in the Frame size change field, it is divided by two.

    2. If the resulting resolution falls below the specified value, it is used further.

    3. If the resulting resolution still exceeds the specified limit, it is divided by two, etc.

       Info
       title Note
       For example, the source image resolution is 2048*1536, and the limit specified value is set to1000. In this case, the source resolution will be divided halved two times (down to 512*384): , as after the first division, the number of pixels on the longer side exceeds the limit (1024 > 1000).

       
       

       Info
       title Note
       If detection is performed on a higher resolution stream and detection errors occur, it is recommended to reduce the compression.

       
       

13. Specify the minimum and maximum sizes of detectable faces in % the captured faces as a percentage of the frame size (8). 

14. In the Minimum threshold of face authenticity field, set the minimum level of face recognition accuracy for the creation of a track (9). You can set any value by trial-and-error; no . No less than 90 is recommended. The higher the value is, the fewer faces are detected, while the recognition accuracy increases.

15. Select the processor for the face detection − CPU or NVIDIA GPU (10, see General Information on Configuring Detection). 
    

    Note
    title Attention!
    It may take several minutes to launch the algorithm on an NVIDIA GPU after you apply the settings.  You can You should use caching to speed up future launches (see Configuring the acceleration of GPU-based neuroanalytics Optimization of Face detection on GPU).

    
    

16. If you use FaceCube integration (see Configuring FaceCube integration), activate the Send face imageimages parameter (11).

17. Enter the time in milliseconds after which the face track is considered to be lost in the Track loss time field (12). Acceptable values range : is [1; 10000]. This parameter applies when a face moves in a frame and gets obscured by hidden behind an obstacle for some time. If this time is less than the set value, the face will be recognized as the same..

18. If necessary, fine-tune the detection tool (see Fine-tuning the face detection tool).

19. In the preview window, set the rectangular area of the frame in which you want to perform face detectionSelect a rectangular area to be searched for faces in the preview window. To select the area, move the intersection anchor points .
    

20. Click the Apply button.

The basic face Face detection tool is now configured.