Facial recognition is a powerful tool that allows cameras to recognize people based on their unique facial features. This goes beyond regular security, offering a proactive way to control access and enhance safety.
Facial recognition works by capturing facial images and turning them into digital data points that represent each person’s unique features.
Through smart algorithms and learning processes, the system becomes better at telling people apart over time.
In this article, we’ll guide you through the steps of configuring facial recognition for Hikvision cameras and systems.
Hikvision: Face Detection Settings and Other Instructions
Switch to the Face function on the VCA resource
Step 1. Navigate to the VCA section by accessing the “VCA” tab, followed by selecting the desired application. Proceed by choosing the specific VCA option you require, and then advance by clicking the “NEXT” button.
Step 2. The system will automatically initiate a reboot upon switching to the VCA feature, ensuring seamless transition and implementation.
Step 3. Once the reboot process concludes, the configuration settings page can be readily accessed within the VCA menu.
Simply locate and click on “Set Application” to proceed with the configuration of your chosen application.
Set the Correct Settings
Step 1. Begin by configuring camera information. This involves assigning a distinct name to the camera, such as a descriptive label like “face camera,” facilitating easy identification.
Step 2. Establish the Installation Parameter, specifically the height at which the camera is positioned above ground level.
It is crucial for this measurement to be precise, as the accuracy of face detection hinges on it.
The proximity between the camera and the subject positively influences the efficacy of detection, resulting in higher success rates.
Step 3. Access the Face Picture Library section. Here, you will find the option to enrich the library with new face images.
Simply click on the “+Add” button to initiate the process of expanding the facial image repository.
Step 4. Proceed to the Audio Alarm Output configuration. This step is essential if your camera is equipped with an integrated speaker or an external audio output device.
In essence, the camera will be programmed to issue audible directives to the subject, serving as warnings or notifications.
For instance, it might convey messages like, “Caution! Restricted area ahead!” to ensure effective communication.
Set the Face Recognition Parameters (and Other Settings)
Step 1. Configuration of recognition rules is facilitated on this page, as illustrated below. Specify the detection area by outlining a green square, effectively designating the region of interest.
Step 2. Establish the range for minimum and maximum pupil distance. This value should align with the face pixel dimensions within the actual scene.
Essentially, you’re determining the optimal distance for the camera to capture facial features.
This might involve positioning a subject in front of the camera and fine-tuning the distance for accurate results.
Step 3. Arrange the Schedule and Linkage settings. This feature enables the transmission of notifications or alerts upon face detection.
For instance, you can configure your system to deliver alerts containing images of the detected individual’s face directly to your phone.
Step 4. Define the Face Capture Parameters. Initiate by activating face information overlay and capturing intricacies.
Within this section, options include selecting a suitable background, optimizing picture quality, and fine-tuning parameters like facial width, head height, and body height.
These adjustments should be based on the anticipated locations for subject capture.
Step 5. Under the Advanced tab, configure settings as demonstrated below. Opt for the Face Capture Mode labeled as “Quick Shot.”
Adjust the Capture Times to an “Unlimited” setting and ensure to enable the “Upload” option, effectively enabling seamless transfer of captured data.
Comparison and Modeling
The comparison refers to the process of analyzing and evaluating detected facial features against a database of known faces.
When a security camera with face detection capabilities identifies a face within its field of view, it captures various facial attributes, such as the arrangement of eyes, nose, mouth, and other distinctive characteristics.
This captured data is then compared with a database of pre-existing facial profiles to determine if there is a match or similarity. This comparison helps identify individuals and can trigger alerts or actions based on recognized faces.
Modeling involves creating a digital representation of a person’s face based on the data captured by the security camera.
This digital model is essentially a mathematical or algorithmic representation of the facial features, proportions, and structures that make up an individual’s face.
These models are used to establish a baseline reference for each known individual in the system.
When a new face is detected, the system creates a model of that face and compares it to the existing models in the database to determine potential matches.
In Hikvision systems, the configuration of face comparison details necessitates the prior establishment of a face library.
This step involves creating a repository of facial images, serving as a reference for subsequent comparisons.
Once the face library is in place, these settings provide a mechanism to fine-tune the face comparison process.