It’s important to note that the database does not store the actual photos, but only their "digital weights"—unique data that the neural network uses for precise face recognition. These digital representations enable quick and efficient face search and identification in video streams, allowing the system to recognize a face even if it changes due to angle, lighting, or other external factors. Wait for the process to complete in order to update the database and start using the new face for recognition.
Additionally, the system has the capability to automatically create a face database based on video streams from surveillance cameras. For this to work, the camera must capture at least 5 images of the same face from different angles. The system will analyze these images, extracting key features to efficiently recognize the face in the future, regardless of angle or lighting.
This approach allows for the quick creation of a face database without the need for constant manual image uploads, greatly simplifying the setup and training process for the recognition system.
Searching for Similar PeopleSmartVision makes it possible to find
similar people across different cameras without identifying individuals or linking data to personal information.
This is useful when you need to:
- track a person’s route across multiple cameras,
- find repeated appearances of the same visitor,
- reconstruct the sequence of events,
No names involved - just
smart search that helps navigate video data quickly and in a privacy-respectful way.
In simple terms, the system recognizes
that it’s the same person, without trying to determine
who that person is.