Smart surveillance camera systems (Smart Camera) tend to be widely deployed in many parts of the world, especially in shopping centers and public infrastructure, and are used for many different purposes such as: tracking goods, monitoring security order, checking booths, ..
The smart camera market is increasingly potential thanks to the development of information technology and artificial intelligence. Processed by advanced algorithms, so it is capable of performing many intensive tasks: Object analysis and detection, face recognition, ..
Let's learn about some typical technologies used in Smart Camera system to bring breakthrough features.
The system identifies and authenticates by recording a 3-D or 2-D image of the object, depending on the specific case. The data will be saved on the server and compared with relevant information in a real-time database. Thanks to the application of artificial intelligence and machine learning technology, the system is able to operate with the highest standards of safety and reliability.
This is considered one of the leading technologies that determine the success of the Smart Camera system.
Data is captured from the Camera (can be a still image or a dynamic video). Image data is guaranteed to be more accurate if the subject is looking towards the camera.
The software will proceed to read the face shape of the subject. The distance between the eyes and the distance from the forehead to the chin are the main factors of concern. The software will identify landmarks on the face, so it will be easy to distinguish with many different objects.
Scores to authenticate the subject's face are passed into the algorithm and the model is compared with a database of available faces.
Results will be returned after face matching between the object in the camera and the face data available in the database.
The system will sometimes be attacked by fraudulent tricks, such as fake videos, images, etc. Therefore, this technology plays an important role in security and safety. With intelligent detection algorithm, face anti-spoofing technology (FAS) is better secured, attracting more attention from different industries.
Using CNN algorithm to distinguish what is real and fake image data. However, this algorithm only works with some specific conditions, camera quality, environment, lighting, etc. If anything changes, CNN will no longer return correct results. Hence this approach is only viable for limited use cases.
Challenge response technique
Using human actions, including smiling states, sad or happy facial expressions, moving or standing still.. The system verifies those challenges occur in a provided video sequence. The response is then based on a set of identified challenges to authenticate an individual's identity.
With this technique, it is effective in detecting forgery, but requires more diverse input and in some cases affects the user experience.
The facial emotion recognition system is usually deployed in 3 steps:
Get photos and process
Photos are taken from many different data sources (File, database, livestream, webcam, camera, ..), The data source goes through a number of processing steps from there to increase the image quality to make emotion detection become easier. should be more efficient.
Extract features
For the traditional methods, this step is very important, the facial features are determined based on the available algorithms.
Classifying and recognizing emotions
Deep learning networks are widely applied to the problem of detecting facial emotions.
Today, there are many modern technologies such as: age-gender identification technology, VIP customer identification, crime prevention, etc. All thanks to large databases along with artificial intelligence, advanced models and algorithms.
Those are all developments from the facial recognition system. The system allows storing personal information of all subjects. In addition to identifying objects entering and exiting buildings and stores, the system conducts analysis, processing, and information extraction. The system also identifies suspicious objects based on criminal data, then reports to sales staff and managers for timely handling plans.
Facial recognition technology can identify VIP customers' images as well as their ID numbers from which staff are ready to welcome help.
Today's smart surveillance camera system not only helps businesses ensure security, conduct surveillance, contribute to customer information collection, data processing, VIP customer detection, .. Smart cameras will develop further in the future, when applying artificial intelligence and deep learning algorithms.
