Provide your company with the correct face recognition solution
Author: huifan Time: 2021-01-11
What is facial recognition?
Facial recognition is actually a kind of biometric recognition technology, which allows administrators to quickly identify and detect people appearing in the video. Using facial temperature recognition software, administrators can extract facial feature information points about people from real-time surveillance videos or recorded videos, and compare and match the extracted facial feature information with facial information feature points stored in the system database . If the face in the video or recording cannot match the information in the system database, the system will trigger a security alarm to inform the administrator that other personnel are coming and going, so as to ensure that the safety of personnel is stable
In addition to detecting potential threats or verifying authorized personnel, facial matching technology can also be used to find missing persons; to identify and exclude employees when taking stock in retail scenes; and to speed up post-event investigations.
Our traditional facial recognition solutions are used by municipal agencies, government offices, or small private companies (for example, we often see banking, casino business, or retail store scanning payment pages). There are also law enforcement officers such as police, security inspectors
Two types of facial recognition
The facial recognition market continues to grow and prosper globally, and consumers can choose the technology to implement. Obviously, we cannot create all facial recognition technologies equally, and not all facial recognition ending schemes have goals and ultimate setting goals.. Face recognition technology can be divided into two types of solutions: the type of solutions used for collaborative access control solutions and the type of solutions used for non-cooperative "field" surveillance solutions.
Access control refers to the implementation that is mainly used to manage certain personnel entering certain areas of the facility. In the control settings, the person who needs to register the facial information needs to send an instruction to the system (we can understand it as an identification object such as the ID/IC card Number number), this identification object can connect the facial information between the system and the person To verify the matchIn the wild" facial recognition involves the use of CCTV cameras designed to monitor the area for facial matching. This type of facial recognition is more challenging because the subject does not necessarily look directly at the camera, and the camera may not be in the best position or provide a high enough resolution to ensure high accuracy.
In addition to these two face acquisition schemes, there are also two methods for matching the acquired face with the reference image. In a controlled setting, a person usually provides an identification object (such as an ID card) to the system, which tells the system the face reference that the person must match with. This type of recognition is called 1:1 matching or "verification" because the acquired face is matching a single predetermined reference image. If the system does not have prior recognition data about the person to be recognized (usually in the case of "field" facial recognition), the system must try to match the face to the entire watch list (or a larger subset). This is called a 1:N match (where N is the size of the watch list to be compared) or "identification".
When comparing the specified accuracies of facial recognition engines, it is crucial to check whether these accuracies were achieved in a 1:1 or 1:N comparison, or under controlled or "field" conditions.
1. Overcome the limitations of face recognition
Face recognition is very valuable for identifying people interested in video; however, facial recognition technology is not always available. First, due to privacy regulations, some cities and countries do not allow facial recognition technology. However, even if facial recognition can be used, video surveillance cameras often capture faces "in the wild" under undesirable conditions: in some cases, the installed camera is not optimally placed or cannot record high enough resolution to enable facial recognition video. In other cases, the subject may face away from the camera, the face may be partially obscured, or they may walk quickly in low light conditions, all of which affect the ability to provide accurate face recognition. Without the best conditions, the technology will not always provide the desired results.
2. Several factors to consider when investing in facial recognition
When choosing a facial recognition solution, organizations should consider how to use the technology to ensure that it can meet its unique needs. Buyers should ask themselves whether their current infrastructure is suitable for face recognition, and whether additional or replacement hardware is needed to support basic image quality requirements. They should also consider whether they need to update or reconfigure existing integrations to support new facial recognition capabilities.
3. Advantages of comprehensive video content analysis
If facial recognition technology cannot operate effectively, especially in the case of illegal use of facial recognition technology, the organization's positioning or identification of personnel will be hindered, and the investigation will be shelved. In these regions, organizations will benefit from a comprehensive video content analysis solution powered by artificial intelligence and deep learning, which provides other video search and alert functions in addition to facial recognition. Based on deep learning technology, advanced video content analysis software can detect, identify, extract and classify objects in video shots based on categories and attributes such as gender, appearance similarity, color, size, and moving direction. This feature allows the operator to search for objects or people using filters, such as "a man with black hair walking south and a man with a red short-sleeved shirt".
The comprehensive video survey software also enables users to configure real-time alerts based on class, attributes or face combinations so that security or law enforcement officers can be notified when someone matches the description in the camera feed. Another benefit is that over time, the aggregated video metadata can also be visualized through the video content analysis system-displaying long-term data in dashboards, heat maps and reports to enable managers to make changes for long-term plans Good data drives decision-making.
By integrating comprehensive and extensible video content analysis solutions including face recognition, organizations can enjoy the advantages of these two solutions and apply the technology to convert videos into searchable when permitted and useful. Operational and quantifiable data.