At present, important bayonet at airports, customs, ports, borders, etc., because of the country’s constant emphasis on safety, monitoring has become more and more popularized and applied, but most of them are still in the stage of traditional monitoring and it is difficult to meet the requirements of bayonet pairs. The actual needs of security. Due to its lack of intelligent analysis of video, it is generally still in a passive state that can only be “supervised†and cannot be “controlledâ€. Most of them only have the function of collecting evidence afterwards, and they cannot play a role in preventing or alerting the occurrence of suspicious and abnormal behaviors. . The use of face recognition technology can solve this problem and enable the bayonet security system to give full play to its proper monitoring capabilities.
Face recognition is a kind of biometric recognition technology based on human facial feature information. A camera or camera captures images or video streams containing faces, and automatically detects and tracks faces in the images, and then performs a series of related technologies on the detected faces. The flow mainly includes the collection and detection of face images. Face image preprocessing, face image feature extraction, and matching and recognition.
For the collection and monitoring of face images, face recognition technology must be able to meet the dynamic recognition in the dynamic monitoring environment of the airport, because in the real environment, except for the mandatory inspection during the security inspection, in other cases, people are basically It is fluid, so in order not to miss the capture of the face, the algorithm requirements for face recognition are correspondingly high to guarantee the running speed and detection and capture speed of the face recognition system. Therefore, for many vendors that provide face recognition technology, whether or not they have advanced algorithms and belong to their own intellectual property rights is an important criterion for distinguishing the company's technical strength. In addition to capturing, the background needs to be combined with the face comparison server. Face matching, for example, in the customs clearance, the system will quickly capture the face with the background server to determine whether the clearance of people who are blacklisted (including terrorists, criminals, suspects) or whitelisted characters If the whitelist characters are allowed to pass the clearance, if the blacklist characters, the system will immediately issue a warning and refuse to enter or leave the other side. In order to ensure the efficiency of customs clearance, the requirements for the speed and accuracy of the comparison pairs are very high. For example, the matching speed provided by Ruiwei Technology is that a single face matching server can complete 20 million real-time comparisons per second from the face. Face detection takes less than 0.2 seconds to ensure clearance efficiency.
Face recognition is a kind of biometric recognition technology based on human facial feature information. A camera or camera captures images or video streams containing faces, and automatically detects and tracks faces in the images, and then performs a series of related technologies on the detected faces. The flow mainly includes the collection and detection of face images. Face image preprocessing, face image feature extraction, and matching and recognition.
For the collection and monitoring of face images, face recognition technology must be able to meet the dynamic recognition in the dynamic monitoring environment of the airport, because in the real environment, except for the mandatory inspection during the security inspection, in other cases, people are basically It is fluid, so in order not to miss the capture of the face, the algorithm requirements for face recognition are correspondingly high to guarantee the running speed and detection and capture speed of the face recognition system. Therefore, for many vendors that provide face recognition technology, whether or not they have advanced algorithms and belong to their own intellectual property rights is an important criterion for distinguishing the company's technical strength. In addition to capturing, the background needs to be combined with the face comparison server. Face matching, for example, in the customs clearance, the system will quickly capture the face with the background server to determine whether the clearance of people who are blacklisted (including terrorists, criminals, suspects) or whitelisted characters If the whitelist characters are allowed to pass the clearance, if the blacklist characters, the system will immediately issue a warning and refuse to enter or leave the other side. In order to ensure the efficiency of customs clearance, the requirements for the speed and accuracy of the comparison pairs are very high. For example, the matching speed provided by Ruiwei Technology is that a single face matching server can complete 20 million real-time comparisons per second from the face. Face detection takes less than 0.2 seconds to ensure clearance efficiency.
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