The face recognition system uses the camera to collect images containing human faces, and automatically detects and tracks human faces in the images, and then performs a series of face related technical processing on the detected faces, so as to achieve the purpose of identifying different people's identities The main process includes: face detection. The system detects human faces based on the characteristics of the eyes, eyebrows, mouth, nose and other organs and the geometric positional relationship between them, that is, whether there is a human face in an image or a sequence of images (such as video), and if so, returns Information about the size and position of faces; preprocessing of face images. The original image acquired by the system is often not directly usable due to various conditions and random interference. It must be preprocessed in the early stages of image processing such as grayscale correction and noise filtering; face image feature extraction. Afterwards, some features of the face are extracted and modeled; face image matching and recognition. Finally, the facial feature to be recognized is compared with the obtained facial feature template, and the identity information of the human face is judged according to the similarity degree.
Campus safety has always been a concern of governments everywhere. In addition to the traditional civil air defense and physical air defense, campus technical defense construction has become the focus in the past two years. The content involved mainly includes video surveillance system, access control system and related attendance system.
Since the campus is a place with high mobility, it mainly involves students, faculty and staff. Most campuses use video surveillance to prevent and protect campus safety. But under normal circumstances, the traditional video surveillance system is mainly carried out through equipment to record and personnel monitoring. The problem is that when there are many monitoring points, the monitoring personnel cannot take care of all the monitoring points, and at the same time cannot guarantee to obtain all the information of the monitoring points within 24 hours. Usually, you can only play back afterwards to confirm the specific situation of the incident. However, due to time reasons, it has often caused related losses, and it also requires a lot of manpower to investigate it through playback, inspection, etc. to obtain the required information.
With the development of intelligent analysis technology in the past two years, especially the maturity and application of AI technology. Combining AI intelligent analysis technology with traditional video surveillance will inevitably make up for many deficiencies in current surveillance work. In practical applications, it is possible to process the monitoring image without human intervention, mainly including positioning, transmission, identification, tracking and other functions. Therefore, the current security work can be improved, and at the same time, emergency situations can be handled in time to reduce unnecessary losses.
The application of AI intelligent analysis technology in campus surveillance video can alleviate the heavy burden on people caused by routine inspections and elimination, thereby alleviating the boring security monitoring process. On the other hand, because AI intelligent analysis technology can quickly filter out the required information, it can help personnel quickly find the key points from the massive surveillance video.
The current video surveillance system based on face recognition plays an important role in ensuring campus security, mainly divided into the following points:
Stranger identification and security response. For schools, as long as the image data of students and teachers are stored in the database, the camera can easily identify whether the school staff is an external person. Even if there are conditions, the image recognition system can also be networked with the public security suspect database to judge whether the person is threatening.
In addition, adult traffic and multi-person gathering monitoring alarm. The school's population density itself is very large, and it often shows a concentration of people at a fixed time point, such as school hours, gatherings and other peak hours. Some boarding schools have more people and vehicles at the school entrance during the big week, and there are many hidden safety risks. Then, using face recognition technology to "count heads" in densely populated areas, if the carrying capacity is exceeded, an early warning will be given, and the relevant personnel will conduct dredging treatments, which will help prevent future problems.
At the same time, with the help of the system, it is also possible to manage the student's school situation. In elementary and middle schools, the attendance of students is often monitored by teachers at all times. Using the cameras arranged in the class, they can identify the vacancies and then report the student's attendance. Even, it can accurately report the absence of individual students, the time period of absence, etc., to facilitate teacher management and prevent the occurrence of safety accidents outside the school.
In addition to the above applications, the application in campus security is to establish a series of face access control and attendance systems at campus entrances, classroom entrances, and dormitory entrances. Compared with the traditional card swipe, fingerprint recognition and other modes, the face recognition attendance system has very obvious advantages, such as: preventing card punching, there will be no card loss, time attendance data fraud and other problems; parents and teachers always know the students themselves at school The attendance situation effectively prevents students from skipping classes and staying at night. First, it can effectively ensure the strong supervision of students by campus administrators and parents; furthermore, the use of new technologies can greatly improve the safety index on campus.
Generally speaking, face recognition systems use cameras to collect images containing faces, and automatically detect and track faces in the images, and then perform a series of face-related technical processing on the detected faces to achieve the recognition of different people The main purpose of the identity includes: face detection. The system detects human faces based on the characteristics of the eyes, eyebrows, mouth, nose and other organs and the geometric positional relationship between them, that is, whether there is a human face in an image or a sequence of images (such as video), and if so, returns Information about the size and position of faces; preprocessing of face images. The original image acquired by the system is often not directly usable due to various conditions and random interference. It must be preprocessed in the early stages of image processing such as grayscale correction and noise filtering; face image feature extraction. Afterwards, some features of the face are extracted and modeled; face image matching and recognition. Finally, the facial feature to be recognized is compared with the obtained facial feature template, and the identity information of the human face is judged according to the similarity degree.
After the AI ​​system successfully recognizes the objects, the daily related data (school entrances and dormitory entrances) will be aggregated in real time, and the data records will be analyzed through the computer to automatically generate the required lists and then distributed to the administrators and student parents. Realize the combination of campus safety management and campus daily business management.
In addition to monitoring using image recognition technology, the education department can establish a model database that predicts adolescents' violence tendency through networking with public security, and has been verified with high accuracy. On the other hand, language recognition of social media for teenagers can also help predict and prevent the occurrence of school violence. This is undoubtedly an important measure to ensure the safety of the campus.
In addition, there is also the use of voice recognition to ensure campus safety. Not long ago, a company called I-TEAM in the United States and two other IT companies Genetec and Lencore developed a gunner detection system. This system detects the location of the sound and immediately issues a danger alarm to help law enforcement personnel rush to the correct location to prevent further expansion of the scope of activity in the shortest time.
Technically, it requires a sensor to be installed on every building. This sensor consists of a microphone used to determine the sound source and an infrared camera that recognizes the flash of the muzzle. After the occurrence, the microphone with machine learning capability is determined through the analysis of the sound, and the flash position is captured by the camera to determine the scene and send the information to the law enforcement personnel.
In terms of specific implementation, this system has other functions. Through the surveillance of the camera, the police can lock its position and block the relevant area. If there are more students and there is a greater risk of casualties, the police can lead the system to the best location recommended by the system according to the overall layout of the school and the distribution of personnel for trapping. In this way, the fastest capture and the smallest casualties can be achieved.
The adaptability of this detection system is of course not limited to campuses, but can be tried out in office buildings, churches, government buildings and even residential areas.
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