CN112132048A - Community patrol analysis method and system based on computer vision - Google Patents
Community patrol analysis method and system based on computer vision Download PDFInfo
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- 230000002159 abnormal effect Effects 0.000 claims abstract description 7
- 238000001514 detection method Methods 0.000 claims description 18
- 238000013441 quality evaluation Methods 0.000 claims description 9
- 230000009471 action Effects 0.000 claims description 3
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/40—Scenes; Scene-specific elements in video content
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
- G06V40/165—Detection; Localisation; Normalisation using facial parts and geometric relationships
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/18—Status alarms
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Abstract
The application provides a community patrol analysis method and system based on computer vision, wherein the method comprises the following steps: establishing a face library, collecting face data of all cell owners and workers and storing the face data into a server; detecting a face, namely detecting a face shot by a camera in a cell to obtain a first face picture; face tracking, namely predicting the moving condition of a face frame through a face tracking algorithm to obtain more face pictures; evaluating the quality of the human face, and screening the shot human face picture; identifying the identities of the persons in the face pictures after the screening according to a face library; and analyzing results, namely analyzing according to the face recognition results to obtain the activity routes and the activity areas of the personnel and judge abnormal information. The system comprises various modules for implementing the method. The method and the device can perform intelligent analysis on the video of the personnel in the community.
Description
Technical Field
The invention relates to the technical field of patrol security, in particular to a community patrol analysis method and system based on computer vision.
Background
In the prior art, with the introduction and popularization of the concept of "smart city", a large number of new engineering fields such as "smart security", "smart medical treatment" and "smart transportation" have gradually become the focus of government and enterprise attention, and "smart security" has been particularly focused as a field closely related to the safety of people's lives and properties. As one of the important components of the intelligent community, the video monitoring system plays an important role in community security.
Along with the gradual improvement of society to the whole scheme requirement of wisdom community, traditional video monitoring system scheme is suitable for the aftertreatment afterwards, in the aspect of community security protection arrangement, mostly adopts the mode of setting up the camera and granting the ID card, but these cameras only accomplish simple shooting and record the function, can't form intelligent unified management to lower and upper. Once a malignant event occurs, the video in the area can be screened manually only afterwards, and since the intelligent screening is not adopted, a large amount of manpower is needed to screen the video, so that effective coordination and cooperation are difficult to perform, advance prevention cannot be performed, and the requirement of social development cannot be met. In order to solve the above problems, people are always seeking an ideal technical solution.
Disclosure of Invention
In view of this, an object of the embodiments of the present application is to provide a method and a system for analyzing a community patrol based on computer vision, which can perform intelligent analysis on videos of people in a community.
In a first aspect, an embodiment of the present application provides a community patrol analysis method based on computer vision, where the method includes:
establishing a face library, collecting face data of all cell owners and workers and storing the face data into a server;
detecting a face, namely detecting a face shot by a camera in a cell to obtain a first face picture;
face tracking, namely predicting the moving condition of a face frame through a face tracking algorithm to obtain more face pictures;
evaluating the quality of the human face, and screening the shot human face picture;
identifying the identities of the persons in the face pictures after the screening according to a face library;
and analyzing results, namely analyzing according to the face recognition results to obtain the activity routes and the activity areas of the personnel and judge abnormal information.
With reference to the first aspect, an embodiment of the present application provides a first possible implementation manner of the first aspect, where in the face detection step, the method includes:
the method comprises the steps of respectively carrying out face detection, face key point detection and face alignment algorithm on video frames shot by a camera in a cell to obtain the position of a face frame and the position of a face key point, mapping the detected face key point and the key point of a standard face, correcting a detected face image through similarity transformation, correcting a side face into a front face, and obtaining a first face image.
With reference to the first aspect, an embodiment of the present application provides a first possible implementation manner of the first aspect, where in the face recognition step, the method includes:
and obtaining the feature vector of the picture by the face recognition algorithm of the screened face picture, and then comparing the feature vector with the face data in the database to judge the identity of the face.
In a second aspect, an embodiment of the present application further provides a computer vision-based community patrol analysis system, configured to implement the method described above, including:
the storage module is used for storing a face library;
the detection module is used for detecting the face shot by the camera in the cell;
the tracking module is in signal connection with the detection module and obtains more face pictures through a face tracking algorithm;
the quality evaluation module is in signal connection with the tracking module and is used for screening the shot face picture;
the face recognition module is in signal connection with the storage module and the quality evaluation module and is used for recognizing the identity of the person in the face picture after the screening according to a face library;
and the result analysis module is in signal connection with the storage module and the face recognition module and is used for comparing the action track of the target pedestrian in the cell with the predetermined track of routing inspection to obtain the activity route and the activity area of the personnel and judge abnormal information.
With reference to the second aspect, the present application provides a first possible implementation manner of the second aspect, where the apparatus further includes an alarm module, which is in signal connection with the result analysis module.
The embodiment of the application provides a community patrol analysis method and system based on computer vision, in an intelligent community, a face recognition system is adopted, the intelligent community has non-replicability, both hands of people coming in and going out can be liberated, more convenient access management is brought, and meanwhile, the intelligent community is more efficient and safer. Meanwhile, an unknown person who sneaks into the cell can be identified through the video deployment and control system adopting face identification, early warning is timely carried out, and the cell safety is guaranteed. In addition, the face recognition system also gives more humanized service to the cell. For example, the special groups such as the elderly living alone and the disabled in the community are concerned. The face recognition system can detect the access information of the people, and once the access information of the people does not exist for a plurality of days, the system can automatically give an early warning to remind property personnel to visit the door in time. The operation cost is reduced, the safety of the region is improved, and the satisfaction of residents is achieved. Especially, under the social background of the aging population at present, the human efficiency is greatly improved, and the social pressure is relieved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and for those skilled in the art, other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 shows a flowchart of a community patrol analysis method based on computer vision according to an embodiment of the present application.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the present application without making any creative effort, shall fall within the protection scope of the present application.
At present, the community patrol analysis method based on computer vision provided by the embodiment of the present application includes:
establishing a face library, collecting face data of all cell owners and workers and storing the face data into a server;
in order to identify people through computer vision, cameras are required to be arranged at important entrances, various paths, intersections and the like of a monitored area for tracking and identifying pedestrians. And high-definition cameras are deployed at a core gateway and a core area to identify human face features, all the cameras are linked to a background server, and camera data are stored in the server. Initializing the faces of the community and establishing a library, and inputting the faces of community owners and community workers into a system for identifying and distinguishing whether the faces are community workers or strangers outside.
Detecting a face, namely detecting a face shot by a camera in a cell to obtain a first face picture;
the video frames are respectively subjected to face detection, face key point detection, face alignment and other algorithms. The method comprises the steps of obtaining the position of a face frame and the position of a face key point by a face detection algorithm for a video frame, mapping the detected face key point and the key point of a standard face, and correcting a detected face image through similarity transformation, namely correcting a side face into a front face, so that the accuracy of face recognition is improved.
Face tracking, namely predicting the moving condition of a face frame through a face tracking algorithm to obtain more face pictures;
because the movement of the human is continuous, after the human face detection algorithm detects a certain human face for the first time, in order to reduce the calculation overhead, the movement condition of the human face frame is predicted through the human face tracking algorithm, and the repeated calling of the detection algorithm is avoided. And the face quality evaluation is carried out by obtaining the face image through the tracking algorithm.
Evaluating the quality of the human face, and screening the shot human face picture;
due to the complex environment in the real scene, even after the faces are aligned, some factors affecting face recognition, such as large-angle side faces, large-area shielding, poor light conditions and the like, still appear, so that the poor-quality pictures can be filtered as much as possible through a face quality evaluation algorithm. Therefore, the probability of recognition errors can be reduced, and the system overhead can be reduced. And the pictures with higher face quality are submitted to a face recognition algorithm for final recognition.
Identifying the identities of the persons in the face pictures after the screening according to a face library;
and obtaining the characteristic vector of the picture by the picture screened by the face quality algorithm through a face recognition algorithm, and then comparing the characteristic vector with face data in a database to judge the identity of the person. The method can be used in occasions such as community entrance guard and the like, and can also be used for early warning the appearance of strangers in a security system.
And analyzing results, namely analyzing according to the face recognition results to obtain the activity routes and the activity areas of the personnel and judge abnormal information.
The activity route and the activity area of the personnel can be obtained through the information obtained through face recognition, and through comparison and analysis, if the old people do not appear in the area appearing at ordinary times for a few days suddenly, a security guard can be informed to go to the door for checking.
Based on the same inventive concept, the embodiment of the present application further provides a computer vision-based community patrol analysis apparatus corresponding to the computer vision-based community patrol analysis method, including: the storage module is used for storing the human face library and the contents shot by the cameras in the cell;
the detection module is used for detecting the face shot by the camera in the cell;
the tracking module is in signal connection with the detection module and obtains more face pictures through a face tracking algorithm;
the quality evaluation module is in signal connection with the tracking module and is used for screening the shot face picture;
the face recognition module is in signal connection with the storage module and the quality evaluation module and is used for recognizing the identity of the person in the face picture after the screening according to a face library;
the result analysis module is in signal connection with the storage module and the face recognition module and is used for comparing the action track of the target pedestrian in the cell with the scheduled track of inspection, acquiring the activity route and the activity area of the personnel and judging abnormal information;
the device also comprises an alarm module which is in signal connection with the result analysis module.
According to the method and the device, the face tracking technology is matched with the face detection, so that the system overhead is reduced, and the recognition speed of the system is improved.
And the face quality evaluation is adopted to filter most invalid face images, so that the reduction of the system overhead is realized, and the identification accuracy is increased.
Modularization and expansibility, and each function of the system is used as an independent module, so that the development efficiency can be improved, and the maintenance cost is saved.
The face recognition system is adopted, the copying performance is realized, the hands of people entering and exiting can be liberated, more convenient entering and exiting management is brought, and meanwhile, the efficiency and the safety are higher. Meanwhile, an unknown person who sneaks into the cell can be identified through the video deployment and control system adopting face identification, early warning is timely carried out, and the cell safety is guaranteed. In addition, the face recognition system also gives more humanized service to the cell. For example, the special groups such as the elderly living alone and the disabled in the community are concerned. The face recognition system can detect the access information of the people, and once the access information of the people does not exist for a plurality of days, the system can automatically give an early warning to remind property personnel to visit the door in time. The operation cost is reduced, the safety of the region is improved, and the satisfaction of residents is achieved. Especially, under the social background of the aging population at present, the human efficiency is greatly improved, and the social pressure is relieved.
Finally, it should be noted that: the above-mentioned embodiments are only specific embodiments of the present application, and are used for illustrating the technical solutions of the present application, but not limiting the same, and the scope of the present application is not limited thereto, and although the present application is described in detail with reference to the foregoing embodiments, those skilled in the art should understand that: any person skilled in the art can modify or easily conceive the technical solutions described in the foregoing embodiments or equivalent substitutes for some technical features within the technical scope disclosed in the present application; such modifications, changes or substitutions do not depart from the spirit and scope of the exemplary embodiments of the present application, and are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (5)
1. A community patrol analysis method based on computer vision is characterized by comprising the following steps:
establishing a face library, collecting face data of all cell owners and workers and storing the face data into a server;
detecting a face, namely detecting a face shot by a camera in a cell to obtain a first face picture;
face tracking, namely predicting the moving condition of a face frame through a face tracking algorithm to obtain more face pictures;
evaluating the quality of the human face, and screening the shot human face picture;
identifying the identities of the persons in the face pictures after the screening according to a face library;
and analyzing results, namely analyzing according to the face recognition results to obtain the activity routes and the activity areas of the personnel and judge abnormal information.
2. The computer vision-based community patrol analysis method according to claim 1, wherein in the face detection step, the method comprises:
the method comprises the steps of respectively carrying out face detection, face key point detection and face alignment algorithm on video frames shot by a camera in a cell to obtain the position of a face frame and the position of a face key point, mapping the detected face key point and the key point of a standard face, correcting a detected face image through similarity transformation, correcting a side face into a front face, and obtaining a first face image.
3. The computer vision-based community patrol analysis method according to claim 2, wherein in the face recognition step, the method comprises:
and obtaining the feature vector of the picture by the face recognition algorithm of the screened face picture, and then comparing the feature vector with the face data in the database to judge the identity of the face.
4. A computer vision based community patrol analysis system for implementing the method of any one of claims 1 to 3, comprising:
the storage module is used for storing the human face library and the contents shot by the cameras in the cell;
the detection module is used for detecting the face shot by the camera in the cell;
the tracking module is in signal connection with the detection module and obtains more face pictures through a face tracking algorithm;
the quality evaluation module is in signal connection with the tracking module and is used for screening the shot face picture;
the face recognition module is in signal connection with the storage module and the quality evaluation module and is used for recognizing the identity of the person in the face picture after the screening according to a face library;
and the result analysis module is in signal connection with the storage module and the face recognition module and is used for comparing the action track of the target pedestrian in the cell with the predetermined track of routing inspection to obtain the activity route and the activity area of the personnel and judge abnormal information.
5. The computer vision based community patrol analysis system according to claim 4, further comprising an alarm module in signal connection with the result analysis module.
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Application publication date: 20201225 |