CN111698471A - Monitoring information storage type identity recognition system - Google Patents
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- CN111698471A CN111698471A CN202010495544.5A CN202010495544A CN111698471A CN 111698471 A CN111698471 A CN 111698471A CN 202010495544 A CN202010495544 A CN 202010495544A CN 111698471 A CN111698471 A CN 111698471A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
- G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
- G06F16/783—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
- G06F16/7837—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using objects detected or recognised in the video content
- G06F16/784—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using objects detected or recognised in the video content the detected or recognised objects being people
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/604—Tools and structures for managing or administering access control systems
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
- G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/80—Generation or processing of content or additional data by content creator independently of the distribution process; Content per se
- H04N21/83—Generation or processing of protective or descriptive data associated with content; Content structuring
- H04N21/845—Structuring of content, e.g. decomposing content into time segments
- H04N21/8456—Structuring of content, e.g. decomposing content into time segments by decomposing the content in the time domain, e.g. in time segments
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/76—Television signal recording
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Abstract
The invention relates to the technical field of identity recognition, in particular to a monitoring information storage type identity recognition system which can quickly find out all video segments of related characters in a monitoring video with longer time span, is convenient to operate, saves a large amount of time for replaying and checking the monitoring video, reduces the labor intensity and improves the practicability; the video monitoring module is used for recording videos and packaging and sending the recorded videos; the first-order video database is used for receiving and storing the recorded video sent by the video monitoring module; the face acquisition unit is used for reading the video in the first-order video database, acquiring a face image appearing in the video and sending the face image; the face modeling unit is used for receiving the face image sent by the face acquisition unit, performing mathematical modeling on the face image and sending a face mathematical model; and the face database is used for receiving and storing the face mathematical model sent by the face modeling unit.
Description
Technical Field
The invention relates to the technical field of identity recognition, in particular to a monitoring information storage type identity recognition system.
Background
Disclosure of Invention
In order to solve the technical problems, the invention provides the monitoring information storage type identity recognition system which can quickly find out all the appeared video segments of the related characters in the monitoring video with longer time span, is convenient to operate, saves a large amount of time for replaying and checking the monitoring video, reduces the labor intensity and improves the practicability.
The invention discloses a monitoring information storage type identity recognition system, which comprises:
the video monitoring module is used for recording videos and packaging and sending the recorded videos;
the first-order video database is used for receiving and storing the recorded video sent by the video monitoring module;
the face acquisition unit is used for reading the video in the first-order video database, acquiring a face image appearing in the video and sending the face image;
the face modeling unit is used for receiving the face image sent by the face acquisition unit, performing mathematical modeling on the face image and sending a face mathematical model;
the face database is used for receiving and storing the face mathematical models sent by the face modeling unit and grouping the face mathematical models with similarity higher than a threshold value into a group;
the video editing unit is used for reading the video in the first-order video database, editing the video segment with the appearance of the object in the video and sending the video segment;
the mapping unit is used for receiving the video segments sent by the video clipping unit, reading the face database, comparing faces appearing in the video segments with face mathematical models stored in the face database, and grouping, packaging and sending the video segments according to the face mathematical models;
the second-order video database is used for receiving and storing the video clips sent by the mapping unit after packet packaging;
and the viewing unit is used for reading the video segments grouped according to the face mathematical model in the second-order video database.
The monitoring information storage type identity recognition system of the invention also comprises:
and the threshold modifying unit is used for modifying the threshold used by the comparison human face mathematical model in the human face database.
The monitoring information storage type identity recognition system of the invention also comprises:
and the backup unit is used for backing up the first-order video database, the face database and the second-order video database.
The monitoring information storage type identity recognition system of the invention also comprises:
and the permission unit is used for setting the use permission when the user reads the second-order video database through the checking unit.
The monitoring information storage type identity recognition system can adopt a password mode, a marking mode and a biological characteristic recognition technology as the mode of setting the authority by the authority unit.
The monitoring information storage type identity recognition system of the invention also comprises:
and the face modeling auxiliary module is used for performing light compensation, gray level transformation, histogram equalization, normalization, geometric correction, filtering and sharpening on the face image received by the face modeling unit.
Compared with the prior art, the invention has the beneficial effects that: the video clip that relevant personage all appeared is found out in the longer surveillance video of time span that can be quick, and the operation of being convenient for saves a large amount of playback simultaneously and looks over the time of surveillance video, reduces intensity of labour, improves the practicality.
Drawings
FIG. 1 is a logic flow diagram of the present invention;
FIG. 2 is a logic flow diagram of a face processing assistance module;
fig. 3 is a logic flow diagram of a threshold modification unit.
Detailed Description
The following detailed description of embodiments of the present invention is provided in connection with the accompanying drawings and examples. The following examples are intended to illustrate the invention but are not intended to limit the scope of the invention.
The video monitoring module records videos and packs and sends the recorded videos; the first-order video database receives and stores the recorded video sent by the video monitoring module; the face acquisition unit reads the video in the first-order video database, acquires a face image appearing in the video and sends the face image; the human face modeling unit receives the human face image sent by the human face acquisition unit, performs mathematical modeling on the human face image and sends the human face mathematical model; the face database receives and stores the face mathematical models sent by the face modeling unit, and classifies the face mathematical models with similarity higher than a threshold into a group; the video clipping unit reads the video in the first-order video database, clips a video segment with an object in the video and sends the video segment; the mapping unit receives the video segments sent by the video clipping unit, reads the face database, compares the faces appearing in the video segments with the face mathematical model stored in the face database, and groups and packages the video segments according to the face mathematical model and sends the video segments; the second-order video database receives and stores video clips sent by the mapping unit after the mapping unit is packed in groups; the checking unit reads video clips grouped according to the face mathematical model in the second-order video database; the video clip that relevant personage all appeared is found out in the longer surveillance video of time span that can be quick, and the operation of being convenient for saves a large amount of playback simultaneously and looks over the time of surveillance video, reduces intensity of labour, improves the practicality.
As a preferred technical scheme, the video monitoring module records videos and packs and sends the recorded videos; the first-order video database receives and stores the recorded video sent by the video monitoring module; the face acquisition unit reads the video in the first-order video database, acquires a face image appearing in the video and sends the face image; the human face modeling unit receives the human face image sent by the human face acquisition unit, performs mathematical modeling on the human face image and sends the human face mathematical model; the face database receives and stores the face mathematical models sent by the face modeling unit, and classifies the face mathematical models with similarity higher than a threshold into a group; the video clipping unit reads the video in the first-order video database, clips a video segment with an object in the video and sends the video segment; the mapping unit receives the video segments sent by the video clipping unit, reads the face database, compares the faces appearing in the video segments with the face mathematical model stored in the face database, and groups and packages the video segments according to the face mathematical model and sends the video segments; the second-order video database receives and stores video clips sent by the mapping unit after the mapping unit is packed in groups; the checking unit reads video clips grouped according to the face mathematical model in the second-order video database; the threshold modifying unit modifies a threshold used for comparing the face mathematical model in the face database; by setting the threshold modifying unit, the sensitivity grouped according to the face mathematical model in the face database can be modified conveniently, the situations that one person is grouped into multiple groups due to overhigh sensitivity and one person is grouped into one group due to overlow sensitivity are reduced, and the accuracy of the system is improved.
As a preferred technical scheme, the video monitoring module records videos and packs and sends the recorded videos; the first-order video database receives and stores the recorded video sent by the video monitoring module; the face acquisition unit reads the video in the first-order video database, acquires a face image appearing in the video and sends the face image; the human face modeling unit receives the human face image sent by the human face acquisition unit, performs mathematical modeling on the human face image and sends the human face mathematical model; the face database receives and stores the face mathematical models sent by the face modeling unit, and classifies the face mathematical models with similarity higher than a threshold into a group; the video clipping unit reads the video in the first-order video database, clips a video segment with an object in the video and sends the video segment; the mapping unit receives the video segments sent by the video clipping unit, reads the face database, compares the faces appearing in the video segments with the face mathematical model stored in the face database, and groups and packages the video segments according to the face mathematical model and sends the video segments; the second-order video database receives and stores video clips sent by the mapping unit after the mapping unit is packed in groups; the checking unit reads video clips grouped according to the face mathematical model in the second-order video database; the backup unit backs up the first-order video database, the face database and the second-order video database; by arranging the backup unit, the first-order video database, the face database and the second-order video database can be backed up, the occurrence of data loss in the first-order video database, the face database and the second-order video database caused by system faults is reduced, data is protected, and the integrity of the system is improved.
As a preferred technical scheme, the video monitoring module records videos and packs and sends the recorded videos; the first-order video database receives and stores the recorded video sent by the video monitoring module; the face acquisition unit reads the video in the first-order video database, acquires a face image appearing in the video and sends the face image; the human face modeling unit receives the human face image sent by the human face acquisition unit, performs mathematical modeling on the human face image and sends the human face mathematical model; the face database receives and stores the face mathematical models sent by the face modeling unit, and classifies the face mathematical models with similarity higher than a threshold into a group; the video clipping unit reads the video in the first-order video database, clips a video segment with an object in the video and sends the video segment; the mapping unit receives the video segments sent by the video clipping unit, reads the face database, compares the faces appearing in the video segments with the face mathematical model stored in the face database, and groups and packages the video segments according to the face mathematical model and sends the video segments; the second-order video database receives and stores video clips sent by the mapping unit after the mapping unit is packed in groups; the checking unit reads video clips grouped according to the face mathematical model in the second-order video database; the permission unit sets the use permission when the user reads the second-order video database through the viewing unit; by setting the authority unit, the situation that no authority personnel check the video to cause video leakage is reduced, and the safety of the system is improved.
As a preferred technical scheme, the video monitoring module records videos and packs and sends the recorded videos; the first-order video database receives and stores the recorded video sent by the video monitoring module; the face acquisition unit reads the video in the first-order video database, acquires a face image appearing in the video and sends the face image; the human face modeling unit receives the human face image sent by the human face acquisition unit, performs mathematical modeling on the human face image and sends the human face mathematical model; the face database receives and stores the face mathematical models sent by the face modeling unit, and classifies the face mathematical models with similarity higher than a threshold into a group; the video clipping unit reads the video in the first-order video database, clips a video segment with an object in the video and sends the video segment; the mapping unit receives the video segments sent by the video clipping unit, reads the face database, compares the faces appearing in the video segments with the face mathematical model stored in the face database, and groups and packages the video segments according to the face mathematical model and sends the video segments; the second-order video database receives and stores video clips sent by the mapping unit after the mapping unit is packed in groups; the checking unit reads video clips grouped according to the face mathematical model in the second-order video database; the permission unit sets the use permission when the user reads the second-order video database through the viewing unit; the authority unit can set authority by password mode, mark mode and biological characteristic identification technology.
As a preferred technical scheme, the video monitoring module records videos and packs and sends the recorded videos; the first-order video database receives and stores the recorded video sent by the video monitoring module; the face acquisition unit reads the video in the first-order video database, acquires a face image appearing in the video and sends the face image; the human face modeling unit receives the human face image sent by the human face acquisition unit, performs mathematical modeling on the human face image and sends the human face mathematical model; the face database receives and stores the face mathematical models sent by the face modeling unit, and classifies the face mathematical models with similarity higher than a threshold into a group; the video clipping unit reads the video in the first-order video database, clips a video segment with an object in the video and sends the video segment; the mapping unit receives the video segments sent by the video clipping unit, reads the face database, compares the faces appearing in the video segments with the face mathematical model stored in the face database, and groups and packages the video segments according to the face mathematical model and sends the video segments; the second-order video database receives and stores video clips sent by the mapping unit after the mapping unit is packed in groups; the checking unit reads video clips grouped according to the face mathematical model in the second-order video database; the face modeling auxiliary module is used for performing light compensation, gray level transformation, histogram equalization, normalization, geometric correction, filtering and sharpening on the face image received by the face modeling unit; by arranging the face modeling auxiliary module, the situation that the face modeling unit is difficult to pick up features for face mathematical modeling due to the fact that the face image received by the face modeling unit is interfered by factors such as ambient light and the like is reduced, and the accuracy of face identification of the system is improved.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (6)
1. A monitoring information storage type identity recognition system, comprising:
the video monitoring module is used for recording videos and packaging and sending the recorded videos;
the first-order video database is used for receiving and storing the recorded video sent by the video monitoring module;
the face acquisition unit is used for reading the video in the first-order video database, acquiring a face image appearing in the video and sending the face image;
the face modeling unit is used for receiving the face image sent by the face acquisition unit, performing mathematical modeling on the face image and sending a face mathematical model;
the face database is used for receiving and storing the face mathematical models sent by the face modeling unit and grouping the face mathematical models with similarity higher than a threshold value into a group;
the video editing unit is used for reading the video in the first-order video database, editing the video segment with the appearance of the object in the video and sending the video segment;
the mapping unit is used for receiving the video segments sent by the video clipping unit, reading the face database, comparing faces appearing in the video segments with face mathematical models stored in the face database, and grouping, packaging and sending the video segments according to the face mathematical models;
the second-order video database is used for receiving and storing the video clips sent by the mapping unit after packet packaging;
and the viewing unit is used for reading the video segments grouped according to the face mathematical model in the second-order video database.
2. The monitored information stored identification system according to claim 1, further comprising:
and the threshold modifying unit is used for modifying the threshold used by the comparison human face mathematical model in the human face database.
3. The monitored information stored identification system according to claim 1, further comprising:
and the backup unit is used for backing up the first-order video database, the face database and the second-order video database.
4. The monitored information stored identification system according to claim 1, further comprising:
and the permission unit is used for setting the use permission when the user reads the second-order video database through the checking unit.
5. The monitored information storage identification system as claimed in claim 4, wherein the means for setting authority by the authority unit can adopt password means, mark means and biometric identification technology.
6. The monitored information stored identity recognition system of claim 5, further comprising:
and the face modeling auxiliary module is used for performing light compensation, gray level transformation, histogram equalization, normalization, geometric correction, filtering and sharpening on the face image received by the face modeling unit.
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Application publication date: 20200922 |