CN114157837A - Safe attendance linked system based on video monitoring cloud platform - Google Patents
Safe attendance linked system based on video monitoring cloud platform Download PDFInfo
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- CN114157837A CN114157837A CN202111437013.1A CN202111437013A CN114157837A CN 114157837 A CN114157837 A CN 114157837A CN 202111437013 A CN202111437013 A CN 202111437013A CN 114157837 A CN114157837 A CN 114157837A
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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
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C1/00—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people
- G07C1/10—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people together with the recording, indicating or registering of other data, e.g. of signs of identity
Abstract
The invention discloses a video monitoring cloud platform-based safety attendance linkage system, which comprises an external unit, a video analysis unit, a storage self-decision unit, a forward monitoring unit, a check monitoring unit, a data interception unit, a preliminary calculation unit and an attendance unit; automatically acquiring a card punching video when a user punches a card through a forward monitoring unit; then, a real-time video of the target area is acquired by using a check-oriented monitoring unit, wherein the check-oriented monitoring unit keeps a mounting place secret during acquisition, and a check-oriented video is acquired; then the forward monitoring unit transmits the card punching video to the video analysis unit, and the core-to-monitoring unit is used for transmitting the core-to-video to the video analysis unit; the video analysis unit is used for carrying out preliminary intercepting statistics on the punching video and the check video to obtain an actual face group and a fake face and automatically obtain a cheating action person and a non-punching person; the application is simple and effective, and is easy to use.
Description
Technical Field
The invention belongs to the field of linkage attendance monitoring, relates to a video monitoring technology, and particularly relates to a safety attendance linkage system based on a video monitoring cloud platform.
Background
The patent with publication number CN109284983A discloses an attendance and security reporting system based on 2.4G remote video snapshot, which comprises a communication service center, a base station, a video monitoring system, a 2.4G remote attendance terminal, a router, a micro-signal enterprise number server, a mobile terminal mobile phone, a 2.4G card reader, a video device and an electronic student identity card; firstly, a 2.4G remote attendance terminal automatically senses and reads an electronic student card, generates a student attendance record and uploads the student attendance record to a communication service center, the communication service center analyzes and processes the attendance record and sends an instruction to a video monitoring system, and videos of 15 seconds before and after the student attendance time are extracted; and then pushed to parents of students through the WeChat enterprise number. The school safety management can be effectively improved, and campus informatization construction is promoted; for the parents, the videos of the children entering and exiting the school can be checked in real time through the micro-signal enterprise number on the mobile phone, so that the parents are more comfortable; for schools, attendance records provide powerful bases for school parties to make clear responsibility and accident handling.
The patent with publication number CN205582024U also provides a student attendance machine for video monitoring, which comprises a real-time video acquisition module, a central processing unit, a card reader, a clock module, a display module and a communication module; the real-time video acquisition module and the output end of the card reader are both connected with the central processing unit; the output end of the central processing unit is connected with a communication module, and the communication module is connected with an external background server; the central processing unit is also respectively connected with the clock module and the display module. The real-time video in front of the attendance machine is collected, and the attendance machine is provided with a communication module which can communicate with an external background server in real time.
However, the two patents provide a video identification card punching machine and also provide the prior art of related video snapshot attendance, but aiming at the two, firstly, the video identification can be deceived in the past in a certain way, and the actual video is not monitored in a linkage manner, under the condition of automatically identifying the card punching, whether the corresponding personnel have the condition that the attendance conditions are inconsistent with the actual working records or not can be detected in a self-service manner, and statistics is carried out aiming at the actual attendance of the personnel; based on this, a solution is provided.
Disclosure of Invention
The invention aims to provide a safe attendance linkage system based on a video monitoring cloud platform.
The purpose of the invention can be realized by the following technical scheme:
the safety attendance linkage system based on the video monitoring cloud platform comprises an external unit, a video analysis unit, a storage self-decision unit, a forward monitoring unit, a nuclear monitoring unit, a data interception unit, a preliminary calculation unit and an attendance unit;
the forward monitoring unit is video card punching equipment arranged at a specified position of a target area and used for automatically acquiring a card punching video when a user punches a card; the nuclear monitoring unit is a monitoring camera device arranged in a target area and is used for acquiring a real-time video of the target area and marking the real-time video as a nuclear video;
the forward monitoring unit is used for transmitting the card punching video to the video analysis unit, and the core-oriented monitoring unit is used for transmitting the core-oriented video to the video analysis unit;
the video analysis unit is pre-stored with the number of standard on-duty people in the target area, and the number of standard on-duty people indicates the number of all people on duty under normal conditions; the video analysis unit is used for carrying out preliminary intercepting statistics on the card punching video and the check video to obtain a real face group and a fake face;
the video analysis unit is used for transmitting the fake face and the real face group to the data interception unit, and the data interception unit stores conventional work time which refers to the working time arrangement of the actual work of the personnel in the target area; the data intercepting unit receives the video analysis unit and transmits the video analysis unit to the real face group, and carries out follow-up monitoring action on the real face group, wherein the follow-up monitoring action is carried out once after work every day, so that the disappearance time and the disappearance times of all real faces are obtained;
the data intercepting unit is used for transmitting the disappearance time and the disappearance times of the fake face and the actual face to the initial calculation unit, and the initial calculation unit is used for performing initial calculation processing on the disappearance time and the disappearance times of the actual face to obtain a negative face, a conventional face and a regular face.
Further, the preliminary interception statistics is specifically as follows:
the method comprises the following steps: acquiring the real-time number of people in the card punching video and the standard number of people on duty;
step two: when the real-time number of people is consistent with the standard number of people on duty, no treatment is carried out;
step three: otherwise, generating a fine check signal; at the moment, all face information in the card punching video is automatically acquired, the face information is matched with standard face information, the non-existing standard face information is marked as an absent face, and the non-existing face information in the standard face information is marked as a redundant face;
step four: after the working time is T1, wherein T1 is preset time, all face information in the check video is automatically acquired again and is marked as a check face information group;
step five: acquiring all face information in the card punching video, and marking the face information as a card punching face group; comparing the card punching face group with the check face information group, and marking the inconsistent card punching face group as a fake face;
step six: marking the face with the card punching face group and the face with the same check face information as a real face group;
step seven: obtaining a false face and a real face group.
Further, the specific manner of the follow-up monitoring behavior is as follows:
s1: acquiring all real face groups;
s2: acquiring the disappearance time and the disappearance times of the actual faces in all the actual face groups; the disappearance time refers to the time when no real face is detected; the disappearance times refer to that the single face disappearance time exceeds the T1 time and the target area is not marked as one time;
s3: and obtaining the disappearance time and the disappearance times of all the real faces.
Further, the T1 time in step S2 is specifically a manager preset value.
Further, the T1 time in step S2 specifically takes a value in the following manner:
s201: collecting office staff in all target areas;
s202: optionally selecting an office worker, and acquiring the time when the face is not acquired every time in one day under the condition that the office worker does not leave a business;
s203: marking all the time as disappearance, wherein all the disappearance constitute a disappearance time group Pi, i ═ 1,. and n;
s204: acquiring the mean value of the disappearance time group, then calculating the absolute value of the difference between all the disappearance times and the mean value, and summing all the absolute values to obtain the difference sum value;
s205: when the difference sum is larger than X1, automatically deleting the disappearance time, otherwise, not processing; according to the mode that the absolute value is from large to small, the corresponding disappearance time with the maximum absolute value is removed firstly;
s206: then repeating the steps S204-S206 again for the remaining disappearance time until the sum of differences is less than or equal to X1; x1 is a preset value;
s207: at this time, the mean value of the disappearance time after deletion is calculated and marked as reasonable time;
s208: acquiring reasonable time of all office workers, calculating a mean value, acquiring a median value between the maximum value of the reasonable time and the mean value, and marking the median value as an upper limit; labeling the median between the minimum and mean of reasonable time as the lower bound of the target;
s209: the value of T1 falls within a range from a target lower limit to a target upper limit.
Further, the initial calculation treatment comprises the following specific steps:
SS 1: calculating the attrition attribute value according to a formula, wherein the specific calculation formula is as follows:
extinction metal value 0.41 disappearance time +0.59 disappearance times;
here, 0.41 and 0.59 are weights preset by the manager;
SS 2: when the abrasion attribute value is greater than X3, the face is considered as a negative face;
when the abrasion metal value is less than or equal to X2 and less than or equal to X3, the human face is determined as a conventional human face;
the remaining labels are face on scale.
Further, the initial calculation unit is used for transmitting the fake face, the passive face, the conventional face and the regular face to the video analysis unit by means of the attendance checking unit, and the video analysis unit is used for transmitting the fake face, the passive face, the conventional face and the regular face to the self-storage decision unit by means of time stamping.
Further, the storage self-decision unit receives a negative face with a timestamp, a conventional face and a regular face transmitted by the video analysis unit, and performs self-statistical analysis, specifically:
redefining the persons marked as negative faces corresponding to more than 5 days in a single month as poor persons;
redefining the persons marked as regular human face corresponding to more than eighty-five percent of days in a single month as recommended persons;
marking the personnel corresponding to the fake face as non-trusted personnel;
the storage self-decision unit is used for transmitting non-trusted people, poor people and recommended people to the external unit for real-time display.
The invention has the beneficial effects that:
according to the invention, a card punching video is automatically acquired when a user punches a card through the forward monitoring unit; then, a real-time video of the target area is acquired by using a check-oriented monitoring unit, wherein the check-oriented monitoring unit keeps a mounting place secret during acquisition, and a check-oriented video is acquired; then the forward monitoring unit transmits the card punching video to the video analysis unit, and the core-to-monitoring unit is used for transmitting the core-to-video to the video analysis unit;
the video analysis unit is used for carrying out preliminary intercepting statistics on the punching video and the check video to obtain an actual face group and a fake face and automatically obtain a cheating action person and a non-punching person; the application is simple and effective, and is easy to use.
Drawings
In order to facilitate understanding for those skilled in the art, the present invention will be further described with reference to the accompanying drawings.
FIG. 1 is a block diagram of the system of the present invention.
Detailed Description
As shown in fig. 1, the security attendance linkage system based on the video monitoring cloud platform provided by the application comprises an external unit, a video analysis unit, a storage self-decision unit, a forward monitoring unit, a nuclear monitoring unit, a data interception unit, an initial calculation unit and an attendance unit;
the forward monitoring unit is video card punching equipment arranged at a specified position of a target area and used for automatically acquiring a card punching video when a user punches a card; the nuclear monitoring unit is a monitoring camera device arranged in a target area and is used for acquiring a real-time video of the target area and marking the real-time video as a nuclear video;
the forward monitoring unit is used for transmitting the card punching video to the video analysis unit, and the core-oriented monitoring unit is used for transmitting the core-oriented video to the video analysis unit;
the video analysis unit is pre-stored with the number of standard on-duty people in the target area, and the number of standard on-duty people indicates the number of all people on duty under normal conditions; the video analysis unit is used for carrying out preliminary intercepting statistics on the punched-card video and the check video, and specifically comprises the following steps:
the method comprises the following steps: acquiring the real-time number of people in the card punching video and the standard number of people on duty;
step two: when the real-time number of people is consistent with the standard number of people on duty, no treatment is carried out;
step three: otherwise, generating a fine check signal; at the moment, all face information in the card punching video is automatically acquired, the face information is matched with standard face information, the non-existing standard face information is marked as an absent face, and the non-existing face information in the standard face information is marked as a redundant face;
step four: after the working time is T1, wherein T1 is preset time, all face information in the check video is automatically acquired again and is marked as a check face information group;
step five: acquiring all face information in the card punching video, and marking the face information as a card punching face group; comparing the card punching face group with the check face information group, and marking the inconsistent card punching face group as a fake face;
step six: marking the face with the card punching face group and the face with the same check face information as a real face group;
step seven: obtaining a fake face and a real face group;
the video analysis unit is used for transmitting the fake face and the real face group to the data interception unit, and the data interception unit stores conventional work time which refers to the working time arrangement of the actual work of the personnel in the target area; the data intercepting unit receives the video analysis unit and transmits the video analysis unit to the real face group, and carries out follow-up monitoring action on the real face group, wherein the follow-up monitoring action is carried out once every day after work, and the follow-up monitoring action specifically comprises the following steps:
s1: acquiring all real face groups;
s2: acquiring the disappearance time and the disappearance times of the actual faces in all the actual face groups; the disappearance time refers to the time when no real face is detected; the disappearance times refer to that the single face disappearance time exceeds the T1 time and the target area is not marked as one time;
the T1 time here is specifically a preset value for the administrator, and a value range may also be defined in the following manner:
s201: collecting office staff in all target areas;
s202: optionally selecting an office worker, and acquiring the time when the face is not acquired every time in one day under the condition that the office worker does not leave a business;
s203: marking all the time as disappearance, wherein all the disappearance constitute a disappearance time group Pi, i ═ 1,. and n;
s204: acquiring the mean value of the disappearance time group, then calculating the absolute value of the difference between all the disappearance times and the mean value, and summing all the absolute values to obtain the difference sum value;
s205: when the difference sum is larger than X1, automatically deleting the disappearance time, otherwise, not processing; according to the mode that the absolute value is from large to small, the corresponding disappearance time with the maximum absolute value is removed firstly;
s206: then repeating the steps S204-S206 again for the remaining disappearance time until the sum of differences is less than or equal to X1; x1 is a preset value;
s207: at this time, the mean value of the disappearance time after deletion is calculated and marked as reasonable time;
s208: acquiring reasonable time of all office workers, calculating a mean value, acquiring a median value between the maximum value of the reasonable time and the mean value, and marking the median value as an upper limit; labeling the median between the minimum and mean of reasonable time as the lower bound of the target;
s209: the value of T1 is within the range from the lower target limit to the upper target limit;
s3: obtaining the disappearance time and the disappearance times of all real faces;
the data intercepting unit is used for transmitting the disappearance time and the disappearance times of the fake face and the actual face to the initial calculation unit, the initial calculation unit is used for performing initial calculation processing on the disappearance time and the disappearance times of the actual face, and the initial calculation processing comprises the following specific steps:
SS 1: calculating the attrition attribute value according to a formula, wherein the specific calculation formula is as follows:
extinction metal value 0.41 disappearance time +0.59 disappearance times;
here, 0.41 and 0.59 are weights preset by the manager;
SS 2: when the abrasion attribute value is greater than X3, the face is considered as a negative face;
when the abrasion metal value is less than or equal to X2 and less than or equal to X3, the human face is determined as a conventional human face;
marking the rest as the regular human face;
the video analysis unit is used for stamping time stamps on the fake face, the negative face, the conventional face and the regular face and transmitting the time stamps to the storage self-decision unit;
the storage self-decision unit receives a negative face with a timestamp, a conventional face and a regular face transmitted by the video analysis unit, and performs self-statistical analysis, specifically:
redefining the persons marked as negative faces corresponding to more than 5 days in a single month as poor persons;
redefining the persons marked as regular human face corresponding to more than eighty-five percent of days in a single month as recommended persons;
marking the personnel corresponding to the fake face as non-trusted personnel;
the storage self-decision unit is used for transmitting non-trusted people, poor people and recommended people to the external unit for real-time display.
According to the invention, a card punching video is automatically acquired when a user punches a card through the forward monitoring unit; then, a real-time video of the target area is acquired by using a check-oriented monitoring unit, wherein the check-oriented monitoring unit keeps a mounting place secret during acquisition, and a check-oriented video is acquired; then the forward monitoring unit transmits the card punching video to the video analysis unit, and the core-to-monitoring unit is used for transmitting the core-to-video to the video analysis unit;
the video analysis unit is used for carrying out preliminary intercepting statistics on the punching video and the check video to obtain an actual face group and a fake face and automatically obtain a cheating action person and a non-punching person; the application is simple and effective, and is easy to use.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.
Claims (8)
1. Safe attendance linked system based on video monitoring cloud platform, its characterized in that includes:
a forward monitoring unit: the system comprises a video card punching device, a video analysis unit and a control unit, wherein the video card punching device is arranged at a designated position of a target area and is used for automatically acquiring a card punching video when a user punches a card and transmitting the card punching video to the video analysis unit;
a nuclear monitoring unit: the system comprises a monitoring camera device, a video analyzing unit and a video analyzing unit, wherein the monitoring camera device is installed in a target area and is used for acquiring a real-time video of the target area, marking the real-time video as a check video and transmitting the check video to the video analyzing unit;
the video analysis unit is used for carrying out primary intercepting statistics on the card punching video and the check video to obtain a real face group and a fake face and transmitting the real face group and the fake face to the data intercepting unit;
the data intercepting unit receives the video analysis unit and transmits the video analysis unit to the real face group, and carries out follow-up monitoring action on the real face group, wherein the follow-up monitoring action is carried out once after work every day, so that the disappearance time and the disappearance times of all real faces are obtained;
a preliminary calculation unit: the false face transmitted by the data interception unit, the real face disappearance time and the disappearance times are subjected to initial calculation processing to obtain a negative face, a conventional face and a regular face.
2. The video monitoring cloud platform-based security attendance linkage system according to claim 1, wherein a standard number of people on duty in the target area is pre-stored in the video analysis unit, and the standard number of people on duty indicates the number of all people on duty under normal conditions; the specific way of preliminary interception statistics is as follows:
the method comprises the following steps: acquiring the real-time number of people in the card punching video and the standard number of people on duty;
step two: when the real-time number of people is consistent with the standard number of people on duty, no treatment is carried out;
step three: otherwise, generating a fine check signal; at the moment, all face information in the card punching video is automatically acquired, the face information is matched with standard face information, the non-existing standard face information is marked as an absent face, and the non-existing face information in the standard face information is marked as a redundant face;
step four: after the working time is T1, wherein T1 is preset time, all face information in the check video is automatically acquired again and is marked as a check face information group;
step five: acquiring all face information in the card punching video, and marking the face information as a card punching face group; comparing the card punching face group with the check face information group, and marking the inconsistent card punching face group as a fake face;
step six: marking the face with the card punching face group and the face with the same check face information as a real face group;
step seven: obtaining a false face and a real face group.
3. The video monitoring cloud platform-based security attendance linkage system according to claim 1, wherein the data intercepting unit stores regular work hours, which refer to work schedule of actual work of personnel in the target area; the following specific mode of monitoring behaviors is as follows:
s1: acquiring all real face groups;
s2: acquiring the disappearance time and the disappearance times of the actual faces in all the actual face groups; the disappearance time refers to the time when no real face is detected; the disappearance times refer to that the single face disappearance time exceeds the T1 time and the target area is not marked as one time;
s3: and obtaining the disappearance time and the disappearance times of all the real faces.
4. The video surveillance cloud platform-based security attendance linkage system according to claim 3, wherein the T1 time in the step S2 is a preset value for a manager.
5. The video monitoring cloud platform-based security attendance linkage system according to claim 4, wherein the T1 time in step S2 specifically takes values in a manner that defines a value range:
s201: collecting office staff in all target areas;
s202: optionally selecting an office worker, and acquiring the time when the face is not acquired every time in one day under the condition that the office worker does not leave a business;
s203: marking all the time as disappearance, wherein all the disappearance constitute a disappearance time group Pi, i ═ 1,. and n;
s204: acquiring the mean value of the disappearance time group, then calculating the absolute value of the difference between all the disappearance times and the mean value, and summing all the absolute values to obtain the difference sum value;
s205: when the difference sum is larger than X1, automatically deleting the disappearance time, otherwise, not processing; according to the mode that the absolute value is from large to small, the corresponding disappearance time with the maximum absolute value is removed firstly;
s206: then repeating the steps S204-S206 again for the remaining disappearance time until the sum of differences is less than or equal to X1; x1 is a preset value;
s207: at this time, the mean value of the disappearance time after deletion is calculated and marked as reasonable time;
s208: acquiring reasonable time of all office workers, calculating a mean value, acquiring a median value between the maximum value of the reasonable time and the mean value, and marking the median value as an upper limit; labeling the median between the minimum and mean of reasonable time as the lower bound of the target;
s209: the value of T1 falls within a range from a target lower limit to a target upper limit.
6. The video monitoring cloud platform-based security attendance linkage system according to claim 1, characterized in that the preliminary calculation processing comprises the following specific steps:
SS 1: calculating the attrition attribute value according to a formula, wherein the specific calculation formula is as follows:
extinction metal value 0.41 disappearance time +0.59 disappearance times;
here, 0.41 and 0.59 are weights preset by the manager;
SS 2: when the abrasion attribute value is greater than X3, the face is considered as a negative face;
when the abrasion metal value is less than or equal to X2 and less than or equal to X3, the human face is determined as a conventional human face;
and marking the rest marks as regular faces, wherein X2 and X3 are preset values.
7. The video surveillance cloud platform-based security attendance linkage system according to claim 1, wherein the initialization unit is configured to transmit the fake face, the passive face, the regular face and the regular face to the video parsing unit via the attendance unit, and the video parsing unit is configured to timestamp the fake face, the passive face, the regular face and the regular face to the stored self-decision unit.
8. The video monitoring cloud platform-based security attendance linkage system according to claim 7, wherein the storage self-decision unit receives the negative face, the conventional face and the regular face with the time stamp transmitted by the video analysis unit, and performs self-statistical analysis, specifically:
redefining the persons marked as negative faces corresponding to more than 5 days in a single month as poor persons;
redefining the persons marked as regular human face corresponding to more than eighty-five percent of days in a single month as recommended persons;
marking the personnel corresponding to the fake face as non-trusted personnel;
the storage self-decision unit is used for transmitting non-trusted people, poor people and recommended people to the external unit for real-time display.
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| CN202111437013.1A CN114157837A (en) | 2021-11-29 | 2021-11-29 | Safe attendance linked system based on video monitoring cloud platform |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114629183A (en) * | 2022-05-17 | 2022-06-14 | 时代云英(深圳)科技有限公司 | Little grid system of distributing type clean energy |
| CN114866843A (en) * | 2022-05-06 | 2022-08-05 | 杭州登虹科技有限公司 | Video data encryption system for network video monitoring |
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- 2021-11-29 CN CN202111437013.1A patent/CN114157837A/en active Pending
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114866843A (en) * | 2022-05-06 | 2022-08-05 | 杭州登虹科技有限公司 | Video data encryption system for network video monitoring |
| CN114866843B (en) * | 2022-05-06 | 2023-08-11 | 杭州登虹科技有限公司 | Video data encryption system for network video monitoring |
| CN114629183A (en) * | 2022-05-17 | 2022-06-14 | 时代云英(深圳)科技有限公司 | Little grid system of distributing type clean energy |
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