CN111815496A - Association detection method and related equipment and device - Google Patents
Association detection method and related equipment and device Download PDFInfo
- Publication number
- CN111815496A CN111815496A CN202010526071.0A CN202010526071A CN111815496A CN 111815496 A CN111815496 A CN 111815496A CN 202010526071 A CN202010526071 A CN 202010526071A CN 111815496 A CN111815496 A CN 111815496A
- Authority
- CN
- China
- Prior art keywords
- preset
- detected
- contact
- target object
- score
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 78
- 238000012216 screening Methods 0.000 claims abstract description 8
- 238000000034 method Methods 0.000 claims description 16
- 230000036760 body temperature Effects 0.000 description 22
- 238000010586 diagram Methods 0.000 description 9
- 230000002159 abnormal effect Effects 0.000 description 6
- 238000009825 accumulation Methods 0.000 description 4
- 238000012545 processing Methods 0.000 description 4
- 238000012360 testing method Methods 0.000 description 4
- 241000712461 unidentified influenza virus Species 0.000 description 4
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000003384 imaging method Methods 0.000 description 3
- 238000001931 thermography Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 2
- 238000005516 engineering process Methods 0.000 description 2
- 238000011835 investigation Methods 0.000 description 2
- 230000000717 retained effect Effects 0.000 description 2
- 206010063385 Intellectualisation Diseases 0.000 description 1
- 241000700605 Viruses Species 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000005540 biological transmission Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 206010022000 influenza Diseases 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 230000009897 systematic effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/26—Government or public services
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J5/0022—Radiation pyrometry, e.g. infrared or optical thermometry for sensing the radiation of moving bodies
- G01J5/0025—Living bodies
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J5/48—Thermography; Techniques using wholly visual means
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
- G01J5/00—Radiation pyrometry, e.g. infrared or optical thermometry
- G01J2005/0077—Imaging
Landscapes
- Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Tourism & Hospitality (AREA)
- Spectroscopy & Molecular Physics (AREA)
- Economics (AREA)
- Educational Administration (AREA)
- Health & Medical Sciences (AREA)
- Development Economics (AREA)
- General Health & Medical Sciences (AREA)
- Human Resources & Organizations (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- General Business, Economics & Management (AREA)
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Image Analysis (AREA)
Abstract
The application discloses a correlation detection method, related equipment and a device, wherein the correlation detection method comprises the following steps: screening an object to be detected meeting a preset distance condition with a target object within a shooting range; and if the object to be detected and the target object meet the preset contact condition, associating the object to be detected with the target object. By the scheme, association detection can be realized.
Description
Technical Field
The present application relates to the field of information technology, and in particular, to a correlation detection method, and related devices and apparatuses.
Background
With the progress and development of science and technology, detection and management equipment in public places such as communities, stations and the like is continuously improved, and the detection and management mode gradually develops towards intellectualization and systematization so as to meet the systematized management requirements of managers.
At present, in various systematic management requirements, due to object association detection, the method has extremely important application values in the aspects of epidemic situation management and control, personnel investigation and the like, and is widely concerned. In view of this, how to implement association detection is an extremely important issue.
Disclosure of Invention
The technical problem mainly solved by the application is to provide a correlation detection method, related equipment and a device, which can realize correlation detection.
In order to solve the above problem, a first aspect of the present application provides an association detection method, including: screening an object to be detected meeting a preset distance condition with a target object within a shooting range; and if the object to be detected and the target object meet the preset contact condition, associating the object to be detected with the target object.
In order to solve the above problem, a second aspect of the present application provides an electronic device, which includes a memory and a processor coupled to each other, the memory storing program instructions, and the processor being configured to execute the program instructions to implement the association detection method in the first aspect.
In order to solve the above problem, a third aspect of the present application provides a storage device storing program instructions executable by a processor, the program instructions being configured to implement the association detection method in the first aspect.
According to the scheme, the object to be detected meeting the preset distance condition between the object to be detected and the target object is screened within the shooting range, and if the object to be detected and the target object meet the preset contact condition, the object to be detected is associated to the target object, so that the object to be detected which is within a certain range of the determined target object and meets the preset contact condition with the target object can be associated to the target object, and then the association detection can be realized.
Drawings
FIG. 1 is a schematic flow chart diagram illustrating an embodiment of a method for detecting association according to the present application;
FIG. 2 is a schematic flow chart diagram illustrating another embodiment of the correlation detection method of the present application;
FIG. 3 is a schematic flow chart diagram illustrating a further embodiment of the correlation detection method of the present application;
FIG. 4 is a block diagram of an embodiment of the correlation detection apparatus of the present application;
FIG. 5 is a block diagram of an embodiment of an electronic device of the present application;
FIG. 6 is a block diagram of an embodiment of a memory device according to the present application.
Detailed Description
The following describes in detail the embodiments of the present application with reference to the drawings attached hereto.
In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular system structures, interfaces, techniques, etc. in order to provide a thorough understanding of the present application.
The terms "system" and "network" are often used interchangeably herein. The term "and/or" herein is merely an association describing an associated object, meaning that three relationships may exist, e.g., a and/or B, may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship. Further, the term "plurality" herein means two or more than two.
Referring to fig. 1, fig. 1 is a schematic flow chart of an embodiment of the association detection method of the present application. Specifically, the method may include the steps of:
step S11: and screening the object to be detected meeting the preset distance condition with the target object within the shooting range.
In one implementation scenario, the target object is a person whose body temperature within the shooting range meets a preset temperature condition, and the preset temperature condition may include: the body temperature is not within a preset body temperature range, the preset body temperature range may be 36 to 38 degrees celsius, and the body temperature may be specifically set according to an actual situation, which is not limited herein. In a specific implementation scenario, the image pickup device may have a thermal imaging function, so that the image pickup device may acquire a thermal imaging image of a person within a shooting range, thereby obtaining a body temperature of the person within the shooting range, and taking the person whose body temperature meets a preset temperature condition as a target object. In another specific implementation scenario, a device for measuring body temperature may be additionally installed near the imaging device, so that a person whose body temperature meets a preset temperature condition is used as a target object, and information of the target object is transmitted, so as to determine the target object within a shooting range of the imaging device. For example, information of the target object may be transmitted to a processing apparatus (e.g., a microcomputer, a server, or the like) connected to the image pickup device, thereby enabling a manager to determine the target object within the shooting range of the image pickup device based on the received information of the target object.
In other implementation scenarios, the target object may also be set as a person meeting other preset conditions according to a specific application scenario, for example, the target object may also be a suspect locked by the police in advance; alternatively, the target object may also be a person who satisfies a preset physical feature; alternatively, the target object may be a missing population (e.g., a kid being abducted, etc.), and may be set according to the actual application, which is not limited herein.
In one implementation scenario, the preset distance condition includes: the distance to the target object is less than or equal to a preset distance threshold (e.g., 2 meters, 2.5 meters, 3 meters, etc.), and the preset distance threshold may be set according to actual situations, and is not limited herein. In a specific implementation scenario, the image capturing device may search for an object to be detected meeting a preset distance condition with a target object in a shooting range according to parameters such as a self pose and a focal length, and specifically, the pose of the image capturing device may include: the mounting position of the imaging device in the world coordinate system, the pitch angle, the yaw angle, the roll angle, and the like are not limited herein.
Step S12: and judging whether the object to be detected and the target object meet preset contact conditions, if so, executing the step S13, otherwise, executing the step S14.
The preset contact condition may be set according to an actual application, for example, the preset contact condition may include: generating a preset contact action with the target object, where the preset contact action specifically includes: at least one of handshake, conversation and hugging is carried out, so that the object to be detected which is in contact with the target object can be found out by judging whether the object to be detected and the target object meet the preset contact condition. For example, taking epidemic situation management and control as an example, if the target object can be a person with abnormal body temperature (possibly infected with influenza virus and the like), then by searching for the objects to be detected which meet preset contact conditions with the target object, the objects to be detected can be continuously tracked subsequently, and if necessary, the objects to be detected are isolated and observed; or, for example, by using a target object as a suspect locked by the police in advance, by searching for objects to be detected meeting preset contact conditions with the target object, and then continuously tracking the objects to be detected, the method can be beneficial to searching and catching crime gangs during gangster crime, and other application scenarios can be analogized, so that the examples are not repeated.
In order to reduce false detection as much as possible and improve the accuracy of the correlation detection, the preset contact condition may further include: the preset contact action is repeatedly generated with the target object more than the preset number of times, and the preset number of times can be set according to practical application, for example, 2 times, 3 times, 4 times and the like, without limitation, so that the object to be detected, which repeatedly generates the preset contact action with the target object more than the preset number of times within the shooting range, can be found. For example, taking epidemic situation management as an example, the target object may be a person with abnormal body temperature (possibly infected with influenza virus, etc.), and by searching for objects to be tested that satisfy preset contact conditions with the target object, the objects to be tested that have too much contact can be continuously tracked, and if necessary, the objects to be tested can be isolated and observed. Other application scenarios may be analogized, and are not exemplified here.
Step S13: and associating the object to be detected to the target object.
If the object to be detected and the target object satisfy the preset contact condition, it may be considered that the object to be detected and the target object have a strong association relationship, for example, taking epidemic situation management and control as an example, the target object may be a person with abnormal body temperature (possibly infected with influenza virus, etc.), and if the object to be detected and the target object satisfy the preset contact condition, it may be considered that the object to be detected has abnormal body temperature (possibly infected with influenza virus, etc.) at a certain probability after a period of time (latency). Or, taking the target object as a suspect locked by the police in advance as an example, if the object to be detected and the target object satisfy the preset contact condition, it may be determined that the object to be detected may have a certain social relationship with the target object (e.g., a case-conscious person, a crime group with the target object, etc.). Other application scenarios may be analogized, and are not exemplified here. Therefore, when the object to be detected and the target object have a strong association relationship, the object to be detected can be associated to the target object, so that when the method is applied to epidemic situation control, personnel in contact with the target object can be quickly searched, and the investigation time is reduced. Specifically, each target object is provided with an associated object set (e.g., an associated face library) corresponding to the target object, and then information (e.g., face information) of the object to be detected may be added to the associated object set (e.g., the associated face library) of the target object. In a specific implementation scenario, before adding the information of the object to be detected to the associated object set of the target object, it may be further detected whether there is an associated object set corresponding to the target object, if so, the information of the object to be detected is directly added to the associated object set of the target object, and if not, the associated object set of the target object is created, and the object to be detected is added to the associated object set of the target object. In another specific implementation scenario, the associated object set of each target object may be stored in a storage end such as a server or a cloud platform, so as to implement data sharing.
In an implementation scenario, a to-be-measured object meeting a preset distance condition with a target object within a shooting range may not meet a preset contact condition with the target object, for example, although the to-be-measured object meets the preset distance condition with the target object with abnormal body temperature, the to-be-measured object does not meet the preset contact condition with the target object (e.g., does not make a preset contact action with the target object), considering that the abnormal body temperature of the target object may be caused by viruses such as influenza and the like, and a certain transmissibility exists in the air, so that a strong association between the to-be-measured object and the target object cannot be completely excluded; or, for example, although the object to be detected and the target object locked as a suspect satisfy the preset distance condition, the object to be detected and the target object do not satisfy the preset contact condition (e.g., do not generate the preset contact action with the target object), considering that the target object may also perform information transmission with the object to be detected in a hidden manner such as eye contact, a special secret number, and the like, it cannot be completely excluded that the object to be detected and the target object have strong association, and other application scenarios may be analogized, which is not exemplified herein. Therefore, in order to further improve the accuracy of the association detection, the following steps may be further performed:
step S14: and keeping the information of the object to be detected for a preset time length so as to continuously detect the object to be detected within the preset time length.
The information of the object to be detected may be face information of the object to be detected, or may also be identity information of the object to be detected, and the like, which is not limited herein.
The preset time period may be one week, one half month, one month, etc., and may be specifically set according to actual situations, which is not limited herein. For example, taking epidemic situation control as an example, the preset duration may be a latency, and other application scenarios may be analogized, which is not illustrated here.
In an implementation scenario, if it is detected that the object to be detected meets the preset alarm condition within the preset time duration, first-level alarm information may be output. Still taking epidemic situation management and control as an example, the preset alarm condition may include: the body temperature of the object to be detected meets the preset temperature condition, and the preset temperature condition can refer to the related steps specifically, which are not described herein again, so that the object to be detected can be considered to be infected by the target object with a certain probability, and at this time, a primary alarm message can be output to remind the manager to pay attention to the continuous observation. In a specific implementation scenario, if a preset number of objects to be detected meet a preset alarm condition within a preset time duration, secondary alarm information may be output, where the preset number may be 2, 3, 4, and the like, and is not limited herein. Still taking epidemic situation management and control as an example, the preset alarm condition may include: the body temperature of the object to be detected meets the preset temperature condition, the preset temperature condition can refer to the related steps specifically, and no further description is given here, the object to be detected can be considered to be infected by the target object with high probability, and at the moment, secondary alarm information can be output to remind a manager to uniformly isolate the object to be detected and the target object when necessary. Other application scenarios may be analogized, and are not exemplified here.
According to the scheme, the object to be detected meeting the preset distance condition between the object to be detected and the target object is screened within the shooting range, and if the object to be detected and the target object meet the preset contact condition, the object to be detected is associated to the target object, so that the object to be detected which is within a certain range of the determined target object and meets the preset contact condition with the target object can be associated to the target object, and then the association detection can be realized.
Referring to fig. 2, fig. 2 is a schematic flow chart of another embodiment of association detection according to the present application. Specifically, the method may include the steps of:
step S21: and screening the object to be detected meeting the preset distance condition with the target object within the shooting range.
Please refer to the related steps in the previous embodiment.
Step S22: and adjusting the total contact score of the object to be measured based on the distance to the target object and/or the contact action with the target object.
In one implementation scenario, the initial value of the total contact score of the object under test may be set to 0.
In one implementation scenario, it may be detected whether a predetermined contact action (e.g., handshake, talk, hug, etc.) occurs between the object to be detected and the target object, and if the predetermined contact action occurs, the total contact score of the object to be detected is adjusted. In a specific implementation scenario, a first contact score corresponding to a preset contact action generated by a target object may be determined, and the higher the contact degree of the preset contact action is, the larger the first contact score is, so as to add the first contact score to the current total contact score of the object to be detected, thereby completing updating of the total contact score of the object to be detected. The contact degree of the preset contact action may be preset, for example, the contact degree of the hug may be set to be higher than the contact degree of the conversation, and the contact degree of the conversation is greater than the contact procedure of the handshake, which is not limited herein; alternatively, the first contact score corresponding to the preset contact action may be preset, for example, the first contact score corresponding to hugging may be preset to 3 points, the first contact score corresponding to talking is preset to 2 points, and the first contact score corresponding to handshaking is preset to 1 point, which is not limited herein. In another specific implementation scenario, a preset detection frequency may be further obtained, so as to perform detection on whether a preset contact action is generated according to the preset detection frequency, specifically, the preset detection frequency may be set according to an actual application, for example, the preset detection frequency may be set to 1 time per minute, 2 times per minute, and the like, without limitation, so as to perform detection on whether the preset contact action is generated according to the preset detection frequency, thereby implementing accumulation of total contact scores of the objects to be detected, and further more accurately detecting the association strength between the objects to be detected and the target object, taking epidemic situation management and control as an example, and by accumulation of the total contact scores of the objects to be detected, more accurately evaluating the dangerous properties (for example, light contact, moderate contact, heavy contact, and the like) of the objects to be detected. Other application scenarios may be analogized, and are not exemplified here.
In an implementation scenario, a second contact score of the object to be detected meeting the preset distance condition may be determined, and the second contact score may be added to the current total contact score of the object to be detected, so as to complete updating of the total contact score of the object to be detected. In a specific implementation scenario, the second contact score of the object to be tested may be set to a preset value (e.g., 1, 2, 3, etc.), so that the total contact score of the object to be tested is uniformly added to the preset value to update the total contact score. In another specific implementation scenario, the second contact score and the distance between the object to be measured and the target object are in a negative correlation relationship, that is, the closer the object to be measured corresponds to a larger second contact score, and the farther the object to be measured corresponds to a smaller second contact score.
Step S23: and judging whether the total contact score of the object to be detected meets a preset score condition, if so, executing the step S24, otherwise, executing the step S25.
Please refer to the related steps in the previous embodiment.
In an implementation scenario, the total contact score of the object to be measured may be updated in real time at a storage terminal such as a server or a cloud platform, so that data can be shared among different image capturing devices. For example, when the target object goes out of the shooting range of the image pickup device A, but comes within the shooting range of the image pickup device B, the detection of the association of the target object and the object to be measured in the shooting range of the image pickup device B can be continued based on the total contact score accumulated in the shooting range of the image pickup device a, to continue the update of the total contact score thereof, when the total contact score of the object to be detected meets a preset score condition, associating the object to be detected with a target object, when the object to be measured is not in the shooting range which can be covered by the system where the camera device is positioned, if the total contact score still does not meet the preset score condition, the information (e.g., face information, total contact score, etc.) of the object to be detected may be retained for a preset time period (e.g., one week, one month, etc.) to continue the detection of the object to be detected for the preset time period.
Step S24: and associating the object to be detected to the target object.
Please refer to the related steps in the previous embodiment.
Step S25: and keeping the information of the object to be detected for a preset time length so as to continuously detect the object to be detected within the preset time length.
Please refer to the related steps in the previous embodiment.
Different from the foregoing embodiment, the target object is determined within the shooting range of the image pickup device, the object to be detected meeting the preset distance condition with the target object is screened within the shooting range, the total contact score of the object to be detected is adjusted based on the distance with the target object and/or the contact action with the target object, and if the total contact score of the object to be detected meets the preset score condition, the object to be detected is associated with the target object, so that the object to be detected within a certain range of the determined target object and meeting the preset score condition with the total contact score can be associated with the target object, the association degree between the object to be detected and the target object can be quantitatively evaluated by using the total contact score, and the accuracy of association detection can be improved.
Referring to fig. 3, fig. 3 is a flowchart illustrating another embodiment of association detection. Specifically, the method may include the steps of:
step S301: and acquiring the body temperature of the target object detected by the thermal imaging camera.
Reference may be made in particular to the relevant steps in the preceding embodiments.
Step S302: and judging whether the body temperature of the target object is within a preset normal temperature range, if not, executing the step S303.
The preset normal temperature range may be set according to actual conditions, and for example, may be set to 36.5 degrees to 37.5 degrees, which is not limited herein. In one implementation scenario, if the body temperature of the target object is within the preset normal temperature range, the process of the association detection may be directly ended.
Step S303: and marking the target object as the object to be detected in the area range according to the pre-configured area range by taking the target object as the center.
The area range may be set according to actual conditions, for example, may be set to be within 5 meters, within 7 meters, within 9 meters, and the like, which is not limited herein.
Step S304: and adding the total contact score of the object to be detected to a first preset score.
The total contact score of the object to be measured may be initially set to 0 point, and the first preset score may be 1 point, 2 points, 3 points, and the like, which is not limited herein. Reference may be made in particular to the relevant steps in the preceding embodiments.
Step S305: and detecting whether a preset contact action is generated between the object to be detected and the target object. If not, go to step S306, otherwise go to step S307.
Reference may be made in particular to the relevant steps in the preceding embodiments.
Step S306: step S305 is re-executed.
If the predetermined contact action is not generated between the object to be detected and the target object, in order to improve the accuracy of the correlation detection, step S305 may be executed again to detect whether the predetermined contact action is generated between the object to be detected and the target object. In an implementation scenario, a preset detection frequency may be set, and the step of detecting whether a preset contact action is generated between the object to be detected and the target object is executed according to the preset detection frequency, which may be referred to as related steps in the foregoing embodiment.
Step S307: and determining a second preset value corresponding to the preset contact action generated between the target objects, and adding the second preset value to the total contact value of the object to be detected.
The second preset value corresponding to the preset contact action can be set according to actual conditions, and specifically, the higher the contact degree of the preset contact action is, the larger the second preset value is. For example, the second preset score corresponding to the hug may be set to 3 points, the second preset score corresponding to the face-to-face conversation may be set to 2 points, the second preset score corresponding to the handshake may be set to 1 point, and so on in other cases, which is not illustrated herein.
Step S308: and judging whether the total contact score exceeds a preset score threshold value, if so, executing the step S309.
If the total contact score exceeds the preset score threshold, it indicates that the object to be detected and the target object are too closely contacted, and the preset score threshold may be set according to an actual situation, which may be specifically referred to in the related steps in the foregoing embodiment. In an implementation scenario, if the total contact score does not exceed the preset score threshold, the information of the object to be detected may be retained for a preset time period, so as to continue to detect the object to be detected within the preset time period, which may be referred to in the relevant steps in the foregoing embodiment.
Step S309: and judging whether the associated face library of the target object is not created, if so, executing the step S310, otherwise, executing the step S311.
The associated face library of the target object comprises face images of the object to be detected which are in close contact with the target object. Reference may be made in particular to the relevant steps in the preceding embodiments.
Step S310: an associated face library of the target object is created.
The associated face library may be created locally or at a server side, which may refer to the relevant steps in the foregoing embodiments, and is not described herein again.
Step S311: and inputting the face image of the object to be detected into an associated face library of the target object.
Specifically, the face image of the object to be measured may be added to the associated face library of the target object. Specifically, reference may be made to the relevant steps in the foregoing embodiments, which are not described herein again.
Step S312: and (6) ending.
Referring to fig. 4, fig. 4 is a schematic diagram of a frame of an embodiment of the association detection apparatus 40 of the present application. The association detection device 40 includes: the object screening module 41 is used for screening an object to be detected meeting a preset distance condition with a target object within a shooting range; the object association module 42 is configured to associate the object to be tested with the target object when the object to be tested and the target object satisfy the preset contact condition.
According to the scheme, the object to be detected meeting the preset distance condition between the object to be detected and the target object is screened within the shooting range, and if the object to be detected and the target object meet the preset contact condition, the object to be detected is associated to the target object, so that the object to be detected which is within a certain range of the determined target object and meets the preset contact condition with the target object can be associated to the target object, and then the association detection can be realized.
In some embodiments, the preset contact conditions include: the total contact score of the object to be detected meets the preset score condition, and the association detecting apparatus 40 further includes a score adjusting module for adjusting the total contact score of the object to be detected based on the distance to the target object and/or the contact action with the target object.
Different from the foregoing embodiment, the target object is determined within the shooting range of the image pickup device, the object to be detected meeting the preset distance condition with the target object is screened within the shooting range, the total contact score of the object to be detected is adjusted based on the distance with the target object and/or the contact action with the target object, and if the total contact score of the object to be detected meets the preset score condition, the object to be detected is associated with the target object, so that the object to be detected within a certain range of the determined target object and meeting the preset score condition with the total contact score can be associated with the target object, the association degree between the object to be detected and the target object can be quantitatively evaluated by using the total contact score, and the accuracy of association detection can be improved.
In some embodiments, the score adjustment module includes a detection sub-module for detecting whether a preset contact action is generated between the object to be detected and the target object, and the score adjustment module includes an adjustment sub-module for adjusting the total contact score of the object to be detected when the preset contact action is generated.
In some embodiments, the adjusting submodule comprises a score determining unit, configured to determine a first contact score corresponding to a preset contact action generated between the target objects, wherein the higher the contact degree of the preset contact action is, the larger the first contact score is, and the adjusting submodule score adding unit is configured to add the first contact score to a current total contact score of the object to be detected.
In some embodiments, the score adjustment module includes a frequency sub-module for obtaining a predetermined detection frequency to perform the detection of whether the predetermined contact action is generated according to the predetermined detection frequency.
Different from the embodiment, the detection of whether the preset contact action is generated or not is executed according to the preset detection frequency by acquiring the preset detection frequency, so that the accumulation of the total contact value of the object to be detected can be realized, and the accuracy of the correlation detection can be improved.
In some embodiments, the score adjusting module includes a determining sub-module for determining a second contact score of the object to be measured satisfying the preset distance condition, and the score adjusting module adds the sub-module for adding the second contact score to the current total contact score of the object to be measured; and the second contact score is a preset numerical value, or the second contact score and the distance between the object to be detected and the target object are in a negative correlation relationship.
In some embodiments, the preset score condition comprises: the total contact score is greater than a preset score threshold, and/or the preset contact action comprises at least one of: handshake, talk, hug.
In some embodiments, the association detecting apparatus 40 further includes an information saving module, configured to, when the object to be detected and the target object do not satisfy the preset contact condition, reserve the information of the object to be detected for a preset time period, so as to continue detecting the object to be detected within the preset time period.
In some embodiments, the association detecting device 40 further includes a target determining module, configured to use a person with a body temperature meeting a preset temperature condition in the shooting range as a target object.
Referring to fig. 5, fig. 5 is a schematic block diagram of an embodiment of an electronic device 50 according to the present application. The electronic device 50 comprises a memory 51 and a processor 52 coupled to each other, the memory 51 stores program instructions, and the processor 52 is configured to execute the program instructions to implement the steps in any of the embodiments of the association detection method described above.
In particular, the processor 52 is configured to control itself and the memory 51 to implement the steps in any of the above-described embodiments of the association detection method. Processor 52 may also be referred to as a CPU (Central Processing Unit). Processor 52 may be an integrated circuit chip having signal processing capabilities. The Processor 52 may also be a general purpose Processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other Programmable logic device, discrete Gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. In addition, processor 52 may be commonly implemented by a plurality of integrated circuit chips.
In this embodiment, the processor 52 is configured to screen, within a shooting range, an object to be detected that meets a preset distance condition with a target object; the processor 52 is configured to associate the object to be tested with the target object if the object to be tested and the target object satisfy the preset contact condition.
According to the scheme, the object to be detected meeting the preset distance condition between the object to be detected and the target object is screened within the shooting range, and if the object to be detected and the target object meet the preset contact condition, the object to be detected is associated to the target object, so that the object to be detected which is within a certain range of the determined target object and meets the preset contact condition with the target object can be associated to the target object, and then the association detection can be realized.
In some embodiments, the preset contact conditions include: the total contact score of the object to be tested satisfies the preset score condition, and the processor 52 is configured to adjust the total contact score of the object to be tested based on the distance to the target object and/or the contact action with the target object.
Different from the foregoing embodiment, the target object is determined within the shooting range of the image pickup device, the object to be detected meeting the preset distance condition with the target object is screened within the shooting range, the total contact score of the object to be detected is adjusted based on the distance with the target object and/or the contact action with the target object, and if the total contact score of the object to be detected meets the preset score condition, the object to be detected is associated with the target object, so that the object to be detected within a certain range of the determined target object and meeting the preset score condition with the total contact score can be associated with the target object, the association degree between the object to be detected and the target object can be quantitatively evaluated by using the total contact score, and the accuracy of association detection can be improved.
In some embodiments, the processor 52 is configured to detect whether a preset contact action is generated between the object to be detected and the target object; the processor 52 is used for adjusting the total contact score of the object to be measured when the preset contact action is generated.
In some embodiments, processor 52 is configured to determine a first contact score corresponding to a preset contact action generated between the target objects, wherein the higher the degree of contact of the preset contact action, the greater the first contact score; processor 52 is configured to add the first contact score to the current total contact score of the test object.
In some embodiments, the processor 52 is configured to obtain a predetermined detection frequency, so as to perform the detection of whether the predetermined contact action is generated according to the predetermined detection frequency.
Different from the embodiment, the detection of whether the preset contact action is generated or not is executed according to the preset detection frequency by acquiring the preset detection frequency, so that the accumulation of the total contact value of the object to be detected can be realized, and the accuracy of the correlation detection can be improved.
In some embodiments, processor 52 is configured to determine a second contact score for the object under test that satisfies the preset distance condition; processor 52 is configured to add the second contact score to the current total contact score of the test object.
In some embodiments, the preset score condition comprises: the total contact score is greater than a preset score threshold; and/or, the preset contact action comprises at least one of: handshake, talk, hug.
In some embodiments, the processor 52 is configured to retain the information of the object to be detected for a preset time period if the object to be detected and the target object do not satisfy the preset contact condition, so as to continue to detect the object to be detected within the preset time period.
In some embodiments, the processor 52 is configured to target a person whose body temperature satisfies a preset temperature condition within the shooting range.
Referring to fig. 6, fig. 6 is a schematic diagram of a memory device 60 according to an embodiment of the present application. The storage device 60 stores program instructions 601 capable of being executed by the processor, the program instructions 601 being for implementing the steps in any of the association detection method embodiments described above.
According to the scheme, the object to be detected meeting the preset distance condition between the object to be detected and the target object is screened within the shooting range, and if the object to be detected and the target object meet the preset contact condition, the object to be detected is associated to the target object, so that the object to be detected which is within a certain range of the determined target object and meets the preset contact condition with the target object can be associated to the target object, and then the association detection can be realized.
In the several embodiments provided in the present application, it should be understood that the disclosed method and apparatus may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, a division of a module or a unit is merely a logical division, and an actual implementation may have another division, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection of devices or units through some interfaces, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
Claims (11)
1. A method for association detection, comprising:
screening an object to be detected meeting a preset distance condition with a target object within a shooting range;
and if the object to be detected and the target object meet the preset contact condition, associating the object to be detected to the target object.
2. The association detection method according to claim 1, characterized in that said preset contact conditions comprise: the total contact score of the object to be detected meets a preset score condition; in the shooting range, after screening an object to be detected meeting a preset distance condition with a target object, and before associating the object to be detected with the target object if the object to be detected and the target object meet a preset contact condition, the method further includes:
and adjusting the total contact score of the object to be tested based on the distance between the object to be tested and/or the contact action between the object to be tested and the target object.
3. The association detection method according to claim 2, wherein the adjusting of the total contact score of the object to be detected based on the contact action with the target object comprises:
detecting whether a preset contact action is generated between the object to be detected and the target object;
and if so, adjusting the total contact score of the object to be detected.
4. The association detection method according to claim 3, wherein said adjusting the total contact score of the object to be detected comprises:
determining a first contact score corresponding to a preset contact action generated between the target objects, wherein the higher the contact degree of the preset contact action is, the larger the first contact score is;
and adding the current total contact score of the object to be tested to the first contact score.
5. The association detection method according to claim 3, wherein before detecting whether the preset contact action is generated between the object to be detected and the target object, the method further comprises:
and acquiring a preset detection frequency to detect whether the preset contact action is generated according to the preset detection frequency.
6. The association detection method according to claim 2, wherein said adjusting the total contact score of the object to be detected based on the distance to the target object comprises:
determining a second contact score of the object to be detected meeting the preset distance condition;
adding the second contact score to the current total contact score of the object to be tested;
the second contact score is a preset numerical value, or the second contact score and the distance between the object to be detected and the target object are in a negative correlation relationship.
7. The association detection method according to claim 2, wherein the preset score condition includes: the total contact score is greater than a preset score threshold;
and/or, the preset contact action comprises at least one of: handshake, talk, hug.
8. The association detection method according to claim 1, characterized in that it further comprises:
if the object to be detected and the target object do not meet the preset contact condition, information of the object to be detected is reserved for a preset time length, and the object to be detected is detected continuously within the preset time length.
9. The correlation detection method according to claim 1, wherein before the object to be detected satisfying a preset distance condition with the target object is screened in the shooting range, the method further comprises;
and taking the person with the temperature meeting the preset temperature condition in the shooting range as the target object.
10. An electronic device comprising a memory and a processor coupled to each other, the memory storing program instructions, the processor being configured to execute the program instructions to implement the association detection method of any one of claims 1 to 9.
11. A storage device storing program instructions executable by a processor to implement the association detection method of any one of claims 1 to 9.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010526071.0A CN111815496A (en) | 2020-06-11 | 2020-06-11 | Association detection method and related equipment and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202010526071.0A CN111815496A (en) | 2020-06-11 | 2020-06-11 | Association detection method and related equipment and device |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111815496A true CN111815496A (en) | 2020-10-23 |
Family
ID=72846081
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202010526071.0A Pending CN111815496A (en) | 2020-06-11 | 2020-06-11 | Association detection method and related equipment and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111815496A (en) |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130325887A1 (en) * | 2012-06-01 | 2013-12-05 | Sony Corporation | Information processing apparatus, information processing method, and program |
| CN106156705A (en) * | 2015-04-07 | 2016-11-23 | 中国科学院深圳先进技术研究院 | A kind of pedestrian's anomaly detection method and system |
| CN107977610A (en) * | 2017-11-21 | 2018-05-01 | 电子科技大学 | A kind of face tracking methods based on massive video processing |
| CN108470179A (en) * | 2018-03-29 | 2018-08-31 | 百度在线网络技术（北京）有限公司 | Method and apparatus for detecting object |
| CN109446998A (en) * | 2018-10-31 | 2019-03-08 | 广州小鹏汽车科技有限公司 | Target person detection method and system |
| CN109872362A (en) * | 2019-01-18 | 2019-06-11 | 腾讯科技（深圳）有限公司 | A kind of object detection method and device |
| CN110008787A (en) * | 2018-01-04 | 2019-07-12 | 佳能株式会社 | The device and method of people and the device of seeker are determined from video |
| CN110110649A (en) * | 2019-05-02 | 2019-08-09 | 西安电子科技大学 | Alternative method for detecting human face based on directional velocity |
| CN110267010A (en) * | 2019-06-28 | 2019-09-20 | Oppo广东移动通信有限公司 | Image processing method, device, server and storage medium |
| CN110458394A (en) * | 2019-07-05 | 2019-11-15 | 阿里巴巴集团控股有限公司 | A kind of index measuring and calculating method and device based on Object related degree |
| CN110598559A (en) * | 2019-08-15 | 2019-12-20 | 深圳和而泰家居在线网络科技有限公司 | Method and device for detecting motion direction, computer equipment and storage medium |
| CN110781853A (en) * | 2019-11-01 | 2020-02-11 | 浙江大华技术股份有限公司 | Crowd abnormality detection method and related device |
| CN111126252A (en) * | 2019-12-20 | 2020-05-08 | 浙江大华技术股份有限公司 | Stall behavior detection method and related device |
-
2020
- 2020-06-11 CN CN202010526071.0A patent/CN111815496A/en active Pending
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130325887A1 (en) * | 2012-06-01 | 2013-12-05 | Sony Corporation | Information processing apparatus, information processing method, and program |
| CN106156705A (en) * | 2015-04-07 | 2016-11-23 | 中国科学院深圳先进技术研究院 | A kind of pedestrian's anomaly detection method and system |
| CN107977610A (en) * | 2017-11-21 | 2018-05-01 | 电子科技大学 | A kind of face tracking methods based on massive video processing |
| CN110008787A (en) * | 2018-01-04 | 2019-07-12 | 佳能株式会社 | The device and method of people and the device of seeker are determined from video |
| CN108470179A (en) * | 2018-03-29 | 2018-08-31 | 百度在线网络技术（北京）有限公司 | Method and apparatus for detecting object |
| CN109446998A (en) * | 2018-10-31 | 2019-03-08 | 广州小鹏汽车科技有限公司 | Target person detection method and system |
| CN109872362A (en) * | 2019-01-18 | 2019-06-11 | 腾讯科技（深圳）有限公司 | A kind of object detection method and device |
| CN110110649A (en) * | 2019-05-02 | 2019-08-09 | 西安电子科技大学 | Alternative method for detecting human face based on directional velocity |
| CN110267010A (en) * | 2019-06-28 | 2019-09-20 | Oppo广东移动通信有限公司 | Image processing method, device, server and storage medium |
| CN110458394A (en) * | 2019-07-05 | 2019-11-15 | 阿里巴巴集团控股有限公司 | A kind of index measuring and calculating method and device based on Object related degree |
| CN110598559A (en) * | 2019-08-15 | 2019-12-20 | 深圳和而泰家居在线网络科技有限公司 | Method and device for detecting motion direction, computer equipment and storage medium |
| CN110781853A (en) * | 2019-11-01 | 2020-02-11 | 浙江大华技术股份有限公司 | Crowd abnormality detection method and related device |
| CN111126252A (en) * | 2019-12-20 | 2020-05-08 | 浙江大华技术股份有限公司 | Stall behavior detection method and related device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6644827B2 (en) | Video surveillance system and video surveillance method | |
| US11171977B2 (en) | Unsupervised spoofing detection from traffic data in mobile networks | |
| AU2014101406B4 (en) | A portable alerting system and a method thereof | |
| US9053621B2 (en) | Image surveillance system and image surveillance method | |
| CN111083435A (en) | Security monitoring method and device and computer readable storage medium | |
| JP2019522949A (en) | Impersonation attack detection during live image capture | |
| CN110210196B (en) | Identity authentication method and device | |
| CN110224870B (en) | Interface monitoring method and device, computing equipment and storage medium | |
| CN111866600B (en) | Method, device and system for protecting privacy | |
| JP2009159448A (en) | Object detecting apparatus, and object detecting method | |
| CN112504473B (en) | Fire detection method, device, equipment and computer readable storage medium | |
| CN110597906A (en) | Block chain-based entrance integral generation method, device, equipment and storage medium | |
| CN111815496A (en) | Association detection method and related equipment and device | |
| CN115687144A (en) | Variation testing method, variation testing device, storage medium and chip | |
| JP7399306B2 (en) | Surveillance system, camera, analysis device and AI model generation method | |
| US20240054489A1 (en) | Traffic information processing methods, apparatuses, electronic devices, servers, and storage mediums | |
| CN114445669A (en) | Smoke and fire alarm method and device, electronic equipment and storage medium | |
| JP6863768B2 (en) | Security system, management device and security method | |
| CN113536899A (en) | Method, device and equipment for optimizing path of fire inspection and computer storage medium | |
| KR101679849B1 (en) | Automatic warning system using mobile phone and method thereof | |
| US12010260B2 (en) | Detecting synthetic sounds in call audio | |
| US20230136241A1 (en) | Detecting synthetic sounds in call audio | |
| CN108881860A (en) | A kind of artificial intelligence TERMINAL DEFENSE system and method | |
| US20210224551A1 (en) | A system and method for deduplicating person detection alerts | |
| US20240062635A1 (en) | A method, an apparatus and a system for managing an event to generate an alert indicating a subject is likely to be unauthorized |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20230824 Address after: Room 201, Building A, Integrated Circuit Design Industrial Park, No. 858, Jianshe 2nd Road, Economic and Technological Development Zone, Xiaoshan District, Hangzhou City, Zhejiang Province, 311225 Applicant after: Zhejiang Huagan Technology Co.,Ltd. Address before: No.1187 Bin'an Road, Binjiang District, Hangzhou City, Zhejiang Province Applicant before: ZHEJIANG DAHUA TECHNOLOGY Co.,Ltd. |