CN111202504A - Abnormal object management method, system, machine readable medium and equipment - Google Patents
Abnormal object management method, system, machine readable medium and equipment Download PDFInfo
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Abstract
The invention provides an abnormal object management method, which comprises the following steps: acquiring multiple types of images of a detection object; determining a target detection area of the detection object; acquiring a detection index of the target detection area; and judging whether the detection object is an abnormal object or not according to the detection index. The invention adopts non-contact detection to detect the detection index, and the detected person can finish the detection without stopping, standing or doing any action. Meanwhile, the staff is far away from the tested crowd, so that cross infection is effectively avoided.
Description
Technical Field
The invention relates to the field of abnormal condition detection, in particular to an abnormal object management method, an abnormal object management system, a machine readable medium and equipment.
Background
The current infectious diseases around the world are inundated, how to quickly find the infected persons at the dense people flow places does not influence the quick clearance of people, and simultaneously, the infection risk of inspectors is reduced, thus becoming the difficulty of resisting the epidemic situation at present.
It is known that fever is a common manifestation of various infectious diseases, and many infectious diseases are even named as "fever", such as hemorrhagic fever, dengue fever, scarlet fever, etc., and fever is closely related to infectious diseases. Fever is usually a pathophysiological response of the human body to pathogenic agents. It is considered that a change in body temperature above 37.3C or more than 1.2C per day is called "fever".
According to the relationship between fever and infectious diseases, suspected people with fever in people can be found out and then further investigation is carried out. However, the traditional investigation adopts a manual one-by-one detection mode, which seriously affects the clearance efficiency and also increases the infection risk of detection personnel.
Disclosure of Invention
In view of the above-mentioned shortcomings of the prior art, it is an object of the present invention to provide an abnormal object management method, system, machine-readable medium and device, which are used to solve the problems of the prior art.
To achieve the above and other related objects, the present invention provides an abnormal object management method, including:
acquiring multiple types of images of a detection object;
determining a target detection area of the detection object;
acquiring a detection index of the target detection area;
and judging whether the detection object is an abnormal object or not according to the detection index.
Optionally, the multiple types of images include: visible light images, infrared images, laser images.
Optionally, the detection index includes: temperature, blood nucleic acid characteristics.
Optionally, if the image of the detection object includes a visible light image and an infrared image;
detecting a target part of the visible light image to obtain a target part position; determining a target detection area of the target part position in an infrared image of a detection object;
acquiring a detection index of the target detection area of a detection object;
and judging whether the detection object is an abnormal object or not according to the detection index of the target detection area.
Optionally, if the image of the detection object includes a visible light image and a laser image;
detecting a target part of the visible light image to obtain a target part position; determining a target detection area of the target position in a laser image of a detection object;
acquiring a detection index of the target detection area of a detection object;
and judging whether the detection object is an abnormal object or not according to the detection index of the target detection area.
Optionally, the target portion includes a face, a back of a hand, a neck, and a shoulder, and the target detection region includes a face region, a back of a hand region, a neck region, and a shoulder region.
Alternatively, if the detection index is temperature, the detection object is an abnormal object when the temperature of the target detection area of the detection object exceeds a temperature threshold.
Optionally, if the detection index is a blood nucleic acid characteristic, the detection object is an abnormal object when the blood nucleic acid characteristic of the target detection region of the detection object meets a preset condition.
Optionally, the method further comprises:
and tracking the abnormal object by adopting a face recognition technology or a human body recognition technology.
Optionally, the method further comprises:
and when the abnormal object is detected, sending an alarm prompt.
Optionally, if the detection indicator is temperature, the method further includes:
acquiring an age attribute of a detection object;
and setting temperature thresholds corresponding to different age groups according to different age attributes.
Optionally, the method further comprises:
and compensating the temperature of the target detection area based on the distance between the detection object and the image acquisition device.
Optionally, the method further comprises:
acquiring an ambient temperature;
and compensating the temperature of the target detection area according to the environment temperature.
Optionally, if the target detection area is a face area, the method further includes:
judging whether the detection object has smoking behavior or not;
and if the smoking behavior exists, shielding the smoking area.
To achieve the above and other related objects, the present invention provides an abnormal object management system, comprising:
the image acquisition module is used for acquiring various types of images of the detection object;
a detection area determination module for determining a target detection area of the detection object;
the index detection module is used for acquiring a detection index of the target detection area;
and the abnormity judging module is used for judging whether the detection object is an abnormal object according to the detection index.
Optionally, the multiple types of images include: visible light images, infrared images, laser images.
Optionally, the detection index includes: temperature, blood nucleic acid characteristics.
Optionally, if the image of the detection object includes a visible light image and an infrared image;
detecting a target part of the visible light image to obtain a target part position;
determining a target detection area of the target part position in an infrared image of a detection object;
acquiring a detection index of the target detection area of a detection object;
and judging whether the detection object is an abnormal object or not according to the detection index of the target detection area.
Optionally, if the image of the detection object includes a visible light image and a laser image;
detecting a target part of the visible light image to obtain a target part position; determining a target detection area of the target position in a laser image of a detection object;
acquiring a detection index of the target detection area of the laser image;
and judging whether the detection object is an abnormal object or not according to the detection index of the target detection area.
Optionally, the target portion includes a face, a back of a hand, a neck, and a shoulder, and the target detection region includes a face region, a back of a hand region, a neck region, and a shoulder region.
Alternatively, if the detection index is temperature, the detection object is an abnormal object when the temperature of the target detection area of the detection object exceeds a temperature threshold.
Optionally, if the detection index is a blood nucleic acid characteristic, the detection object is an abnormal object when the blood nucleic acid characteristic of the target detection region of the detection object meets a preset condition.
Optionally, the system further comprises:
and the tracking module is used for tracking the abnormal object by adopting a face recognition technology or a human body recognition technology.
Optionally, the system further comprises:
and the alarm module is used for sending out an alarm prompt when the abnormal object is detected.
Optionally, if the detection indicator is temperature, the system further includes:
the age attribute acquisition module is used for acquiring the age attribute of the detection object;
and the temperature threshold setting module is used for setting temperature thresholds corresponding to different age groups according to different age attributes.
Optionally, the system further comprises:
and the first temperature compensation module is used for compensating the temperature of the target detection area based on the distance between the detection object and the image acquisition device.
Optionally, the system further comprises:
the temperature acquisition module is used for acquiring the ambient temperature;
and the second temperature compensation module is used for compensating the temperature of the target detection area according to the environment temperature.
Optionally, if the target detection area is a face area, the system further includes:
the smoking judgment module is used for judging whether the detection object has smoking behavior or not;
and the shielding module is used for shielding the smoking area when smoking behavior exists.
To achieve the above and other related objects, the present invention provides an apparatus comprising:
one or more processors; and
one or more machine-readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform one or more of the methods described previously.
To achieve the foregoing and other related objectives, the present invention provides one or more machine-readable media having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform one or more of the methods described above.
As described above, the abnormal object management method, system, machine-readable medium and device provided by the present invention have the following beneficial effects:
the invention obtains various types of images of a detection object; determining a target detection area of the detection object; acquiring a detection index of the target detection area; and judging whether the detection object is an abnormal object or not according to the detection index. The invention adopts non-contact detection to detect the detection index, and the detected person can finish the detection without stopping, standing or doing any action. Meanwhile, the staff is far away from the tested crowd, so that cross infection is effectively avoided.
Drawings
Fig. 1 is a flowchart of an abnormal object management method according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a method for managing an abnormal object according to another embodiment of the present invention;
FIG. 3 is a flowchart illustrating a method for managing an abnormal object according to another embodiment of the present invention;
fig. 4 is a schematic diagram of a hardware structure of an abnormal object management system according to an embodiment of the present invention;
fig. 5 is a schematic diagram of a hardware structure of a terminal device according to an embodiment of the present invention;
fig. 6 is a schematic diagram of a hardware structure of a terminal device according to another embodiment of the present invention.
Detailed Description
The embodiments of the present invention are described below with reference to specific embodiments, and other advantages and effects of the present invention will be easily understood by those skilled in the art from the disclosure of the present specification. The invention is capable of other and different embodiments and of being practiced or of being carried out in various ways, and its several details are capable of modification in various respects, all without departing from the spirit and scope of the present invention. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present invention, and the components related to the present invention are only shown in the drawings rather than drawn according to the number, shape and size of the components in actual implementation, and the type, quantity and proportion of the components in actual implementation may be changed freely, and the layout of the components may be more complicated.
As shown in fig. 1, an abnormal object management method includes:
s11, acquiring multiple types of images of the detection object;
s12 determining a target detection region of the detection object;
s13, acquiring a detection index of the target detection area;
s14 determines whether or not the detection target is an abnormal target based on the detection index.
The invention obtains various types of images of a detection object; determining a target detection area of the detection object; acquiring a detection index of the target detection area; and judging whether the detection object is an abnormal object or not according to the detection index. The invention adopts non-contact detection to detect the detection index, and the detected person can finish the detection without stopping, standing or doing any action. Meanwhile, the staff is far away from the tested crowd, so that cross infection is effectively avoided.
In this embodiment, the plurality of types of images may include: visible light images, infrared images, laser images. The visible light image can be collected by a visible light image collecting sensor, the infrared image can be collected by an infrared image collecting sensor, and certainly, after the image is collected by an RGB-IR image sensor (capable of receiving RGB components and IR components simultaneously), the RGB-IR processing unit separates the received RGB-IR image data to obtain a synchronous RGB image (visible light image) and an IR image (infrared image); the laser image can be acquired by a laser image acquisition sensor acquisition module. Of course, in another embodiment, at least two images of the two images may be collected by one device, for example, an infrared temperature probe that can simultaneously collect a visible light image and an infrared image, or a laser temperature probe that can simultaneously collect a laser image and an infrared image, or other image collecting devices with the same function; or an image acquisition device which can simultaneously acquire visible light images, infrared images and laser images.
In this embodiment, the detection indexes of the target detection area include: temperature, blood nucleic acid characteristics.
And if the detection index is temperature, when the temperature of the target detection area of the detection object exceeds a temperature threshold value, the detection object is an abnormal object. And finally, when the abnormal object is detected, giving an alarm prompt.
It will be appreciated that the user may set alarm parameters such as preset temperature thresholds, alarm sensitivity, etc. For example, when the temperature of the target detection area exceeds 37.3 degrees, an alarm is given. The alarm mode can be various, such as sound and light indication alarm or voice alarm.
The alarm device is displayed by eye-catching colors on a screen displaying an infrared image or a laser image, can set alarm levels, can display different alarm levels by different colors, and sends different alarm signals by different alarm levels. For example, the alarm level is low, only sound and light alarm, alarm and the like can be given, the voice alarm can be given with higher level, the alarm level is high, and sound and light alarm and voice alarm can be given at the same time.
If the detection index is the blood nucleic acid characteristic, when the blood nucleic acid characteristic of the target detection area of the detection object meets the preset condition, the detection object is an abnormal object. It is understood that an abnormal nucleic acid feature library is previously provided, in which a plurality of nucleic acid features reflecting abnormal states of the human body are stored, and abnormal symptoms corresponding to the nucleic acid features can be identified. If the predetermined condition is satisfied, the blood nucleic acid feature of the detection object can be regarded as one of the abnormal nucleic acid feature libraries. And finally, when the abnormal object is detected, giving an alarm prompt. The foregoing embodiments can be referred to for sending out the alarm prompt, and details are not repeated here.
In one embodiment, a target detection area of the detection object may be determined based on the multi-type images, and then it is determined whether the detection object is an abnormal object according to a detection index of the target detection area. Take a visible light image and an infrared image as examples. As shown in fig. 2, the specific process includes:
s21, detecting the target part of the visible light image to obtain the position of the target part; determining a target detection area of the target part position in an infrared image of a detection object;
s22 acquiring a detection index of the target detection region of the detection object;
s23 determines whether or not the detection target is an abnormal target based on the detection index of the target detection region.
The target part comprises a face, a back of a hand, a neck and a shoulder, and the target detection area comprises a face area, a back of a hand area, a neck area and a shoulder area.
The following description will be made with the target portion as a face, the target detection area as a face area, and the detection index as temperature.
It will be appreciated that since infrared detection is an ongoing process, detection may be performed continuously over a period of time to obtain a plurality of infrared images. Therefore, when detecting the temperature of the face region, it is necessary to obtain images at the same time, that is, an infrared image at the current time and a visible light image at the current time. In the process of determining the face area, firstly, the face detection is carried out on the visible light image at the current moment to obtain the position of the face, and then the face position in the visible light image at the current moment is mapped to the infrared image of the detection object at the current moment to obtain the face area of the detection object in the infrared image at the current moment.
After the face area is determined, the temperature of the face area in the infrared image at the current moment can be measured to obtain the temperature of the face area.
It can be understood that the image of the face area is an infrared image, a corresponding relationship between color and temperature can be obtained in advance, and the temperature corresponding to the color in the face area is determined according to the corresponding relationship between the color and the temperature, so that the temperature of the face area can be determined.
The embodiment adopts a face detection technology, and can simultaneously detect a plurality of faces in a video picture so as to obtain face data of a detection object. Further, an optimal face can be obtained through the face data, the face temperature is measured, and the face area when the optimal face is used as a temperature measurement object. The optimal face can be comprehensively selected through multiple dimensions such as face quality score, face size, face angle, face occlusion rate and the like.
In another embodiment, a target detection area of the detection object may be determined based on the multi-type images, and then it is determined whether the detection object is an abnormal object according to a detection index of the target detection area. Take visible light image and laser image as examples. As shown in fig. 3, the specific process includes:
s31, detecting the target part of the visible light image to obtain the position of the target part; determining a target detection area of the target position in a laser image of a detection object;
s32 acquiring a detection index of the target detection region of the detection object;
s33 determines whether or not the detection target is an abnormal target based on the detection index of the target detection region.
The target part comprises a face, a back of a hand, a neck and a shoulder, and the target detection area comprises a face area, a back of a hand area, a neck area and a shoulder area.
The following description will be made with the target portion as a face, the target detection area as a face area, and the detection index as temperature.
It can be understood that, when the temperature of the face region is detected, images at the same time, that is, a visible light image at the current time and a laser image at the current time, need to be obtained. In the process of determining the face area, firstly, face detection is carried out on visible light at the current moment to obtain the position of a face, and then the face position in the visible light image at the current moment is mapped into the laser image of the detection object at the current moment to obtain the face area of the detection object in the laser image at the current moment.
After the face area is determined, the face area in the laser image at the current moment can be measured to obtain the temperature of the face area.
The embodiment adopts a face detection technology, and can simultaneously detect a plurality of faces in a video picture so as to obtain face data of a detection object. Further, an optimal face can be obtained through the face data, the face temperature is measured, and the face area when the optimal face is used as a temperature measurement object. The optimal face can be comprehensively selected through multiple dimensions such as face quality score, face size, face angle, face occlusion rate and the like.
Since different ages may have different temperatures, the method further comprises:
acquiring an age attribute of a detection object;
and setting temperature thresholds corresponding to different age groups according to different age attributes.
For example, the metabolic rate of children is higher, the body temperature is slightly higher than that of adults, and the temperature threshold corresponding to children can be set slightly higher; the elderly have a lower metabolic rate and may have a slightly lower temperature than the young and the old, and therefore the threshold may be set slightly lower for the elderly.
In an embodiment, a face recognition technique or a human body recognition technique may also be used to track the abnormal object.
After the face or the human body of the detection object is captured, the detection index is detected, and after the detection index is judged to be an abnormal object, the abnormal object is tracked through the recognized face or human body characteristics.
Or, after the face or the human body of the detection object is captured, the face or the human body is compared with the face or the human body in the abnormal object library, and if the comparison is successful, the detection object is tracked.
In an embodiment, if the target detection area is a face area, the method further includes:
judging whether the detection object has smoking behavior or not;
and if the smoking behavior exists, shielding the smoking area.
It is considered that the burning cigarette ends belong to an external heat source and interfere with the detection of the temperature of the face area, and therefore, if the smoking behavior of the detection object exists, the smoking area is shielded.
Whether smoking behavior exists or not can be judged by the following method. For example:
firstly, acquiring a behavior picture of a detected object;
then inputting the behavior picture into a pre-trained behavior recognition model based on a neural network for behavior recognition processing to obtain a behavior identifier for marking the behavior of the detection object;
and if the behavior identification is a preset smoking behavior identification, determining that the behavior of the detection object belongs to a smoking behavior.
It will be appreciated that the temperature of the target detection area is related to the distance between the image capture device acquiring the image and the target detection area, and therefore, in one embodiment, the method further comprises: and compensating the temperature of the target detection area based on the distance between the detection object and the image acquisition device. The accuracy of the measurement is improved by compensating for the temperature of the target detection area.
Because the environmental factors can affect the accuracy of temperature measurement when infrared temperature measurement is performed, the temperature of the target detection area needs to be compensated. Specifically, an ambient temperature is obtained, and the temperature of the target detection area is compensated according to the ambient temperature. More specifically, under the condition of low environmental temperature, the detected temperature value is lower than the real body temperature, and at the moment, the infrared sensing measurement value is properly improved according to the environmental temperature; under the condition of high ambient temperature, the detected temperature value may be higher than the real body temperature, and at this time, the infrared sensing measurement value should be properly reduced according to the ambient temperature.
According to the invention, through infrared images, visible light images and laser images and combining with an artificial intelligence algorithm, automatic tracking, measurement and alarm can be carried out on heating personnel, so that normal personnel can pass through rapidly without feeling, the heating personnel can give an alarm in time, and the risk of infection of inspection personnel is reduced.
As shown in fig. 4, an abnormal object management system includes:
an image acquisition module 41 for acquiring a plurality of types of images of the detection object;
a detection region determination module 42, configured to determine a target detection region of the detection object;
an index detection module 43, configured to obtain a detection index of the target detection area;
and an abnormality determining module 44, configured to determine whether the detection object is an abnormal object according to the detection index.
The invention obtains various types of images of a detection object; determining a target detection area of the detection object; acquiring a detection index of the target detection area; and judging whether the detection object is an abnormal object or not according to the detection index. The invention adopts non-contact detection to detect the detection index, and the detected person can finish the detection without stopping, standing or doing any action. Meanwhile, the staff is far away from the tested crowd, so that cross infection is effectively avoided.
In this embodiment, the plurality of types of images may include: visible light images, infrared images, laser images. The visible light image can be collected through the visible light camera, the infrared image can be collected through the infrared image collecting sensor, and the laser image can be obtained through the laser image obtaining module. Of course, in another embodiment, at least two images of the two images may be collected by one device, for example, an infrared temperature probe that can simultaneously collect a visible light image and an infrared image, or a laser temperature probe that can simultaneously collect a laser image and an infrared image, or other image collecting devices with the same function; of course, after an RGB-IR image sensor (capable of receiving RGB components and IR components simultaneously) collects an image, the RGB-IR processing unit separates the received RGB-IR image data to obtain a synchronized RGB image (visible light image) and an IR image (infrared image); and the image acquisition equipment can also simultaneously acquire visible light images, infrared images and laser images.
In this embodiment, the detection indexes of the target detection area include: temperature, blood nucleic acid characteristics.
And if the detection index is temperature, when the temperature of the target detection area of the detection object exceeds a temperature threshold value, the detection object is an abnormal object. And finally, sending out an alarm prompt when the abnormal object is detected through the alarm prompt module.
It will be appreciated that the user may set alarm parameters such as preset temperature thresholds, alarm sensitivity, etc. For example, when the temperature of the target detection area exceeds 37.3 degrees, an alarm is given. The alarm mode can be various, such as sound and light indication alarm or voice alarm.
Or, the screen displaying the infrared image is displayed by a striking color, the alarm level can be set, different alarm levels can be displayed by different colors, and different alarm signals can be sent by different alarm levels. For example, the alarm level is low, only sound and light alarm, alarm and the like can be given, the voice alarm can be given with higher level, the alarm level is high, and sound and light alarm and voice alarm can be given at the same time.
If the detection index is the blood nucleic acid characteristic, when the blood nucleic acid characteristic of the target detection area of the detection object meets the preset condition, the detection object is an abnormal object. It is understood that an abnormal nucleic acid feature library is previously provided, in which a plurality of nucleic acid features reflecting abnormal states of the human body are stored, and abnormal symptoms corresponding to the nucleic acid features can be identified. If the predetermined condition is satisfied, the blood nucleic acid feature of the detection object can be regarded as one of the abnormal nucleic acid feature libraries. And finally, when the abnormal object is detected, giving an alarm prompt. The foregoing embodiments can be referred to for sending out the alarm prompt, and details are not repeated here.
In one embodiment, a target detection area of the detection object may be determined based on the multi-type images, and then it is determined whether the detection object is an abnormal object according to a detection index of the target detection area. Take a visible light image and an infrared image as examples. The specific process comprises the following steps:
detecting a target part of the visible light image to obtain a target part position; determining a target detection area of the target part position in an infrared image of a detection object;
acquiring a detection index of the target detection area of a detection object;
and judging whether the detection object is an abnormal object or not according to the detection index of the target detection area.
The target part comprises a face, a back of a hand, a neck and a shoulder, and the target detection area comprises a face area, a back of a hand area, a neck area and a shoulder area.
The following description will be made with the target portion as a face and the target detection area as a face area.
It will be appreciated that since infrared detection is an ongoing process, detection may be performed continuously over a period of time to obtain a plurality of infrared images. Therefore, when detecting the temperature of the face region, it is necessary to obtain images at the same time, that is, an infrared image at the current time and a visible light image at the current time. In the process of determining the face area, firstly, the face detection is carried out on the visible light image at the current moment to obtain the position of the face, and then the face position in the visible light image at the current moment is mapped to the infrared image of the detection object at the current moment to obtain the face area of the detection object in the infrared image at the current moment.
After the face area is determined, the temperature of the face area in the infrared image at the current moment can be measured to obtain the temperature of the face area.
It can be understood that the image of the face area is an infrared image, a corresponding relationship between color and temperature can be obtained in advance, and the temperature corresponding to the color in the face area is determined according to the corresponding relationship between the color and the temperature, so that the temperature of the face area can be determined.
The embodiment adopts a face detection technology, and can simultaneously detect a plurality of faces in a video picture so as to obtain face data of a detection object. Further, an optimal face can be obtained through the face data, the face temperature is measured, and the face area when the optimal face is used as a temperature measurement object. The optimal face can be comprehensively selected through multiple dimensions such as face quality score, face size, face angle, face occlusion rate and the like.
In another embodiment, a target detection area of the detection object may be determined based on the multi-type images, and then it is determined whether the detection object is an abnormal object according to a detection index of the target detection area. Take visible light image and laser image as examples. The specific process comprises the following steps:
detecting a target part of the visible light image to obtain a target part position; determining a target detection area of the target position in a laser image of a detection object;
acquiring a detection index of the target detection area of the laser image;
and judging whether the detection object is an abnormal object or not according to the detection index of the target detection area.
The target part comprises a face, a back of a hand, a neck and a shoulder, and the target detection area comprises a face area, a back of a hand area, a neck area and a shoulder area.
The following description will be made with the target portion as a face and the target detection area as a face area.
It can be understood that, when the temperature of the face region is detected, images at the same time, that is, a visible light image at the current time and a laser image at the current time, need to be obtained. In the process of determining the face area, firstly, the face detection is carried out on the visible light image at the current moment to obtain the position of the face, and then the face position in the visible light image at the current moment is mapped to the laser image of the detection object at the current moment to obtain the face area of the detection object in the laser image at the current moment.
After the face area is determined, the face area in the laser image at the current moment can be measured to obtain the temperature of the face area.
It can be understood that the image of the face area is a laser image, a corresponding relationship between color and temperature can be obtained in advance, and the temperature corresponding to the color in the face area is determined according to the corresponding relationship between the color and the temperature, so that the temperature of the face area can be determined.
The embodiment adopts a face detection technology, and can simultaneously detect a plurality of faces in a video picture so as to obtain face data of a detection object. Further, an optimal face can be obtained through the face data, the face temperature is measured, and the face area when the optimal face is used as a temperature measurement object. The optimal face can be comprehensively selected through multiple dimensions such as face quality score, face size, face angle, face occlusion rate and the like.
Since different ages may have different temperatures, the system further comprises:
the age attribute acquisition module is used for acquiring the age attribute of the detection object;
and the temperature threshold setting module is used for setting temperature thresholds corresponding to different age groups according to different age attributes.
For example, the metabolic rate of children is higher, the body temperature is slightly higher than that of adults, and the temperature threshold corresponding to children can be set slightly higher; the elderly have a lower metabolic rate and may have a slightly lower temperature than the young and the old, and therefore the threshold may be set slightly lower for the elderly.
In an embodiment, the system further comprises:
and the tracking module is used for tracking the abnormal object by adopting a face recognition technology or a human body recognition technology.
After the face or the human body of the detection object is captured, the detection index is detected, and after the detection index is judged to be an abnormal object, the abnormal object is tracked through the recognized face or human body characteristics.
Or, after the face or the human body of the detection object is captured, the face or the human body is compared with the face or the human body in the abnormal object library, and if the comparison is successful, the detection object is tracked.
In an embodiment, if the target detection area is a face area, the system further includes:
the smoking judgment module is used for judging whether the detection object has smoking behavior or not;
and the shielding module is used for shielding the smoking area when smoking behavior exists.
It is considered that the burning cigarette ends belong to an external heat source and interfere with the detection of the temperature of the face area, and therefore, if the smoking behavior of the detection object exists, the smoking area is shielded.
Whether smoking behavior exists or not can be judged by the following method. For example:
firstly, acquiring a behavior picture of a detected object;
then inputting the behavior picture into a pre-trained behavior recognition model based on a neural network for behavior recognition processing to obtain a behavior identifier for marking the behavior of the detection object;
and if the behavior identification is a preset smoking behavior identification, determining that the behavior of the detection object belongs to a smoking behavior.
It will be appreciated that the temperature of the target detection area is related to the distance between the image capture device that captured the image and the target detection area, and therefore, in one embodiment, the system further comprises:
and the first temperature compensation module is used for compensating the temperature of the target detection area based on the distance between the detection object and the image acquisition device. The accuracy of the measurement is improved by compensating for the temperature of the target detection area.
Because the environmental factors can affect the accuracy of temperature measurement when infrared temperature measurement is performed, the temperature of the target detection area needs to be compensated. Thus, the system further comprises:
the temperature acquisition module is used for acquiring the ambient temperature;
and the second temperature compensation module is used for compensating the temperature of the target detection area according to the environment temperature.
Specifically, more specifically, under the condition of low ambient temperature, the detected temperature value is lower than the real body temperature, and at this time, the infrared sensing measurement value should be properly improved according to the ambient temperature; under the condition of high ambient temperature, the detected temperature value may be higher than the real body temperature, and at this time, the infrared sensing measurement value should be properly reduced according to the ambient temperature.
According to the invention, through infrared images, visible light images and laser images and combining with an artificial intelligence algorithm, automatic tracking, measurement and alarm can be carried out on heating personnel, so that normal personnel can pass through rapidly without feeling, the heating personnel can give an alarm in time, and the risk of infection of inspection personnel is reduced.
The invention adopts non-contact temperature measurement, and the detected person can finish the body temperature detection without stopping, standing or doing any action. Meanwhile, the staff is far away from the tested crowd, so that cross infection is effectively avoided. The image response speed is 0.04ms, the temperature measurement response speed is high, 16 targets can be detected within 30 ms, the 16 targets can be measured in real time, the method has the characteristics of non-contact rapidness, convenience, intuition, safety and the like, and the problem that the traditional thermometers, forehead thermometers, point thermometers, ear thermometers and the like only aim at individual measurement is solved (for example, the traditional thermometers generally need 3 minutes per person for detection, and the common point thermometers, forehead thermometers and ear thermometers generally need 4-5 seconds per person for detection).
The temperature measuring range of the invention is as follows: temperature measurement precision is as follows at 0-60 deg.C: the temperature is between 28 and 45 ℃ and is less than or equal to +/-0.3 ℃, and automatic temperature measurement correction is built in. The human face quarantine body temperature screening and early warning avoids the defects of long time consumption, easy cross infection and the like, can effectively control epidemic spread and reduce casualties, and is very suitable for quickly examining the body temperature in occasions with large human flow, such as airports, docks, stations, banks, hospitals, markets and the like.
The invention can carry out long-distance and large-area detection
Thermal imaging resolution 384 × 288; focal length 6.8/15 mm: 1.2-2 meters detection distance, 15mm focal length: detecting the distance of 3-7 meters;
visible light resolution: 1920 x 1080, focal length 5 mm;
an embodiment of the present application further provides an apparatus, which may include: one or more processors; and one or more machine readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform the method of fig. 1. In practical applications, the device may be used as a terminal device, and may also be used as a server, where examples of the terminal device may include: the mobile terminal includes a smart phone, a tablet computer, an electronic book reader, an MP3 (Moving Picture Experts Group Audio Layer III) player, an MP4 (Moving Picture Experts Group Audio Layer IV) player, a laptop, a vehicle-mounted computer, a desktop computer, a set-top box, an intelligent television, a wearable device, and the like.
The present application further provides a non-transitory readable storage medium, where one or more modules (programs) are stored in the storage medium, and when the one or more modules are applied to a device, the device may be caused to execute instructions (instructions) of steps included in the method in fig. 1 according to the present application.
Fig. 5 is a schematic diagram of a hardware structure of a terminal device according to an embodiment of the present application. As shown, the terminal device may include: an input device 1100, a first processor 1101, an output device 1102, a first memory 1103, and at least one communication bus 1104. The communication bus 1104 is used to implement communication connections between the elements. The first memory 1103 may include a high-speed RAM memory, and may also include a non-volatile storage NVM, such as at least one disk memory, and the first memory 1103 may store various programs for performing various processing functions and implementing the method steps of the present embodiment.
Alternatively, the first processor 1101 may be, for example, a Central Processing Unit (CPU), an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components, and the first processor 1101 is coupled to the input device 1100 and the output device 1102 through a wired or wireless connection.
Optionally, the input device 1100 may include a variety of input devices, such as at least one of a user-oriented user interface, a device-oriented device interface, a software programmable interface, a camera, and a sensor. Optionally, the device interface facing the device may be a wired interface for data transmission between devices, or may be a hardware plug-in interface (e.g., a USB interface, a serial port, etc.) for data transmission between devices; optionally, the user-facing user interface may be, for example, a user-facing control key, a voice input device for receiving voice input, and a touch sensing device (e.g., a touch screen with a touch sensing function, a touch pad, etc.) for receiving user touch input; optionally, the programmable interface of the software may be, for example, an entry for a user to edit or modify a program, such as an input pin interface or an input interface of a chip; the output devices 1102 may include output devices such as a display, audio, and the like.
In this embodiment, the processor of the terminal device includes a module for executing functions of each module in each device, and specific functions and technical effects may refer to the foregoing embodiments, which are not described herein again.
Fig. 6 is a schematic hardware structure diagram of a terminal device according to an embodiment of the present application. FIG. 6 is a specific embodiment of the implementation of FIG. 5. As shown, the terminal device of the present embodiment may include a second processor 1201 and a second memory 1202.
The second processor 1201 executes the computer program code stored in the second memory 1202 to implement the method described in fig. 1 in the above embodiment.
The second memory 1202 is configured to store various types of data to support operations at the terminal device. Examples of such data include instructions for any application or method operating on the terminal device, such as messages, pictures, videos, and so forth. The second memory 1202 may include a Random Access Memory (RAM) and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.
Optionally, a second processor 1201 is provided in the processing assembly 1200. The terminal device may further include: communication component 1203, power component 1204, multimedia component 1205, speech component 1206, input/output interfaces 1207, and/or sensor component 1208. The specific components included in the terminal device are set according to actual requirements, which is not limited in this embodiment.
The processing component 1200 generally controls the overall operation of the terminal device. The processing assembly 1200 may include one or more second processors 1201 to execute instructions to perform all or part of the steps of the data processing method described above. Further, the processing component 1200 can include one or more modules that facilitate interaction between the processing component 1200 and other components. For example, the processing component 1200 can include a multimedia module to facilitate interaction between the multimedia component 1205 and the processing component 1200.
The power supply component 1204 provides power to the various components of the terminal device. The power components 1204 may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the terminal device.
The multimedia components 1205 include a display screen that provides an output interface between the terminal device and the user. In some embodiments, the display screen may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the display screen includes a touch panel, the display screen may be implemented as a touch screen to receive an input signal from a user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundary of a touch or slide action, but also detect the duration and pressure associated with the touch or slide operation.
The voice component 1206 is configured to output and/or input voice signals. For example, the voice component 1206 includes a Microphone (MIC) configured to receive external voice signals when the terminal device is in an operational mode, such as a voice recognition mode. The received speech signal may further be stored in the second memory 1202 or transmitted via the communication component 1203. In some embodiments, the speech component 1206 further comprises a speaker for outputting speech signals.
The input/output interface 1207 provides an interface between the processing component 1200 and peripheral interface modules, which may be click wheels, buttons, etc. These buttons may include, but are not limited to: a volume button, a start button, and a lock button.
The sensor component 1208 includes one or more sensors for providing various aspects of status assessment for the terminal device. For example, the sensor component 1208 may detect an open/closed state of the terminal device, relative positioning of the components, presence or absence of user contact with the terminal device. The sensor assembly 1208 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact, including detecting the distance between the user and the terminal device. In some embodiments, the sensor assembly 1208 may also include a camera or the like.
The communication component 1203 is configured to facilitate communications between the terminal device and other devices in a wired or wireless manner. The terminal device may access a wireless network based on a communication standard, such as WiFi, 2G or 3G, or a combination thereof. In one embodiment, the terminal device may include a SIM card slot therein for inserting a SIM card therein, so that the terminal device may log onto a GPRS network to establish communication with the server via the internet.
As can be seen from the above, the communication component 1203, the voice component 1206, the input/output interface 1207 and the sensor component 1208 referred to in the embodiment of fig. 6 can be implemented as the input device in the embodiment of fig. 5.
The foregoing embodiments are merely illustrative of the principles and utilities of the present invention and are not intended to limit the invention. Any person skilled in the art can modify or change the above-mentioned embodiments without departing from the spirit and scope of the present invention. Accordingly, it is intended that all equivalent modifications or changes which can be made by those skilled in the art without departing from the spirit and technical spirit of the present invention be covered by the claims of the present invention.
Claims (30)
1. An abnormal object management method, comprising:
acquiring multiple types of images of a detection object;
determining a target detection area of the detection object;
acquiring a detection index of the target detection area;
and judging whether the detection object is an abnormal object or not according to the detection index.
2. The abnormal object management method according to claim 1, wherein the plural types of images include: visible light images, infrared images, laser images.
3. The abnormal object management method according to claim 2, wherein the detection index includes: temperature, blood nucleic acid characteristics.
4. The abnormal object management method according to claim 2, wherein if the image of the detected object includes a visible light image and an infrared image;
detecting a target part of the visible light image to obtain a target part position; determining a target detection area of the target part position in an infrared image of a detection object;
acquiring a detection index of the target detection area of a detection object;
and judging whether the detection object is an abnormal object or not according to the detection index of the target detection area.
5. The abnormal object management method according to claim 2, wherein if the image of the detection object includes a visible light image and a laser image;
detecting a target part of the visible light image to obtain a target part position; determining a target detection area of the target position in a laser image of a detection object;
acquiring a detection index of the target detection area of a detection object;
and judging whether the detection object is an abnormal object or not according to the detection index of the target detection area.
6. The abnormal object management method according to claim 4 or 5, wherein the target part comprises a human face, a hand back, a neck and a shoulder, and the target detection region comprises a human face region, a hand back region, a neck region and a shoulder region.
7. The abnormal object management method according to claim 6, wherein if the detection index is temperature, the detection object is an abnormal object when a temperature of a target detection area of the detection object exceeds a temperature threshold.
8. The abnormal object management method according to claim 6, wherein if the detection index is a blood nucleic acid characteristic, the detection object is an abnormal object when the blood nucleic acid characteristic of the target detection region of the detection object satisfies a predetermined condition.
9. The method of claim 1, further comprising:
and tracking the abnormal object by adopting a face recognition technology or a human body recognition technology.
10. The method of claim 1, further comprising:
and when the abnormal object is detected, sending an alarm prompt.
11. The method of claim 7, wherein if the detection indicator is temperature, the method further comprises:
acquiring an age attribute of a detection object;
and setting temperature thresholds corresponding to different age groups according to different age attributes.
12. The method of claim 7, further comprising:
and compensating the temperature of the target detection area based on the distance between the detection object and the image acquisition device.
13. The method of claim 7, further comprising:
acquiring an ambient temperature;
and compensating the temperature of the target detection area according to the environment temperature.
14. The abnormal object management method according to claim 7, wherein if the target detection area is a face area, the method further comprises:
judging whether the detection object has smoking behavior or not;
and if the smoking behavior exists, shielding the smoking area.
15. An abnormal object management system, comprising:
the image acquisition module is used for acquiring various types of images of the detection object;
a detection area determination module for determining a target detection area of the detection object;
the index detection module is used for acquiring a detection index of the target detection area;
and the abnormity judging module is used for judging whether the detection object is an abnormal object according to the detection index.
16. The abnormal object management system of claim 15, wherein the multiple types of images comprise: visible light images, infrared images, laser images.
17. The abnormal object management system of claim 16, wherein the detection metrics comprise: temperature, blood nucleic acid characteristics.
18. The abnormal object management system of claim 16, wherein if the image of the detected object comprises a visible light image and an infrared image;
detecting a target part of the visible light image to obtain a target part position; determining a target detection area of the target part position in an infrared image of a detection object;
acquiring a detection index of the target detection area of a detection object;
and judging whether the detection object is an abnormal object or not according to the detection index of the target detection area.
19. The abnormal object management system of claim 16, wherein if the image of the detected object comprises a visible light image and a laser image;
detecting a target part of the visible light image to obtain a target part position; determining a target detection area of the target position in a laser image of a detection object;
acquiring a detection index of the target detection area of a detection object;
and judging whether the detection object is an abnormal object or not according to the detection index of the target detection area.
20. The system according to claim 18 or 19, wherein the target portion includes a face, a back of a hand, a neck, and a shoulder, and the target detection region includes a face region, a back of a hand region, a neck region, and a shoulder region.
21. The system according to claim 17, wherein if the detection index is temperature, the detection target is an abnormal target when a temperature of a target detection area of the detection target exceeds a temperature threshold.
22. The system according to claim 17, wherein if the detection index is a blood nucleic acid characteristic, the detection target is an abnormal target when the blood nucleic acid characteristic of the target detection region of the detection target satisfies a predetermined condition.
23. The abnormal object management system of claim 15, further comprising:
and the tracking module is used for tracking the abnormal object by adopting a face recognition technology or a human body recognition technology.
24. The abnormal object management system of claim 15, further comprising:
and the alarm module is used for sending out an alarm prompt when the abnormal object is detected.
25. The system for managing an abnormal object according to claim 21, wherein if the detection index is a temperature, the system further comprises:
the age attribute acquisition module is used for acquiring the age attribute of the detection object;
and the temperature threshold setting module is used for setting temperature thresholds corresponding to different age groups according to different age attributes.
26. The abnormal object management system of claim 21, further comprising:
and the first temperature compensation module is used for compensating the temperature of the target detection area based on the distance between the detection object and the image acquisition device.
27. The system for managing abnormal objects according to claim 21, wherein if the target detection area is a face area, the system further comprises:
the temperature acquisition module is used for acquiring the ambient temperature;
and the second temperature compensation module is used for compensating the temperature of the target detection area according to the environment temperature.
28. The abnormal object management system of claim 21, further comprising:
the smoking judgment module is used for judging whether the detection object has smoking behavior or not;
and the shielding module is used for shielding the smoking area when smoking behavior exists.
29. An apparatus, comprising:
one or more processors; and
one or more machine-readable media having instructions stored thereon that, when executed by the one or more processors, cause the apparatus to perform the method of one or more of claims 1-14.
30. One or more machine-readable media having instructions stored thereon, which when executed by one or more processors, cause an apparatus to perform one or more of the methods recited in claims 1-14.
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| PCT/CN2020/110454 WO2021159682A1 (en) | 2020-02-12 | 2020-08-21 | Abnormal object management method and system, machine-readable medium, and device |
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| CN202010089232.4A CN111202504A (en) | 2020-02-12 | 2020-02-12 | Abnormal object management method, system, machine readable medium and equipment |
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Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111310692A (en) * | 2020-02-25 | 2020-06-19 | 云从科技集团股份有限公司 | Detection object management method, system, machine readable medium and equipment |
| CN111458037A (en) * | 2020-06-08 | 2020-07-28 | 深圳市迪米科技有限公司 | Body temperature screening recording device and body temperature screening processing method |
| CN111695509A (en) * | 2020-06-12 | 2020-09-22 | 云从科技集团股份有限公司 | Identity authentication method, identity authentication device, machine readable medium and equipment |
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| WO2021159682A1 (en) * | 2020-02-12 | 2021-08-19 | 上海云从汇临人工智能科技有限公司 | Abnormal object management method and system, machine-readable medium, and device |
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| WO2021259365A1 (en) * | 2020-06-24 | 2021-12-30 | 杭州海康威视数字技术股份有限公司 | Target temperature measurement method and apparatus, and temperature measurement system |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102147835A (en) * | 2010-11-26 | 2011-08-10 | 中华人民共和国深圳出入境检验检疫局 | Driver body temperature automatic measurement system applied to port lanes and implementation method thereof |
| CN105931254A (en) * | 2016-05-17 | 2016-09-07 | 北京市检验检疫科学技术研究院 | Low-temperature inspection method and system for entry and exit inspection and quarantine of frontier port |
| CN108344525A (en) * | 2018-02-09 | 2018-07-31 | 英华达（上海）科技有限公司 | Adaptive body temperature monitoring method and system |
| CN110411570A (en) * | 2019-06-28 | 2019-11-05 | 武汉高德智感科技有限公司 | Infrared human body temperature screening method based on human testing and human body tracking technology |
Family Cites Families (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110160670A (en) * | 2019-05-05 | 2019-08-23 | 深圳中集智能科技有限公司 | Body temperature detection device |
| CN111202504A (en) * | 2020-02-12 | 2020-05-29 | 上海云从汇临人工智能科技有限公司 | Abnormal object management method, system, machine readable medium and equipment |
| CN111325127A (en) * | 2020-02-12 | 2020-06-23 | 上海云从汇临人工智能科技有限公司 | Abnormal object judgment method, system, machine readable medium and equipment |
-
2020
- 2020-02-12 CN CN202010089232.4A patent/CN111202504A/en not_active Withdrawn
- 2020-08-21 WO PCT/CN2020/110454 patent/WO2021159682A1/en active Application Filing
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102147835A (en) * | 2010-11-26 | 2011-08-10 | 中华人民共和国深圳出入境检验检疫局 | Driver body temperature automatic measurement system applied to port lanes and implementation method thereof |
| CN105931254A (en) * | 2016-05-17 | 2016-09-07 | 北京市检验检疫科学技术研究院 | Low-temperature inspection method and system for entry and exit inspection and quarantine of frontier port |
| CN108344525A (en) * | 2018-02-09 | 2018-07-31 | 英华达（上海）科技有限公司 | Adaptive body temperature monitoring method and system |
| CN110411570A (en) * | 2019-06-28 | 2019-11-05 | 武汉高德智感科技有限公司 | Infrared human body temperature screening method based on human testing and human body tracking technology |
Cited By (12)
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|---|---|---|---|---|
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| WO2021259365A1 (en) * | 2020-06-24 | 2021-12-30 | 杭州海康威视数字技术股份有限公司 | Target temperature measurement method and apparatus, and temperature measurement system |
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| CN117373110A (en) * | 2023-08-30 | 2024-01-09 | 武汉星巡智能科技有限公司 | Visible light-thermal infrared imaging infant behavior recognition method, device and equipment |
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Application publication date: 20200529 |
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