CN113065528A - Embedded visual computing system for face recognition, counting and temperature measurement - Google Patents
Embedded visual computing system for face recognition, counting and temperature measurement Download PDFInfo
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- 230000036760 body temperature Effects 0.000 claims description 15
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- 238000001931 thermography Methods 0.000 claims description 13
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- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/161—Detection; Localisation; Normalisation
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- G—PHYSICS
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- 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
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- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/168—Feature extraction; Face representation
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- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/172—Classification, e.g. identification
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- G01J—MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT, POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRARED, VISIBLE OR ULTRAVIOLET LIGHT; COLORIMETRY; RADIATION PYROMETRY
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Abstract
The invention relates to the technical field of computer vision, in particular to an embedded visual computing system for face recognition, counting and temperature measurement, wherein after edge computing equipment is started, the system is started to operate; initializing a FaceSDK/body SDK algorithm module; the camera stream taking module obtains a video stream from predefined camera information; the video stream is pushed to a video stream algorithm processing module by a single frame in a queue form to be analyzed according to a loading algorithm; the parsed structured result is processed according to business needs and then presented to the user in a visual result form. The invention overcomes the defects of the prior art, and achieves the purpose of solving the business scenes of staff sign-in, visitor welcome, frequent hall and the like through face comparison and deploying the central server at the Internet end or the remote machine room due to adopting an AIOT framework of intelligent edge calculation by setting the applications of face recognition, welcome, frequent hall and the like derived based on face detection and a face comparison algorithm.
Description
Technical Field
The invention relates to the technical field of computer vision, in particular to an embedded visual computing system for face recognition, counting and temperature measurement.
Background
A visual computing system is a multi-level, bottom-up analysis process in which a series of different characterizations of an object are generated that provide more and more detailed information about the visual environment of interest.
The human face recognition temperature measurement system supports body temperature detection and automatic alarm. A thermal imaging crowd temperature measurement module is arranged in the face recognition all-in-one machine, and full-automatic face recognition and body temperature detection are carried out, and thermal imaging images and real-time recognition images are automatically stored. The automatic passing is realized under the condition that the face recognition and the body temperature detection are normal, the equipment gives an alarm in real time when the body temperature is abnormal, and the error is only 0.4 percent within 1 meter after the temperature is judged. In addition, the human face recognition records the temperature of each area of the human body in real time, reports are automatically generated and summarized into attendance and body temperature reports to be output, and the WeChat is automatically pushed to designated management personnel. Under the condition of strictly preventing and controlling epidemic situations, the face recognition temperature measurement system can realize automatic intelligent close control, does not need a specially-assigned person to measure the body temperature, and really achieves quick, accurate and comprehensive detection.
However, the existing visual computing system for face recognition, counting and temperature measurement also has the problems that for a large-flow people stream temperature measurement scene, single-channel equipment such as an entrance guard and a handheld temperature measuring instrument has a low temperature measurement speed, so that a large number of people are gathered, the actual use requirements cannot be met, the face temperature measurement of an Intel X86 framework individual soldier is used offline, the face comparison algorithm is limited, and the face comparison and frequent hall application cannot be performed.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an embedded visual computing system for face recognition, counting and temperature measurement, which overcomes the defects of the prior art, has simple structural design, and effectively solves the problems that a large number of people gather due to the slow temperature measurement speed of single-channel equipment such as an entrance guard, a handheld temperature measuring instrument and the like in a large-flow people stream temperature measurement scene, the actual use requirement cannot be met, the face temperature measurement of a human face with an X86 framework of Intel is used offline, the human face comparison algorithm is limited, and the human face comparison cannot be carried out and the frequent hall application cannot be carried out.
In order to solve the technical problems, the invention provides the following technical scheme:
an embedded visual computing system for face recognition, counting and temperature measurement comprises the following steps:
s1: after the edge computing equipment is started, starting a system to operate;
s2: initializing a FaceSDK/body SDK algorithm module;
s3: the camera stream taking module obtains a video stream from predefined camera information;
s4: the video stream is pushed to a video stream algorithm processing module by a single frame in a queue form to be analyzed according to a loading algorithm;
and S5, the parsed structured result is processed according to business needs and then presented to the user in a visual result form.
As a preferred technical solution of the present invention, in S3, the camera streaming module acquires a video stream from predefined camera information, and if the camera streaming fails, the streaming module makes multiple attempts, and if the camera streaming still fails, the streaming module notifies the application layer in an abnormal form.
As a preferred technical solution of the present invention, after the video stream is successfully acquired in S4, the video stream is decoded, and frame data is queued to be stored in a global processing buffer, the video stream processing task fetches frames from the buffer queue one by one, and performs parsing detection according to a preset number of skipped frames, and screens out a human face and a human body target for the target by a human face and human body detection algorithm, and obtains target structured information; and distributing a global tracking ID face processing flow to the face and the human body through the pre-trained face and human body tracking deep learning model.
As a preferred technical solution of the present invention, in S5, a relatively reliable face image is obtained through a face quality algorithm, and is sent to a face comparison model for feature comparison, and at the same time, a reliable face temperature in an area is taken out from a temperature measurement camera according to a face position, the face comparison model matches a captured face feature with a face prestored in an image library to obtain best matching personnel information, an application layer performs logical judgment of employees, visitors, and strangers according to personnel roles, and a human body structured sequence screened out through a human body tracking model obtains point location information and direction information of a person entering a camera and disappearing to perform hall entrance and exit judgment.
As a preferred technical scheme of the invention, the human body detection technology and the human face detection technology are computer vision technology which judges whether pedestrians exist in an image or a video sequence and provides accurate positioning, can be combined with technologies such as pedestrian tracking, pedestrian re-identification and the like, and are applied to the fields of artificial intelligence systems, vehicle auxiliary driving systems, intelligent robots, intelligent video monitoring, human body behavior analysis, intelligent transportation and the like.
As a preferred technical solution of the present invention, the edge terminal embedded application is a method of processing data in a location physically close to data generation, that is, a field area such as a home and a remote office where things and people are located. An open platform integrating network, computing, storage and application core capabilities provides edge intelligent service nearby, and meets the key requirements of industry digitization on agile connection, real-time service, data optimization, application intelligence, safety, privacy protection and the like.
As a preferred technical solution of the present invention, the intelligent edge computing small station is a concept proposed with respect to a data center, and it means that the behavior of collecting and analyzing data occurs in local devices and networks close to data generation, without transmitting the data to the data center with centralized computing resources for processing. Edge computing is also known as distributed cloud computing, fog computing, or fourth generation data centers.
As a preferred technical scheme of the invention, the infrared thermal imaging temperature measurement is thermal imaging, so that a temperature distribution image can be obtained, namely temperature data of all pictures can be obtained, and even if large-scale people enter a monitoring range of a system at the same time, the body temperature data of all people can be measured at the same time. The detection of the infrared radiation of the human body by thermal imaging is carried out in real time, the body temperature data obtained by the algorithm is more in millisecond unit, the system does not need any stop of people at all when in work, and once the people enter the monitoring range of the equipment, the body temperature data can be immediately measured.
The embodiment of the invention provides an embedded visual computing system for face recognition, counting and temperature measurement, which has the following beneficial effects:
1. by setting the applications of face recognition, welcoming, frequent hall application and the like derived based on face detection and a face comparison algorithm, the purposes that business scenes such as staff sign-in, visitor welcoming, frequent hall application and the like are solved through face comparison and an AIOT framework adopting intelligent edge calculation is adopted, a central server can be deployed at an internet end or a remote machine room are achieved, and the problems that a single soldier can be used offline with a face temperature measurement of an X86 framework of Intel and is limited by the face comparison algorithm, the face comparison cannot be carried out and the frequent hall application cannot be carried out are solved.
2. Through setting up and based on face detection, the application of thermal imaging temperature measurement camera derived face temperature measurement, reached and carried out the temperature measurement through the mode that face detection locking thermal imaging region, very big quickening the temperature measurement process, avoid people to flow to gather and detect, the recognition algorithm is with embedded integrated operation on edge calculation terminals such as intelligent edge calculation little station, with the purpose that alleviates the calculation pressure of center end calculation server and the bandwidth pressure of video transmission, solved to large-traffic people flow temperature measurement scene, entrance guard, single channel equipment such as handheld thermoscope temperature measurement speed is slower, lead to personnel to gather in a large number, can't satisfy the problem that the in-service use needs.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic view of a human face and body tracking process flow of the present invention;
FIG. 2 is a schematic diagram of a business process overall flow structure according to the present invention;
FIG. 3 is a schematic view of the face processing flow structure of the present invention;
fig. 4 is a schematic view of the structure of the face processing flow of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
Example (b): as shown in fig. 1-4, an embedded visual computing system for face recognition, counting and temperature measurement comprises the following steps:
s1: after the edge computing equipment is started, starting a system to operate;
s2: initializing a FaceSDK/body SDK algorithm module;
s3: the camera stream taking module obtains a video stream from predefined camera information;
s4: the video stream is pushed to a video stream algorithm processing module by a single frame in a queue form to be analyzed according to a loading algorithm;
and S5, the parsed structured result is processed according to business needs and then presented to the user in a visual result form.
In S3, the camera fetching module obtains the video stream from the predefined camera information, and if the camera fetching fails, the camera fetching module will make multiple attempts, and if the camera fetching still fails, the camera fetching module will notify the application layer in an abnormal form.
After the video stream is successfully acquired in the step S4, the video stream is decoded, the frame data are stored in a global processing buffer in a queue, the video stream processing task fetches frames from the buffer queue one by one, and performs analysis and detection according to a preset frame skipping number, and a human face and a human body target are screened out from the target through a human face and human body detection algorithm, and target structural information is obtained; and distributing a global tracking ID face processing flow to the face and the human body through the pre-trained face and human body tracking deep learning model.
In the step S5, a relatively reliable face image is obtained through a face quality algorithm, the face image is sent to a face comparison model for feature comparison, meanwhile, the reliable face temperature in the area is taken out from a temperature measuring camera according to the face position, the face comparison model matches the captured face features with the face stored in an image library in advance to obtain the best matched personnel information, the application layer performs logic judgment of staff, visitors and strangers according to personnel roles, and the person structural sequence selected through the human body tracking model obtains the point location information and the direction information of the person entering a lens and disappearing to perform judgment of the person entering a hall.
The human body detection technology and the human face detection technology are used for judging whether pedestrians exist in an image or a video sequence and accurately positioning the pedestrians by the computer vision technology, can be combined with technologies such as pedestrian tracking and pedestrian re-identification, and are applied to the fields of artificial intelligence systems, vehicle auxiliary driving systems, intelligent robots, intelligent video monitoring, human body behavior analysis, intelligent transportation and the like.
Among them, the edge terminal embedded application is a method of processing data in a physically close location to data generation, i.e., a field area such as a home and a remote office where things and people are located. An open platform integrating network, computing, storage and application core capabilities provides edge intelligent service nearby, and meets the key requirements of industry digitization on agile connection, real-time service, data optimization, application intelligence, safety, privacy protection and the like.
The intelligent edge computing small station is a concept put forward relative to a data center, and means that actions of collecting and analyzing data occur in local equipment and a network close to data generation without transmitting the data to the data center with centralized computing resources for processing. Edge computing is also known as distributed cloud computing, fog computing, or fourth generation data centers.
The infrared thermal imaging temperature measurement can acquire a temperature distribution image for thermal imaging, namely can acquire temperature data of all pictures, so that even if large-scale people enter a monitoring range of the system at the same time, the body temperature data of all people can be measured at the same time. The detection of the infrared radiation of the human body by thermal imaging is carried out in real time, the body temperature data obtained by the algorithm is more in millisecond unit, the system does not need any stop of people at all when in work, and once the people enter the monitoring range of the equipment, the body temperature data can be immediately measured.
Finally, it should be noted that: in the description of the present invention, it should be noted that the terms "vertical", "upper", "lower", "horizontal", and the like indicate orientations or positional relationships based on those shown in the drawings, and are only for convenience of describing the present invention and simplifying the description, but do not indicate or imply that the referred device or element must have a specific orientation, be constructed in a specific orientation, and be operated, and thus, should not be construed as limiting the present invention.
In the description of the present invention, it should also be noted that, unless otherwise explicitly specified or limited, the terms "disposed," "mounted," "connected," and "connected" are to be construed broadly and may, for example, be fixedly connected, detachably connected, or integrally connected; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood by those skilled in the art according to specific situations.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (8)
1. An embedded visual computing system for face recognition, counting and temperature measurement comprises the following steps:
s1: after the edge computing equipment is started, starting a system to operate;
s2: initializing a FaceSDK/body SDK algorithm module;
s3: the camera stream taking module obtains a video stream from predefined camera information;
s4: the video stream is pushed to a video stream algorithm processing module by a single frame in a queue form to be analyzed according to a loading algorithm;
and S5, the parsed structured result is processed according to business needs and then presented to the user in a visual result form.
2. The embedded visual computing system for face recognition, counting and temperature measurement as claimed in claim 1, wherein the camera fetching module in S3 obtains a video stream from predefined camera information, and if the camera fetching fails, the fetching module makes multiple attempts, and if the camera fetching still fails, the fetching module informs the application layer in an abnormal form.
3. The embedded visual computing system for face recognition, counting and temperature measurement according to claim 1, wherein after the video stream is successfully acquired in S4, the video stream is decoded and the frame data is stored in a global processing buffer in a queue, the video stream processing task fetches frames from the buffer queue one by one, and performs parsing detection according to a preset number of skipped frames, and screens out the face and body targets from the targets through a face and body detection algorithm, and obtains target structural information; and distributing a global tracking ID face processing flow to the face and the human body through the pre-trained face and human body tracking deep learning model.
4. The embedded visual computing system for face recognition, counting and temperature measurement as claimed in claim 1, wherein in S5, a relatively reliable face image is obtained through a face quality algorithm, and sent to a face comparison model for feature comparison, and at the same time, a reliable face temperature in an area is taken out from a temperature measurement camera according to a face position, the face comparison model matches the captured face features with a prestored image library for face matching, so as to obtain best matching personnel information, the application layer performs logical judgment of employees, visitors and strangers according to personnel roles, and obtains point location information and orientation information of a person entering a lens and disappearing through a human body structured sequence screened by a human body tracking model, so as to perform human body entrance and exit judgment.
5. The embedded visual computing system for face recognition, counting and temperature measurement according to claim 3, wherein the human body detection technology and the face detection technology are computer vision technologies for judging whether pedestrians exist in images or video sequences and providing accurate positioning, and the technology can be combined with technologies such as pedestrian tracking and pedestrian re-recognition, and is applied to the fields of artificial intelligence systems, vehicle-assisted driving systems, intelligent robots, intelligent video monitoring, human behavior analysis, intelligent transportation and the like.
6. An embedded face recognition, counting, thermometry vision computing system according to claim 1, where the edge-terminal embedded application is a method of processing data physically close to the location where the data is generated, i.e. the field area where things and people are located such as in homes and remote offices; an open platform integrating network, computing, storage and application core capabilities provides edge intelligent service nearby, and meets the key requirements of industry digitization on agile connection, real-time service, data optimization, application intelligence, safety, privacy protection and the like.
7. The embedded visual computing system for face recognition, counting and temperature measurement as claimed in claim 1, wherein the intelligent edge computing small station is a concept proposed with respect to a data center, which means that the behavior of collecting and analyzing data occurs in local devices and networks near data generation without transmitting the data to the data center with centralized computing resources for processing; edge computing is also known as distributed cloud computing, fog computing, or fourth generation data centers.
8. The embedded visual computing system for face recognition, counting and temperature measurement according to claim 1, wherein the infrared thermal imaging temperature measurement is thermal imaging capable of acquiring a temperature distribution image, that is, capable of acquiring temperature data of all one screen, so that even if a large number of people enter a monitoring range of the system at the same time, body temperature data of all people can be measured at the same time; the detection of the infrared radiation of the human body by thermal imaging is carried out in real time, the body temperature data obtained by the algorithm is more in millisecond unit, the system does not need any stop of people at all when in work, and once the people enter the monitoring range of the equipment, the body temperature data can be immediately measured.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113823027A (en) * | 2021-09-09 | 2021-12-21 | 浙江慧享信息科技有限公司 | Intelligent non-inductive passing control system |
| CN113902968A (en) * | 2021-12-09 | 2022-01-07 | 中国人民解放军总医院 | Face recognition system based on edge calculation framework |
| CN114884842A (en) * | 2022-04-13 | 2022-08-09 | 哈工大机器人（合肥）国际创新研究院 | Visual security detection system and method for dynamically configuring tasks |
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