CN115830294A - Identification method and device applied to personnel management and control in infrastructure construction operation field - Google Patents
Identification method and device applied to personnel management and control in infrastructure construction operation field Download PDFInfo
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- CN115830294A CN115830294A CN202211429160.9A CN202211429160A CN115830294A CN 115830294 A CN115830294 A CN 115830294A CN 202211429160 A CN202211429160 A CN 202211429160A CN 115830294 A CN115830294 A CN 115830294A
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Abstract
The invention discloses an identification method and device applied to personnel management and control in a capital construction operation field, which comprises the steps of collecting images of personnel in a real-time operation field through a monitoring camera; identifying and positioning the face position and behavior action of the person in the current image through a target detection algorithm; extracting a face image, and performing super-resolution reconstruction when the face image is smaller than a preset value; and inputting the image after super-resolution reconstruction into a classification network for fine identification, and outputting an identification result. The invention can analyze the personnel behaviors in real time, alarm the violation behaviors of the personnel in time, ensure the safety of operation and construction, and solve the problems of untimely safety control, incapability of mastering the personnel state and low quality and efficiency of the safety management of a working responsible person on an operation site in the existing infrastructure scene.
Description
Technical Field
The invention relates to the technical field of intelligent identification, in particular to an identification method and device applied to personnel management and control in a capital construction operation field.
Background
At present, the personnel safety control requirements with high safety level are required in the aspects of infrastructure construction, intelligent marketing, field operation, information communication, intelligent logistics, safety supervision guarantee and the like, for example, in the aspect of infrastructure construction, the field management of power grid infrastructure projects at the present stage has insufficient constraint force on people, the management on personnel identity safety is lacked, the identity information of constructors is unclear, and people with different employment can not be accurately positioned when safety problems occur in the power construction process; in the aspect of intelligent logistics, the current safety control of power grid logistics personnel mainly adopts a manual registration mode, materials such as personnel working certificates and the like are manually checked one by one, the efficiency is low, whether certificate holders and certificates are integrated into one can not be accurately distinguished, a great potential safety hazard exists, and illegal personnel information can not be quickly positioned when safety problems occur; in the aspect of safety supervision, the identity of a person needs to be checked during power conservation, real-person real-name verification is realized, the identity of the power conservation person is mainly checked manually at present, the workload is large, and the efficiency is low; meanwhile, in key areas such as a transformer substation, a core machine room, a command center and mobile inspection, a post needs to be in place and a person needs to be in place during power conservation.
Disclosure of Invention
This section is for the purpose of summarizing some aspects of embodiments of the invention and to briefly introduce some preferred embodiments. In this section, as well as in the abstract and the title of the invention of this application, simplifications or omissions may be made to avoid obscuring the purpose of the section, the abstract and the title, and such simplifications or omissions are not intended to limit the scope of the invention.
The invention is provided in view of the above and/or the existing infrastructure scene for the problem that the safety control is not timely, the personnel state can not be mastered, and the quality of the safety management of the working responsible person on the working site is not high.
The problem to be solved by the invention is therefore how to identify and analyze persons in real time.
In order to solve the technical problems, the invention provides the following technical scheme:
in a first aspect, an embodiment of the present invention provides an identification method applied to personnel management and control in a infrastructure construction job site, which includes,
collecting real-time operation site personnel images through a monitoring camera;
identifying and positioning the face position and behavior action of the person in the current image through a target detection algorithm;
extracting a face image, and performing super-resolution reconstruction when the face image is smaller than a preset value;
and inputting the super-resolution reconstructed image into a classification network for fine identification, and outputting personnel information.
As an optimal solution of the identification method applied to personnel management and control in the infrastructure construction work site, the method comprises the following steps: the acquisition of the real-time operation site personnel images through the monitoring camera comprises,
the images are decimated from the video stream or camera SDK and scaled to 640x 640.
As an optimal solution of the identification method applied to personnel management and control in the infrastructure construction work site, the method comprises the following steps: the position of the face of the person in the current image is identified and positioned through a target detection algorithm, the behavior action comprises,
detecting whether a face exists in the picture;
processing the extracted face to enhance the face features;
extracting key features of the face information;
and matching the input face with the faces in the database, finding out the face image with the minimum distance, and verifying the matching degree.
As an optimal solution of the identification method applied to personnel management and control in the infrastructure construction work site, the method comprises the following steps: when the facial image is less than a preset value, the super-resolution reconstruction is carried out,
if the extracted facial image pixels are larger than 112 × 112 pixels, the extracted facial image pixels are directly adjusted to 224 × 224 in equal proportion and then sent to a classifier for recognition;
if the extracted face image pixels are smaller than 112 × 112 pixels, super-resolution reconstruction is performed on the image, the target size is 224 × 224, and then recognition is performed.
As an optimal solution of the identification method applied to personnel management and control in the infrastructure construction work site, the method comprises the following steps: the image after super-resolution reconstruction is input into a classification network for refined identification, the output personnel information comprises,
extracting the characteristic vectors by adopting a neural network, and calculating the maximum normalized autocorrelation coefficients of the extracted characteristic vectors and all the characteristic vectors in the negative sample characteristic library:
γ max ＝max(γ k )k＝1,2,...,N
wherein, V k For the kth feature vector, V, in the sample library T For extracting the obtained feature directionAmount of the compound (A).
As an optimal solution of the identification method applied to personnel management and control in the infrastructure construction work site, the method comprises the following steps: the image after super-resolution reconstruction is input into a classification network for refined identification, the output personnel information comprises,
when gamma is equal to max If the detection result is more than 0.9, the detection result is considered as a negative sample false alarm, and the result is not output;
otherwise, the detection result is considered to be correct detection, and the detection result is output.
As an optimal solution of the identification method applied to personnel management and control in the infrastructure construction work site, the method comprises the following steps: the outputting of the recognition result includes outputting,
when the extracted face image does not match the database, identifying as a foreign person and issuing a warning;
when the extracted facial image is matched with the database, generating personnel track information according to the result of face recognition, and comparing the personnel track information with an allowable track;
and when the personnel track information exceeds the movable range, recognizing the personnel track information as an out-of-range intrusion, and alarming until the personnel track enters the allowable range again.
In a second aspect, an embodiment of the present invention provides an identification system for personnel management and control in a infrastructure construction work site, including:
the image acquisition module is used for acquiring real-time operation site personnel images through the monitoring camera;
the target detection module is used for identifying and positioning the face position and the behavior action of the person in the current image through a target detection algorithm;
the image reconstruction module is used for extracting a face image and performing super-resolution reconstruction when the face image is smaller than a preset value;
the personnel identification module is used for inputting the image after the super-resolution reconstruction into a classification network for fine identification and outputting an identification result
In a third aspect, an embodiment of the present invention provides a computer device, including a memory and a processor, where the memory stores a computer program, and where: the processor, when executing the computer program, performs any of the steps of the above-described method.
In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, wherein: which when executed by a processor performs any of the steps of the above-described method.
The invention has the beneficial effects that: the behavior violation detection algorithm based on super-resolution reconstruction is provided, and the small target image is reconstructed by adopting the image super-resolution reconstruction algorithm, so that the false alarm phenomenon in the algorithm can be reduced, and the recall rate and accuracy of the algorithm to personnel identification in the infrastructure site are improved; analyzing the head images of the operating personnel acquired in real time by using a human face detection algorithm, detecting whether non-reporting work enters the site or not, and giving an alarm for the intrusion of illegal personnel in time when the non-reporting work exists; the system can analyze the personnel behaviors in real time, and alarm the violation behaviors of the personnel in time, thereby ensuring the safety of operation and construction, and solving the problems that the safety control is not timely, the personnel state cannot be mastered and the quality of the safety management of a working responsible person on an operation site is not high under the existing infrastructure scene; the system realizes real-time management and control on the site operation state, the personnel operation behavior and the safe civilized construction, intelligently evaluates the early preparation process of the site operation, establishes a digital evaluation file, and comprehensively improves the management and control efficiency of the safety production and the lean management level of the construction operation.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings based on these drawings without inventive exercise. Wherein:
fig. 1 is a flowchart of an identification method applied to personnel management and control in a infrastructure construction work site.
Detailed Description
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, specific embodiments accompanied with figures are described in detail below, and it is apparent that the described embodiments are a part of the embodiments of the present invention, not all of the embodiments. All other embodiments, which can be obtained by a person skilled in the art without making creative efforts based on the embodiments of the present invention, shall fall within the protection scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways than those specifically described and will be readily apparent to those of ordinary skill in the art without departing from the spirit of the present invention, and therefore the present invention is not limited to the specific embodiments disclosed below.
Furthermore, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
The present invention will be described in detail with reference to the drawings, wherein the cross-sectional views illustrating the structure of the device are not enlarged partially in general scale for convenience of illustration, and the drawings are only exemplary and should not be construed as limiting the scope of the present invention. In addition, the three-dimensional dimensions of length, width and depth should be included in the actual fabrication.
Meanwhile, in the description of the present invention, it should be noted that the terms "upper, lower, inner and outer" and the like indicate orientations or positional relationships based on the orientations or positional relationships 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 operate, and thus, cannot be construed as limiting the present invention. Furthermore, the terms first, second, or third are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
The terms "mounted, connected and connected" in the present invention are to be understood broadly, unless otherwise explicitly specified or limited, for example: can be fixedly connected, detachably connected or integrally connected; they may be mechanically, electrically, or directly connected, or indirectly connected through intervening media, or may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Example 1
Referring to fig. 1, a first embodiment of the present invention provides an identification method applied to personnel management and control in a infrastructure construction job site, including:
s100: and acquiring the images of the personnel on the operation site in real time through a monitoring camera.
It should be noted that, the images are obtained by frame extraction from the video stream or the camera SDK, and the formats of the images collected on site are all in a JPG picture format, and are scaled to 640 × 640.
S200: and identifying and positioning the face position and behavior action of the person in the current image through a target detection algorithm.
The target detection algorithm adopts a YooloX detection algorithm, and detects the image acquired on site to obtain the position of the face image in the picture, and the specific steps comprise:
detecting and positioning a human face, and detecting whether the human face exists in the picture;
image preprocessing, namely processing the extracted face to enhance the face characteristics, wherein the method comprises gray level conversion, image correction, sharpening, smooth geometric correction and the like;
extracting human face features, namely extracting key features of human face information, wherein the main methods comprise human face geometric features, feature face and template matching and the like;
and face recognition, namely matching the input face with the face in the database, finding out a face image with the minimum distance, and verifying the matching degree.
It should be noted that the information recorded in the database includes personnel information, security qualification, classification authority, security history, violation record, and the like.
S300: and extracting a face image, and when the face image is smaller than 112 pixels, performing super-resolution reconstruction until the image size is 224 pixels.
It should be noted that, at present, field management mostly uses lenses with small millimeter number, and the coverage of point locations is not comprehensive, and key details cannot be mastered. If a large scene and no dead angle coverage are pursued, the problem that the detail definition and the global control degree cannot be balanced is inevitably caused, only the general situation and the actions of a human body can be observed through a large scene monitoring camera, but the monitoring details and the human face detail characteristics of a key area cannot be seen clearly, so that a lot of inconvenience is brought to video analysis and personnel identification, therefore, a super-resolution reconstruction technology is adopted to reconstruct a low-resolution image, a corresponding high-resolution image is restored through a specific algorithm, a clearer human body area image is obtained, the false alarm phenomenon in the algorithm is reduced, and the recall rate and the accuracy rate of the algorithm to the personnel identification of a capital construction site are improved.
Specifically, if the extracted facial image pixels are larger than 112 × 112 pixels, the extracted facial image pixels are directly adjusted to 224 × 224 in equal proportion and then sent to a classifier for identification;
otherwise, performing super-resolution reconstruction on the image by adopting a BasicVSR + + algorithm, wherein the target size is 224 × 224, and then identifying.
S400: and inputting the super-resolution reconstructed image into a classification network for fine recognition, and outputting a recognition result.
It should be noted that the ShuffleNet V2 neural network is used to extract the feature vector and calculate the maximum normalized autocorrelation coefficient of this feature vector with all feature vectors in the negative sample feature library:
γ max ＝max(γ k )k＝1,2,...,N
wherein, V k For the kth feature vector in the sample library, V T The obtained feature vectors are extracted.
If gamma is max Greater than 0.9, this detection junction is consideredIf the result is a negative sample false alarm, the result output is not carried out; otherwise, the detection result is considered to be correct detection, and the detection result is output.
Further, when the extracted face image does not match the database, it is recognized as an alien person, and a warning is issued;
when the extracted facial image is matched with the database, generating personnel track information according to the result of face recognition, and comparing the personnel track information with an allowable track;
and when the personnel track information exceeds the movable range, recognizing the personnel track information as an out-of-range intrusion, and alarming until the personnel track enters the allowable range again.
Further, this embodiment still provides an identification system who is applied to capital construction operation field personnel management and control, includes:
the image acquisition module is used for acquiring real-time operation field personnel images through the monitoring camera;
the target detection module is used for identifying and positioning the face position and behavior action of the person in the current image through a target detection algorithm;
the image reconstruction module is used for extracting a face image and performing super-resolution reconstruction when the face image is smaller than a preset value;
and the personnel identification module is used for inputting the image after super-resolution reconstruction into a classification network for fine identification and outputting an identification result.
The embodiment further provides a computer device, which is suitable for the identification method applied to personnel management and control in the infrastructure construction job site, and includes:
a memory and a processor; the memory is used for storing computer executable instructions, and the processor is used for executing the computer executable instructions to realize the identification method applied to personnel management and control of the capital construction operation field.
The computer device may be a terminal comprising a processor, a memory, a communication interface, a display screen and an input means connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program to run on the non-volatile storage medium. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless communication can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, a key, a track ball or a touch pad arranged on the shell of the computer equipment, an external keyboard, a touch pad or a mouse and the like.
The present embodiment also provides a storage medium on which a computer program is stored, which when executed by a processor implements the identification method applied to the personnel management and control of the infrastructure job site as set forth in the above embodiments.
The storage medium proposed by the present embodiment belongs to the same inventive concept as the data storage method proposed by the above embodiments, and technical details that are not described in detail in the present embodiment can be referred to the above embodiments, and the present embodiment has the same beneficial effects as the above embodiments.
Example 2
Referring to fig. 1, a second embodiment of the present invention provides an identification method applied to personnel management and control of a infrastructure construction job site.
It should be noted that the detection algorithm in this embodiment adopts a yoolox detection algorithm, the super-resolution reconstruction uses a BasicVSR + + algorithm, and the deep learning framework adopts a PyTorch framework developed by FaceBook corporation. The pictures collected on site are all in JPG picture format, the resolution of the detected pictures is 640x 640, the environment for model deployment is Ubuntu 18.04LTS, and the hardware platform for reasoning test is a Getforce RTX series display card developed by Nvidia.
To further verify the effectiveness of the method of the present invention, a field installation test was performed, and the results are shown in table 1.
Table 1 statistical table of validity test results
| Item | Number of occurrences | Number of warnings | Number of false alarms | Accuracy (%) |
| Face recognition | 10 | 0 | 0 | 100 |
| Safety perimeter | 8 | 7 | 1 | 87.5 |
| Trajectory of persons | 10 | 0 | 0 | 100 |
| Break-in over border | 5 | 5 | 0 | 100 |
| Safety protection | 15 | 11 | 2 | 60 |
As can be seen from the above table, the overall effective rate of the method is at a high level, the specific situation of the site can be effectively monitored, the site operator is reminded under the AI identification condition, and the specific behavior of the site operator is recorded through background data. Meanwhile, the method has difference in performance on different indexes. The face recognition, the personnel track and the cross-border intrusion AI recognition effect are optimal, and false alarm does not occur on the basis of effective recognition. The system can realize real-time management and control on the site operation state, the personnel operation behavior and the safe civilized construction, intelligently evaluate the early preparation process of the site operation, establish a digital evaluation archive, and comprehensively improve the management and control efficiency of the safety production and the lean management level of the construction operation.
It should be noted that the above-mentioned embodiments are only for illustrating the technical solutions of the present invention and not for limiting, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made on the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, which should be covered by the claims of the present invention.
Claims (10)
1. An identification method applied to personnel management and control of a capital construction operation field is characterized in that: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
collecting real-time operation site personnel images through a monitoring camera;
identifying and positioning the face position and behavior action of the person in the current image through a target detection algorithm;
extracting a face image, and performing super-resolution reconstruction when the face image is smaller than a preset value;
and inputting the super-resolution reconstructed image into a classification network for fine recognition, and outputting a recognition result.
2. An identification method applied to personnel management and control of a construction work site according to claim 1, characterized in that: the acquisition of the real-time operation site personnel images through the monitoring camera comprises,
the images are decimated from the video stream or camera SDK and scaled to 640x 640.
3. An identification method applied to personnel management and control of a construction work site according to claim 2, characterized in that: the position of the face of the person in the current image is identified and positioned through a target detection algorithm, the behavior action comprises,
detecting whether a face exists in the picture;
processing the extracted human face to enhance the human face characteristics;
extracting key features of the face information;
and matching the input human face with the human face in the database, finding out the human face image with the minimum distance, and verifying the matching degree.
4. An identification method applied to personnel management and control of a construction work site according to claim 3, characterized in that: when the facial image is less than a preset value, the super-resolution reconstruction is carried out,
if the extracted facial image pixels are larger than 112 × 112 pixels, the extracted facial image pixels are directly adjusted to 224 × 224 in equal proportion and then sent to a classifier for recognition;
if the extracted face image pixels are smaller than 112 × 112 pixels, super-resolution reconstruction is performed on the image, the target size is 224 × 224, and then recognition is performed.
5. An identification method applied to personnel management and control of a construction work site according to claim 4, characterized in that: the inputting of the super-resolution reconstructed image into a classification network for fine recognition comprises,
extracting the characteristic vectors by adopting a neural network, and calculating the maximum normalized autocorrelation coefficients of the extracted characteristic vectors and all the characteristic vectors in the negative sample characteristic library:
γ max ＝max(γ k )k＝1,2,...,N
wherein, V k For the kth feature vector in the sample library, V T The obtained feature vector is extracted.
6. An identification method applied to personnel management and control of a construction work site according to claim 5, characterized in that: inputting the super-resolution reconstructed image into a classification network for fine identification,
when gamma is equal to max If the detection result is more than 0.9, the detection result is regarded as a negative sample false alarm, and the result is not output;
otherwise, the detection result is considered to be correct detection, and the detection result is output.
7. An identification method applied to personnel management and control of a construction work site according to claim 6, characterized in that: the outputting of the recognition result includes outputting,
when the extracted face image does not match the database, identifying the face image as an external person and sending a warning;
when the extracted facial image is matched with the database, generating personnel track information according to the result of face recognition, and comparing the personnel track information with an allowable track;
and when the personnel track information exceeds the movable range, recognizing the personnel track information as an out-of-range intrusion, and alarming until the personnel track enters the allowable range again.
8. An identification system applied to personnel management and control of a capital construction operation field is based on the identification method applied to personnel management and control of the capital construction operation field of claims 1 to 7, and is characterized in that: comprises the steps of (a) preparing a mixture of a plurality of raw materials,
the image acquisition module is used for acquiring real-time operation site personnel images through the monitoring camera;
the target detection module is used for identifying and positioning the face position and behavior action of the person in the current image through a target detection algorithm;
the image reconstruction module is used for extracting a face image and performing super-resolution reconstruction when the face image is smaller than a preset value;
and the personnel identification module is used for inputting the image after super-resolution reconstruction into a classification network for fine identification and outputting an identification result.
9. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that: the processor, when executing the computer program, performs the steps of the method of any one of claims 1 to 7.
10. A computer-readable storage medium having stored thereon a computer program, characterized in that: the computer program, when executed by a processor, implements the steps of the method of any one of claims 1 to 7.
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| CN117576764B (en) * | 2024-01-15 | 2024-04-16 | 四川大学 | Video irrelevant person automatic identification method based on multi-target tracking |
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