CN114581959A - Work clothes wearing detection method based on clothes style feature extraction - Google Patents

Work clothes wearing detection method based on clothes style feature extraction Download PDF

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CN114581959A
CN114581959A CN202210496533.8A CN202210496533A CN114581959A CN 114581959 A CN114581959 A CN 114581959A CN 202210496533 A CN202210496533 A CN 202210496533A CN 114581959 A CN114581959 A CN 114581959A
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image
person
clothes
wearing
extracting
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王三明
王聪明
云尧
胡小敏
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Qiye Cloud Big Data Nanjing Co ltd
Nanjing Anyuan Technology Co ltd
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Qiye Cloud Big Data Nanjing Co ltd
Nanjing Anyuan Technology Co ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/10—Segmentation; Edge detection
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/70—Determining position or orientation of objects or cameras
    • G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
    • G—PHYSICS
    • G08—SIGNALLING
    • G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
    • G08B21/18—Status alarms
    • G08B21/24—Reminder alarms, e.g. anti-loss alarms
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/10—Image acquisition modality
    • G06T2207/10016—Video; Image sequence
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/20—Special algorithmic details
    • G06T2207/20112—Image segmentation details
    • G06T2207/20132—Image cropping
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/30—Computing systems specially adapted for manufacturing

Abstract

The invention discloses a method for detecting wearing of an industrial garment based on garment style feature extraction, which comprises the following steps: extracting key points of a human body, detecting a person target, recording a work clothes library, extracting features of the work clothes library, extracting features of person clothes in a video stream picture, comparing the features, and triggering an alarm. The method does not need to manually construct the features, effectively reduces the occurrence of false alarm and false alarm situations of a manual feature extraction method, realizes the detection work of wearing of the personnel and the clothing in a video stream picture, greatly improves the online efficiency of a scene model of the clothing, and is suitable for the detection of the clothing of different styles.

Description

Work clothes wearing detection method based on clothes style feature extraction
Technical Field
The invention belongs to the technical field of image recognition, and particularly relates to a method for detecting wearing of an industrial garment.
Background
In industrial production, the wearing of worker's clothes can bring a great deal of benefit for the enterprise, not only to the culture of enterprise, image and even cohesion, can promote the popularity of enterprise even to a certain extent, improve market competition, and to having special needs in the operating environment, labourers should be according to relevant danger, customize the work clothes that correspond safeguard function, common function has fire prevention, waterproof, prevent wind, dustproof, protect against radiation, prevent static, anti-oxidation, prevent high temperature, prevent low temperature etc. in order to avoid arousing the occurence of failure or injure them. The problem that needs to be solved urgently in industrial production management is to realize the correct wearing of industrial clothes. The wearing of the artificial monitoring work clothes consumes a large amount of manpower, so the labor input is greatly reduced based on the method for monitoring whether the work clothes are worn correctly or not by the intelligent video. The existing model algorithm solution usually needs to collect a large amount of image data in a production environment to carry out customized training of a worker's clothes model, and due to customization and lack of mobility, the scheme cannot realize rapid online of a system model when a new worker's clothes model is met in a new production environment. Therefore, the method for detecting the wearing of the industrial clothes by extracting the features of the clothes style not only meets the requirement of accuracy, but also can adapt to the rapid detection of wearing of different industrial clothes styles.
Disclosure of Invention
The invention aims to provide a method for detecting wearing of an industrial garment based on garment style feature extraction, which aims to solve the problem that the prior art cannot adapt to quick detection of wearing of different types of industrial garments.
In order to achieve the purpose, the invention adopts the following technical scheme:
a method for detecting wearing of an industrial garment based on garment style feature extraction comprises the following steps:
(1) extracting key points of a human body: extracting human key points from all the people in the image by a human key point extraction method, wherein if all the key points of one person are extracted, the target mark of the person is 1, and if not, the target mark is 0;
(2) detecting a person target: identifying a personnel target in the image through a target detection algorithm, and returning the position information of a circumscribed rectangular frame of the personnel target;
(3) recording a work service library: when a bottom library is manufactured for a certain style of work clothes, only one person in a camera collecting picture is ensured, an image of the work clothes correctly worn by the person is collected in the camera picture, whether all key points of the person are in the image is judged by adopting a human body key point extraction method, if the image is stored in the bottom library of the style work clothes, the image of the angle is collected again if the key points are not in the image;
(4) extracting the characteristics of the work service library: cutting out the image of the personnel part in the image by a target detection algorithm, cutting out personnel image pieces, extracting personnel clothing characteristics in the image pieces
Figure 752371DEST_PATH_IMAGE001
The base library of each work clothing style generates three feature vectors:
Figure 958093DEST_PATH_IMAGE002
wherein
Figure 839462DEST_PATH_IMAGE003
；
(5) Extracting clothing features of people with video streaming pictures: using a target detection algorithm, cutting an image of a person part in the image according to a person detection frame to obtain a person image sheet, extracting person key points in the image sheet by using a human body key point extraction method, and judging whether the whole body part of the person is in the image sheet; let the number of image slices satisfying the condition that the whole body part of the person is within the image slice beNThen extract the first
Figure 601881DEST_PATH_IMAGE004
The individual image pieces are characterized in that
Figure 108DEST_PATH_IMAGE005
In which
Figure 861885DEST_PATH_IMAGE006
And is
Figure 230549DEST_PATH_IMAGE007
；
(6) And (3) feature comparison: if in step (5)
Figure 780348DEST_PATH_IMAGE008
Namely, the condition that the whole body part of a person is in the image slice is not contained in the intercepted video frame picture, and the analysis of the video frame is skipped; if it is
Figure 550858DEST_PATH_IMAGE009
For the second in the video stream picture in step (5)
Figure 583536DEST_PATH_IMAGE004
Corresponding feature extracted from personal image slice
Figure 190229DEST_PATH_IMAGE005
Respectively with feature vectors
Figure 28872DEST_PATH_IMAGE002
Using the Euclidean distance between
Figure 388309DEST_PATH_IMAGE010
In which
Figure 919785DEST_PATH_IMAGE011
Wherein
Figure 449992DEST_PATH_IMAGE002
Express the first in the work clothes base
Figure 92326DEST_PATH_IMAGE012
The feature vectors of the individual person-image slices,
Figure 571849DEST_PATH_IMAGE005
representing the first in a video frame
Figure 22029DEST_PATH_IMAGE004
Feature vectors of individual person image patches;
Figure 587002DEST_PATH_IMAGE013
representing feature vectors
Figure 970710DEST_PATH_IMAGE002
To (1) a
Figure 554007DEST_PATH_IMAGE014
The number of the elements is one,
Figure 161706DEST_PATH_IMAGE015
representing feature vectors
Figure 479555DEST_PATH_IMAGE005
To (1) a
Figure 198112DEST_PATH_IMAGE014
An element;
Figure 402960DEST_PATH_IMAGE016
，
Figure 384822DEST_PATH_IMAGE017
and is
Figure 924388DEST_PATH_IMAGE018
，
Figure 961483DEST_PATH_IMAGE019
Representing feature vectors
Figure 270104DEST_PATH_IMAGE002
And
Figure 219606DEST_PATH_IMAGE005
dimension of (d); mapping the distance between two characteristic vectors, and judging the second time according to a set threshold value
Figure 980888DEST_PATH_IMAGE004
Whether the person in the individual image patch is wearing the frock correctly;
(7) and (3) alarm triggering: and if any characteristic score in the video streaming picture is higher than a set threshold value, triggering a system alarm message to remind a manager to manage and control the personnel who don the work clothes incorrectly in the video picture.
In the steps (1), (3) and (5), the extraction method of the key points of the human body is an mmpos algorithm.
In the step (1), the key points comprise a head, shoulders, a crotch and four limbs.
In the steps (2), (4) and (5), the target detection algorithm is a Yolov5 target detection algorithm.
And (3) acquiring three images of the person wearing the style frock correctly at different angles in a camera picture, wherein the three images are respectively a front side, a side surface and a back side.
In the step (4), the ResNet network is used for extracting the personnel service characteristics in the image slice.
In the step (5), the ResNet network is used for extracting the second
Figure 257893DEST_PATH_IMAGE020
The clothing characteristics of the individual image pieces.
In the step (6), the distance between the two feature vectors is mapped to 0% -100% by using the deformation of the sigmoid function.
Has the advantages that: compared with the prior art, the invention has the following advantages:
(1) by applying the technologies of target detection, human body key point detection, clothing feature extraction and the like in the field of computer vision, the method is different from other work clothing wearing detection methods, features do not need to be constructed manually, and the situations of false alarm and false alarm of the manual feature extraction method are effectively reduced;
(2) the method for detecting the wearing of the industrial clothes based on the clothing style feature extraction is different from other methods which need to collect a large number of industrial clothes image data sets and carry out customized training, and the detection work of the wearing of the personnel clothes in a video stream picture can be realized only by providing three pictures shot at different angles of the style industrial clothes as an industrial clothes base, so that the online efficiency of an industrial clothes scene model is greatly improved, and the method is suitable for the detection of the industrial clothes of different styles.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The invention is further explained below with reference to the drawings.
As shown in fig. 1, the method for detecting wearing of an industrial garment based on the extraction of the style features of the garment of the present invention includes the following steps:
(1) extracting key points of a human body: extracting human body key points from all the persons contained in the image through an mmpos algorithm, wherein if all the key points of one person are extracted, the person target is marked as 1, and if not, the person target is marked as 0;
(2) detecting a person target: identifying a person target in the image through a Yolov5 target detection algorithm, and returning the position information of a circumscribed rectangular frame of the person target;
(3) recording a work service library: when a bottom library is manufactured for a certain style of industrial garment, only one person in a camera acquisition picture is ensured, and three images of different angles, namely the front side, the side and the back side, of the worker correctly wearing the style of industrial garment are acquired in the camera picture; judging whether all key points of the personnel are in the image by adopting the same method as the step (1), if so, storing the image into a bottom library of the style frock, and if not, re-collecting the image of the angle;
(4) extracting the characteristics of the work service library: image cutting is carried out on the personnel part in the image through a Yolov5 target detection algorithm, personnel image pieces are cut out, and personnel uniform characteristics in the image pieces are extracted
Figure 421021DEST_PATH_IMAGE021
The base library of each work clothes style can generate three feature vectors:
Figure 807003DEST_PATH_IMAGE022
in which
Figure 570428DEST_PATH_IMAGE023
；
(5) Extracting clothing features of people with video streaming pictures: using a Yolov5 target detection algorithm, cutting images of personnel parts in the images according to the personnel detection frame, cutting personnel image slices, extracting personnel key points in the image slices by using the human body key point extraction method adopted in the step (1), and judging whether the whole body part of the personnel is in the image slices; let the number of image slices satisfying the condition that the whole body part of the person is within the image slice beNThen extract the first
Figure 637741DEST_PATH_IMAGE024
The individual image pieces are characterized in that
Figure 655376DEST_PATH_IMAGE025
Wherein
Figure 962992DEST_PATH_IMAGE026
And is
Figure 964446DEST_PATH_IMAGE027
；
(6) And (3) feature comparison: if in step (5)
Figure 632187DEST_PATH_IMAGE028
Namely, the condition that the whole body part of a person is in the image slice is not contained in the intercepted video frame picture, and the analysis of the video frame is skipped; if it is
Figure 956858DEST_PATH_IMAGE029
For the second in the video stream picture in step (5)
Figure 684643DEST_PATH_IMAGE030
Corresponding feature extracted from personal image slice
Figure 907814DEST_PATH_IMAGE025
Respectively with feature vectors
Figure 379246DEST_PATH_IMAGE022
Using a Euclidean distance between
Figure 142713DEST_PATH_IMAGE031
Wherein
Figure 244662DEST_PATH_IMAGE032
In which
Figure 689550DEST_PATH_IMAGE022
Express the first in the work clothes base
Figure 213941DEST_PATH_IMAGE033
The feature vector of the individual person image slice,
Figure 326253DEST_PATH_IMAGE025
representing the first in a video frame
Figure 130261DEST_PATH_IMAGE024
Feature vectors of individual person image patches;
Figure 282019DEST_PATH_IMAGE034
representing feature vectors
Figure 829675DEST_PATH_IMAGE022
To (1) a
Figure 796494DEST_PATH_IMAGE035
The number of the elements is one,
Figure 36982DEST_PATH_IMAGE036
representing feature vectors
Figure 971309DEST_PATH_IMAGE025
To (1) a
Figure 525918DEST_PATH_IMAGE035
An element;
Figure 347244DEST_PATH_IMAGE037
，
Figure 772016DEST_PATH_IMAGE038
and is
Figure 678792DEST_PATH_IMAGE039
，
Figure 568250DEST_PATH_IMAGE040
Representing feature vectors
Figure 962192DEST_PATH_IMAGE022
And
Figure 278903DEST_PATH_IMAGE025
dimension (d); mapping of the distance between two feature vectors is achieved through deformation of a sigmoid function, the mapping is 0% -100%, and the second judgment is carried out according to a set threshold value
Figure 938555DEST_PATH_IMAGE030
Whether the person in the individual image patch is wearing the frock correctly; the threshold is manually set, generally based on manual experience and specific model detection effect, and is increased if the detection sensitivity is higher, otherwise, the threshold is reduced;
(7) and (3) alarm triggering: and if any characteristic score in the video streaming picture is higher than a set threshold value, triggering a system alarm message to remind a manager to manage and control the personnel who don the work clothes incorrectly in the video picture.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.

Claims (8)

1. A method for detecting wearing of industrial clothes based on clothes style feature extraction is characterized in that: the method comprises the following steps:
(1) extracting key points of a human body: extracting human key points from all the people in the image by a human key point extraction method, wherein if all the key points of one person are extracted, the target mark of the person is 1, and if not, the target mark is 0;
(2) detecting a person target: identifying a personnel target in the image through a target detection algorithm, and returning the position information of a circumscribed rectangular frame of the personnel target;
(3) recording a work service library: when a bottom library is manufactured for a certain style of work clothes, only one person in a camera collecting picture is ensured, an image of the work clothes correctly worn by the person is collected in the camera picture, whether all key points of the person are in the image is judged by adopting a human body key point extraction method, if the image is stored in the bottom library of the style work clothes, the image of the angle is collected again if the key points are not in the image;
(4) extracting the characteristics of the work service library: cutting out the image of the personnel part in the image by a target detection algorithm, cutting out personnel image pieces, extracting personnel clothing characteristics in the image pieces
Figure 208828DEST_PATH_IMAGE001
The base library of each work clothing style generates three feature vectors:
Figure 594810DEST_PATH_IMAGE002
wherein
Figure 92656DEST_PATH_IMAGE003
；
(5) Extracting clothing features of people with video streaming pictures: using a target detection algorithm, cutting an image of a person part in the image according to a person detection frame to obtain a person image sheet, extracting person key points in the image sheet by using a human body key point extraction method, and judging whether the whole body part of the person is in the image sheet; let the number of image slices satisfying the condition that the whole body part of the person is within the image slice beNThen extract the first
Figure 159970DEST_PATH_IMAGE004
The individual image pieces are characterized in that
Figure 443183DEST_PATH_IMAGE005
Wherein
Figure 747869DEST_PATH_IMAGE006
And is
Figure 483744DEST_PATH_IMAGE007
；
(6) And (3) feature comparison: if in step (5)
Figure 151486DEST_PATH_IMAGE008
Namely, the condition that the whole body part of a person is in the image slice is not contained in the intercepted video frame picture, and the analysis of the video frame is skipped; if it is
Figure 289206DEST_PATH_IMAGE008
For the second in the video stream picture in step (5)
Figure 203941DEST_PATH_IMAGE004
Corresponding feature extracted from personal image slice
Figure 427112DEST_PATH_IMAGE005
Respectively with feature vectors
Figure 898545DEST_PATH_IMAGE009
Using the Euclidean distance between
Figure 641504DEST_PATH_IMAGE010
Wherein
Figure 743452DEST_PATH_IMAGE011
Wherein
Figure 453919DEST_PATH_IMAGE009
Express the first in the work clothes base
Figure 712731DEST_PATH_IMAGE012
The feature vector of the individual person image slice,
Figure 825044DEST_PATH_IMAGE005
representing the first in a video frame
Figure 832314DEST_PATH_IMAGE004
Feature vectors of individual person image patches;
Figure 777880DEST_PATH_IMAGE013
representing feature vectors
Figure 591115DEST_PATH_IMAGE009
To (1)
Figure 557934DEST_PATH_IMAGE014
The number of the elements is one,
Figure 250953DEST_PATH_IMAGE015
representing feature vectors
Figure 670433DEST_PATH_IMAGE005
To (1) a
Figure 21780DEST_PATH_IMAGE016
An element;
Figure 108684DEST_PATH_IMAGE017
，
Figure 270806DEST_PATH_IMAGE018
and is
Figure 177583DEST_PATH_IMAGE019
，
Figure 270303DEST_PATH_IMAGE020
Representing feature vectors
Figure 460982DEST_PATH_IMAGE009
And
Figure 308853DEST_PATH_IMAGE005
dimension (d); mapping the distance between two characteristic vectors, and judging the second time according to a set threshold value
Figure 702925DEST_PATH_IMAGE004
Whether the person in the individual image patch is wearing the frock correctly;
(7) and (3) alarm triggering: and if any characteristic score in the video streaming picture is higher than a set threshold value, triggering a system alarm message to remind a manager to manage and control the personnel who don the work clothes incorrectly in the video picture.
2. The method for detecting the wearing of the industrial clothes based on the extraction of the features of the clothes style according to claim 1, wherein: in the steps (1), (3) and (5), the extraction method of the key points of the human body is an mmpos algorithm.
3. The method for detecting the wearing of the industrial clothes based on the extraction of the features of the clothes style according to claim 1, wherein: in the step (1), the key points comprise a head, shoulders, a crotch and four limbs.
4. The method for detecting the wearing of the industrial clothes based on the extraction of the features of the clothes style according to claim 1, wherein: in the steps (2), (4) and (5), the target detection algorithm is a Yolov5 target detection algorithm.
5. The method for detecting the wearing of the industrial clothes based on the extraction of the features of the clothes style according to claim 1, wherein: and (3) acquiring three images of the person wearing the style frock correctly at different angles in a camera picture, wherein the three images are respectively a front side, a side surface and a back side.
6. The method for detecting the wearing of the industrial clothes based on the extraction of the features of the clothes style according to claim 1, wherein: in the step (4), the ResNet network is used for extracting the personnel service characteristics in the image slice.
7. The method for detecting the wearing of the industrial clothes based on the extraction of the features of the clothes style according to claim 1, wherein: in the step (5), the ResNet network is used for extracting the second
Figure 347139DEST_PATH_IMAGE021
The clothing characteristics of the individual image pieces.
8. The method for detecting the wearing of the industrial clothes based on the extraction of the features of the clothes style according to claim 1, wherein: in the step (6), the distance between the two feature vectors is mapped to 0% -100% by using the deformation of the sigmoid function.
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Cited By (1)

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Publication number Priority date Publication date Assignee Title
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CN113792607A (en) * 2021-08-19 2021-12-14 辽宁科技大学 Neural network sign language classification and identification method based on Transformer

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Application publication date: 20220603