CN108470255A - Workload Account method and device, storage medium, computing device - Google Patents
Workload Account method and device, storage medium, computing device Download PDFInfo
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- CN108470255A CN108470255A CN201810325328.9A CN201810325328A CN108470255A CN 108470255 A CN108470255 A CN 108470255A CN 201810325328 A CN201810325328 A CN 201810325328A CN 108470255 A CN108470255 A CN 108470255A
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Abstract
A kind of Workload Account method and device, storage medium, computing device, the Workload Account method include obtaining video information；Face datection is carried out to obtain face information to the video information, and User Identity is determined according to the face information；The Item Information for identifying the user behavior posture of each user according to the video information and/or taking；The user behavior posture of each user and/or the Item Information taken are associated with corresponding User Identity；For each User Identity, according to its associated user behavior posture and/or the Item Information taken, counting user workload.The technical solution provided through the invention can intelligently count the amount of user effort of each user, and accuracy is high, and saves human cost.
Description
Technical field
The present invention relates to applied statistics technical fields, are situated between more particularly to a kind of Workload Account method and device, storage
Matter, computing device.
Background technology
Currently, how to carry out quantitative statistics to the work of each employee is the research contents that administrative staff extremely pay close attention to.It passes
The Workload Account method of system is by artificially observing, counting determining.The workload artificially counted is easily influenced by subjective factor,
There are the problems such as unilateral, inaccurate, and it is time-consuming and laborious, and human cost is higher.
Therefore, the workload of employee how is counted, it has also become one of managers' urgent problem to be solved.
Invention content
The technical problem to be solved by the present invention is to provide a kind of Workload Account methods, to improve the accuracy of statistical result,
The workload of each employee is intelligently counted, and saves human cost.
In order to solve the above technical problems, the embodiment of the present invention provides a kind of Workload Account method, the Workload Account
Method includes：Obtain video information；Face datection is carried out to obtain face information, and according to the face to the video information
Information determines User Identity；The object for identifying the user behavior posture of each user according to the video information and/or taking
Product information；The user behavior posture of each user and/or the Item Information taken are associated with corresponding User Identity；It is right
In each User Identity, according to its associated user behavior posture and/or the Item Information taken, counting user work
Amount.
Optionally, described for each User Identity, according to its associated user behavior posture and/or the object taken
Product information, counting user workload include：For each User Identity, if its associated user behavior posture with it is default
The Item Information that action classification matches and/or takes is matched with default goods categories, then is denoted as detection hit；According to each user
The quantity of identity detection hit, determines the amount of user effort of the User Identity.
Optionally, the deliberate action classification includes passing the action of dish end plate, and the default goods categories include vegetable and support
Disk.
Optionally, the acquisition video information includes：The video information is obtained from picture pick-up device, and the picture pick-up device is used
In shooting vegetable outlet.
Optionally, the quantity according to the detection hit of each User Identity, determines the use of the User Identity
Family workload includes：The quantity of each User Identity detection hit is summarized within a preset period of time, it is each to obtain
The amount of user effort of a user.
Optionally, the Workload Account method further includes：Face datection is being carried out to obtain people to the video information
Before face information, the face information of each user and the User Identity bound therewith are stored to database.
In order to solve the above technical problems, the embodiment of the present invention also provides a kind of Workload Account device, the workload system
Counter device includes：Acquisition module is suitable for obtaining video information；Determining module is suitable for carrying out Face datection to the video information
To obtain face information, and User Identity is determined according to the face information；Identification module is suitable for being believed according to the video
The Item Information that breath identifies the user behavior posture of each user and/or takes；Relating module is suitable for the user of each user
Behavior posture and/or the Item Information taken are associated with corresponding User Identity；Statistical module is suitable for for each user
Identity, according to its associated user behavior posture and/or the Item Information taken, counting user workload.
Optionally, the statistical module includes：Submodule is marked, for each User Identity, if its associated
User behavior posture is matched with deliberate action categorical match and/or the Item Information taken with default goods categories, then the mark
Note submodule is suitable for being denoted as detection hit；Determination sub-module is suitable for the quantity according to the detection hit of each User Identity, really
The amount of user effort of the fixed User Identity.
Optionally, the deliberate action classification includes passing the action of dish end plate, and the default goods categories include vegetable and support
Disk.
Optionally, the acquisition module includes：Acquisition submodule, the video information is obtained from picture pick-up device, described to take the photograph
As equipment is for shooting vegetable outlet.
Optionally, the determination sub-module includes：Collection unit is suitable within a preset period of time to each user identity mark
The quantity for knowing detection hit is summarized, to obtain the amount of user effort of each user.
Optionally, the Workload Account device further includes：Memory module is suitable for carrying out face to the video information
Detection is before obtaining face information, the face information of each user and the User Identity bound therewith to be stored to number
According to library.
In order to solve the above technical problems, the embodiment of the present invention also provides a kind of storage medium, it is stored thereon with computer and refers to
The step of order, the computer instruction executes above-mentioned Workload Account method when running.
In order to solve the above technical problems, the embodiment of the present invention also provides a kind of computing device, including memory and processor,
The computer instruction that can be run on the processor is stored on the memory, the processor runs the computer and refers to
The step of above-mentioned Workload Account method is executed when enabling.
Compared with prior art, the technical solution of the embodiment of the present invention has the advantages that：
The embodiment of the present invention provides a kind of Workload Account method, including obtains video information；To the video information into
Row Face datection determines User Identity to obtain face information according to the face information；According to the video information
The Item Information for identifying the user behavior posture of each user and/or taking；By the user behavior posture of each user and/or take
The Item Information taken is associated with corresponding User Identity；For each User Identity, according to its associated user's row
For posture and/or the Item Information taken, counting user workload.The technical solution provided through the embodiment of the present invention, can be with
User identity is determined by carrying out Face datection to video information, and then identifies user behavior posture and/or the article taken letter
Each user identity is ceased and be associated with, so as to no longer rely on manpower merely, realizes that intelligent, systematization counts each user's
Amount of user effort, time saving and energy saving, accuracy is high, and can save human cost.
Further, described for each User Identity, according to its associated user behavior posture and/or the object taken
Product information, counting user workload include：For each User Identity, if its associated user behavior posture with it is default
The Item Information that action classification matches and/or takes is matched with default goods categories, then is denoted as detection hit；According to each user
The quantity of identity detection hit, determines the amount of user effort of the User Identity.It provides through the embodiment of the present invention
Technical solution can screen the user behavior posture counted for amount of user effort and/or the Item Information taken, exclude as possible
The disturbing factor (such as cannot be used for the user behavior posture of counting user workload) of amount of user effort statistics, to improve user
The accuracy of Workload Account.
Further, the quantity of each User Identity detection hit is summarized within a preset period of time, to obtain
The amount of user effort of each user.Summarize within a preset period of time, the amount of user effort in effective period of time can be obtained, favorably
In realization trend monitoring and management.
Description of the drawings
Fig. 1 is a kind of flow diagram of Workload Account method of the embodiment of the present invention；
Fig. 2 is a kind of flow diagram of specific implementation mode of step S105 in Fig. 1；
Fig. 3 is a kind of typical case schematic diagram of a scenario of the embodiment of the present invention；
Fig. 4 is a kind of structural schematic diagram of Workload Account device of the embodiment of the present invention.
Specific implementation mode
It will be appreciated by those skilled in the art that as described in the background art, existing Workload Account scheme still relies on manpower system
Amount of user effort is counted, it is of high cost, it is time-consuming and laborious, and statistical result, easily by interference from human factor, accuracy is low.
The embodiment of the present invention provides a kind of Workload Account method, including obtains video information；To the video information into
Row Face datection determines User Identity to obtain face information according to the face information；According to the video information
The Item Information for identifying the user behavior posture of each user and/or taking；By the user behavior posture of each user and/or take
The Item Information taken is associated with corresponding User Identity；For each User Identity, according to its associated user's row
For posture and/or the Item Information taken, counting user workload.
The technical solution provided through the embodiment of the present invention can determine user identity by Face datection, identify user
Behavior posture and/or the Item Information taken simultaneously are associated with each user identity, so as to no longer rely on manpower merely, realize intelligence
Energyization, systematization count the amount of user effort of each user, and accuracy is high, time saving and energy saving, and can save human cost.
It is understandable to enable above-mentioned purpose, feature and the advantageous effect of the present invention to become apparent, below in conjunction with the accompanying drawings to this
The specific embodiment of invention is described in detail.
Fig. 1 is a kind of flow diagram of Workload Account method of the embodiment of the present invention.The Workload Account method
It may comprise steps of：
Step S101：Obtain video information；
Step S102：Face datection is carried out to obtain face information, and according to the face information to the video information
Determine User Identity；
Step S103：According to the article letter that the video information identifies the user behavior posture of each user and/or takes
Breath；
Step S104：By the user behavior posture of each user and/or the Item Information taken and corresponding user identity
Mark association；
Step S105：For each User Identity, according to its associated user behavior posture and/or the article taken
Information, counting user workload.
Specifically, before being counted to amount of user effort, camera, video camera etc. can be placed in predeterminated position
Picture pick-up device, to shoot video information.
As a non-limiting embodiment, the picture pick-up device can be arranged in the oblique upper of the vegetable outlet in restaurant,
And the position of vegetable outlet can be shot.The picture pick-up device can shoot vegetable outlet, obtain video information.
For example, in food and beverage sevice, the picture pick-up device can be taken with shooting service person end the pallet for holding vegetable and vegetable,
Get fire at end flavoring food pot, shooting service person of shooting service person passes the action of dish end plate, the bowls and chopsticks to be cleaned that take of shooting service person end
Deng.In the specific implementation, it can become and dissolve more embodiments, which is not described herein again.
As another non-limiting embodiment, the picture pick-up device can be arranged in the warehouse of storage express delivery, and
The position of courier's inspection package can be shot.For example, shooting courier's packing wrapping action, shooting courier's sorting package are dynamic
Make etc., it no longer repeats one by one here.
Later, it can be each user (such as restaurant waiter) pre-set user identity.According to the user identity
Mark can uniquely determine user identity.
Further, the picture pick-up device can also be utilized to shoot the face information of each user.In the people of each user
It, can be by the face information of the user and the user bound therewith body after the User Identity of face information and the user are bound
Part mark is stored together to database.
Wherein, the database can be the external data base being connect with the picture pick-up device, can also be to be contained in institute
State the database in the data memory module in picture pick-up device.
As a non-limiting embodiment, the user can be the restaurant attendant in catering industry.It is described
Picture pick-up device can in advance store the face information of each restaurant attendant taken into the database, in case after
It is used when continuous counting user workload.
In step S101, cloud server or local computer can obtain video information from the picture pick-up device.
The video information includes the face information of user, user behavior posture and/or the Item Information etc. taken.
In step s 102, cloud server or local computer can be to the faces in the video information into pedestrian
Face detects.For example, Face datection is carried out to the face occurred in the video information using face recognition technology, to obtain face
Information.
After determining face information, user can be determined according to the User Identity that the face information is bound.
In step s 103, cloud server or local computer can be to the user behavior appearances in the video information
Gesture is identified, to identify the behavior posture of each user；Alternatively, can in the video information, what each user took
Item Information is identified, to identify Item Information that user takes；Alternatively, to the user behavior posture in the video information
And/or the Item Information that user takes is identified, with the behavior posture for identifying each user and the Item Information taken.It needs
Illustrate, to reduce calculation amount, can in the video information user behavior posture and/or the article taken of user believe
Breath carries out fuzzy diagnosis.
In step S104, User Identity and knowledge that cloud server or local computer can obtain identification
The behavior posture for each user not obtained is associated；Alternatively, will identify what obtained User Identity and identification obtained
The Item Information that each user takes is associated；Alternatively, it is each to identify that obtained User Identity and identification obtain
The behavior posture of user, the Item Information taken are associated.
In step S105, cloud server or local computer can count the use to each User Identity
The quantity of the behavior posture of the associated user of family identity, to obtain the amount of user effort of the User Identity；Alternatively, system
The quantity for counting the Item Information that the associated user of the User Identity takes, to obtain the user job of the User Identity
Amount；Alternatively, count the behavior posture of the associated user of the User Identity and the quantity of Item Information that user takes, with
To the amount of user effort of the User Identity.
Specifically, with reference to figure 2, the step S105 may comprise steps of：
Step S1051：For each User Identity, if its associated user behavior posture and deliberate action classification
The Item Information for matching and/or taking is matched with default goods categories, then is denoted as detection hit；
Step S1052：According to the quantity of each User Identity detection hit, the user of the User Identity is determined
Workload.
More specifically, in step S1051, for each User Identity, the use being associated can be compared
Whether behavior posture in family matches deliberate action classification, if it does, then detection hit can be denoted as.Wherein, the deliberate action
Classification can be to be stored in advance in action classification database, and characterization user completes the various action classifications of work.For example, described
Deliberate action classification may include passing the action of dish end plate, can be the action that both hands extension lifts article in specific implementation, or
Person, end of bending over take action of kitchen range etc..
Wherein, the action classification database can be established in advance, for storing the various actions appearance for completing work
The deliberate action classification of the deliberate action classification of gesture, storage can be obtained by the demonstration movement of shooting.
Alternatively, for each User Identity, can compare the Item Information taken whether with default goods categories
Matching, if it does, then detection hit can be denoted as.Wherein, the default goods categories can be thought as that user completes work and touches
And various goods categories.For example, it may be vegetable and pallet.
Wherein, the default goods categories can be stored in advance in item database, which includes
Goods categories to actual article by being taken pictures to obtain.The goods categories can be preserved to the item database.
Alternatively, for each User Identity, matched when with the associated user behavior posture of the User Identity
Deliberate action classification, and the user take Item Information matching preset goods categories when, can be denoted as detection hit.
In step S1052, after determining User Identity, the number of hit can be detected according to the User Identity
Amount, obtains the corresponding amount of user effort of the User Identity.
Specifically, the amount of user effort for the User Identity being associated, then can be incremented by by once detection hit
(such as plus 1), finally obtains the amount of user effort of the User Identity.
More specifically, cloud server or local computer can be in preset time periods (such as daily or monthly)
The quantity for calculating each User Identity detection hit, to obtain user job of the user in the preset time period
Amount.
Fig. 3 is a kind of typical case schematic diagram of a scenario of the embodiment of the present invention.
As shown in figure 3, in typical case scene restaurant 200, it is assumed that video camera 201 is erected at vegetable outlet oblique upper, just
It is directed at dish delieving device 203 well.
In specific implementation, when waiter 202 passes dish (such as chafing dish bottom flavorings pot of taking, take vegetable and pallet etc.), take the photograph
Camera 201 can take the face information of waiter 202, and whether the waiter 202 can be detected by face recognition technology
For restaurant attendant, if it is, can determine the waiter's 202 according to the database (not shown) comprising face information
User Identity.
Later, if waiter 202 passes through from dish delieving device 203, the article that user behavior posture can be carried out and/or taken
The detection of information, if detection hit, can add 1 to the amount of user effort of the User Identity.
In preset time period (such as daily), the amount of user effort of the waiter 202 can be obtained based on above-mentioned steps.
Thus, it is possible to realize that the amount of user effort to each waiter in restaurant 200 counts, and obtains the user of each waiter
Workload.Based on the amount of user effort of each waiter, trend monitoring and management may be implemented.
By upper, the technical solution provided through the embodiment of the present invention can intelligently complete the user to each user
The statistics of workload, accuracy is high, not only time saving and energy saving, but also can save human cost.
Fig. 4 is a kind of Workload Account device of the embodiment of the present invention.The Workload Account device 4 can be used for implementing
Workload Account method and technology scheme described in Fig. 1 and embodiment illustrated in fig. 2.
With reference to figure 4, the Workload Account device 4 may include：Acquisition module 41, determining module 43, identification module 44,
Relating module 45 and statistical module 46.
Specifically, the acquisition module 41 is suitable for obtaining video information；The determining module 43 is suitable for the video
Information carries out Face datection to obtain face information, and determines User Identity according to the face information；The identification mould
The Item Information that block 44 is suitable for identifying the user behavior posture of each user according to the video information and/or taking；The pass
Gang mould block 45 is suitable for closing the user behavior posture of each user and/or the Item Information taken with corresponding User Identity
Connection；The statistical module 46 is suitable for for each User Identity, according to its associated user behavior posture and/or takes
Item Information, counting user workload.
Further, the statistical module 46 may include：Mark submodule 461 and determination sub-module 462.
Specifically, for each User Identity, if its associated user behavior posture and deliberate action classification
The Item Information for matching and/or taking is matched with default goods categories, then the label submodule 461 is suitable for being denoted as detection life
In；The determination sub-module 462 is suitable for, according to the quantity of each User Identity detection hit, determining the User Identity
Amount of user effort.
Further, the deliberate action classification includes passing the action of dish end plate, the default goods categories include vegetable with
Pallet.
Further, the acquisition module 41 may include：Acquisition submodule 411.Specifically, the video information from
Picture pick-up device obtains, and the picture pick-up device is for shooting vegetable outlet.
Further, the determination sub-module 462 may include collection unit 4621.
It is hit specifically, the collection unit 4621 is suitable within a preset period of time detecting each User Identity
Quantity summarized, to obtain the amount of user effort of each user.
Further, the Workload Account device 4 can also include memory module 42.
Specifically, the memory module 42 is suitable for carrying out Face datection to the video information to obtain face information
Before, the face information of each user and the User Identity bound therewith are stored to database.
Operation principle, more contents of working method about the Workload Account device 4, are referred to above-mentioned Fig. 1
With the associated description in Fig. 2, which is not described herein again.
Further, a kind of storage medium is also disclosed in the embodiment of the present invention, is stored thereon with computer instruction, the calculating
The Workload Account method and technology scheme described in above-mentioned Fig. 1 and embodiment illustrated in fig. 2 is executed when machine instruction operation.Preferably,
The storage medium may include such as non-volatile (non-volatile) memory or non-transient (non-
Transitory) the computer readable storage mediums such as memory.The computer readable storage medium may include ROM, RAM,
Disk or CD etc..
Further, a kind of computing device, including memory and processor, the memory is also disclosed in the embodiment of the present invention
On be stored with the computer instruction that can be run on the processor, the processor executes when running the computer instruction
Workload Account method and technology scheme described in above-mentioned Fig. 1 and embodiment illustrated in fig. 2.Specifically, the computing device can
To be the either local computer etc. of cloud server.
Although present disclosure is as above, present invention is not limited to this.Any art technology user is not departing from this
It in the spirit and scope of invention, can make various changes or modifications, therefore protection scope of the present invention should be with claim institute
Subject to the range of restriction.
Claims (14)
1. a kind of Workload Account method, which is characterized in that including：
Obtain video information；
Face datection is carried out to obtain face information to the video information, and user identity mark is determined according to the face information
Know；
The Item Information for identifying the user behavior posture of each user according to the video information and/or taking；
The user behavior posture of each user and/or the Item Information taken are associated with corresponding User Identity；
For each User Identity, according to its associated user behavior posture and/or the Item Information taken, counting user
Workload.
2. Workload Account method according to claim 1, which is characterized in that it is described for each User Identity,
Include according to its associated user behavior posture and/or the Item Information taken, counting user workload：
For each User Identity, if its associated user behavior posture and deliberate action categorical match and/or taken
Item Information matched with default goods categories, then be denoted as detection hit；
According to the quantity of each User Identity detection hit, the amount of user effort of the User Identity is determined.
3. Workload Account method according to claim 2, which is characterized in that the deliberate action classification includes passing dish end
Disk acts, and the default goods categories include vegetable and pallet.
4. Workload Account method according to claim 3, which is characterized in that the acquisition video information includes：
The video information is obtained from picture pick-up device, and the picture pick-up device is for shooting vegetable outlet.
5. Workload Account method according to claim 2, which is characterized in that described to be examined according to each User Identity
The quantity for surveying hit, determines that the amount of user effort of the User Identity includes：
The quantity of each User Identity detection hit is summarized within a preset period of time, to obtain the use of each user
Family workload.
6. Workload Account method according to any one of claims 1 to 5, which is characterized in that the video information
Face datection is carried out before obtaining face information, to further include：
The face information of each user and the User Identity bound therewith are stored to database.
7. a kind of Workload Account device, which is characterized in that including：
Acquisition module is suitable for obtaining video information；
Determining module, suitable for carrying out Face datection to obtain face information, and according to the face information to the video information
Determine User Identity；
Identification module, suitable for the article letter for identifying the user behavior posture of each user according to the video information and/or taking
Breath；
Relating module, suitable for by the user behavior posture of each user and/or the Item Information taken and corresponding user identity
Mark association；
Statistical module is suitable for for each User Identity, according to its associated user behavior posture and/or the article taken
Information, counting user workload.
8. Workload Account device according to claim 7, which is characterized in that the statistical module includes：Mark submodule
Block, for each User Identity, if its associated user behavior posture and deliberate action categorical match and/or taken
Item Information is matched with default goods categories, then the label submodule is suitable for being denoted as detection hit；
Determination sub-module is suitable for, according to the quantity of each User Identity detection hit, determining the use of the User Identity
Family workload.
9. Workload Account device according to claim 8, which is characterized in that the deliberate action classification includes passing dish end
Disk acts, and the default goods categories include vegetable and pallet.
10. Workload Account device according to claim 9, which is characterized in that the acquisition module includes：Obtain submodule
Block, the video information are obtained from picture pick-up device, and the picture pick-up device is for shooting vegetable outlet.
11. Workload Account device according to claim 8, which is characterized in that the determination sub-module includes：
Collection unit, suitable for summarizing within a preset period of time to the quantity of each User Identity detection hit, with
To the amount of user effort of each user.
12. according to claim 7 to 11 any one of them Workload Account device, which is characterized in that further include：Store mould
Block, suitable for carrying out Face datection to the video information with before obtaining face information, by the face information of each user with
And the User Identity bound therewith is stored to database.
13. a kind of storage medium, is stored thereon with computer instruction, which is characterized in that executed when the computer instruction operation
The step of claim 1 to 6 any one of them Workload Account method.
14. a kind of computing device, including memory and processor, it is stored with and can runs on the processor on the memory
Computer instruction, which is characterized in that perform claim requires any one of 1 to 6 when the processor runs the computer instruction
The step of described Workload Account method.
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| CN201810325328.9A CN108470255B (en) | 2018-04-12 | 2018-04-12 | Workload statistical method and device, storage medium and computing equipment |
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| CN201810325328.9A CN108470255B (en) | 2018-04-12 | 2018-04-12 | Workload statistical method and device, storage medium and computing equipment |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109636200A (en) * | 2018-12-17 | 2019-04-16 | 秒针信息技术有限公司 | Restaurant service behavioral statistics method and apparatus |
| CN110619500A (en) * | 2019-09-26 | 2019-12-27 | 秒针信息技术有限公司 | Method, device, equipment and medium for determining employee information of packing staff |
| CN111242546A (en) * | 2020-01-10 | 2020-06-05 | 秒针信息技术有限公司 | Goods picking task accounting method and device based on face recognition |
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| CN111242546A (en) * | 2020-01-10 | 2020-06-05 | 秒针信息技术有限公司 | Goods picking task accounting method and device based on face recognition |
| WO2023279785A1 (en) * | 2021-07-06 | 2023-01-12 | 上海商汤智能科技有限公司 | Method and apparatus for detecting whether staff member is compatible with post, computer device, and storage medium |
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