KR20210103140A - Job Recommendation System and Job Recommendation Method using the same - Google Patents

Abstract

The present invention relates to a job recommendation system and a job recommendation method using the job recommendation system including: an image input module where a subject face image is input; a face analysis unit analyzing a feature point on the subject face based on the face image input to the image input module and determining the subject's personality type by comparative analysis between the analyzed subject face feature point information and pre-stored reference face feature point information by personality type; a questionnaire providing unit providing the subject with a recommendation job survey questionnaire corresponding to the subject's personality type determined by the face analysis unit among pre-stored recommendation job survey questionnaires for job recommendation; an information input module for inputting answer information of the subject regarding questions of the recommendation job survey questionnaire provided to the subject by the questionnaire providing unit; and a job recommendation module recommending a job suitable for the subject based on the answer information input at the information input module. According to the present invention, the personality type is determined in accordance with the subject's face characteristics, the subject is provided with a questionnaire corresponding to the determined personality type, and job recommendation is performed based on subject answer information analysis. Accordingly, a suitable job for the subject can be recommended more accurately.

Description

Job Recommendation System and Job Recommendation Method using the same}

The present invention relates to a work recommendation system and a work recommendation method using the same, and more particularly, by determining the personality type of a subject according to the subject's facial features, and providing a questionnaire corresponding to the subject based on the determined personality type A task recommendation system capable of recommending a task suitable for a subject according to response information, and a task recommendation method using the same.

The current generalized test method for examining the psychology of an individual, such as personality, ability, and aptitude to recommend work is the psychological test method through questionnaire. There are structured tests such as questionnaire-type personality tests and intelligence tests. These test methods include a number of questions, and a score is calculated for the responses to the questions to determine the subject's disposition.

However, since the conventional inspection method is a method in which the inspected directly writes the response to the question, if the inspected intentionally writes wrong information about the question, it is difficult to determine the task suitable for the inspected.

Registered Patent Publication No. 10-1553327: Psychological analysis device

The present invention was created to solve the above problems, and the personality type is determined according to the facial features of the examinee, and a questionnaire corresponding to the determined personality type is provided to the examinee to perform a task suitable for the subject based on the subject's response information An object of the present invention is to provide a recommendable work recommendation system and a work recommendation method using the same.

The task recommendation system according to the present invention for achieving the above object includes an image input module to which a face image of a subject is input, and a feature point of the subject's face based on the face image input to the image input module, and analyzed A face analysis unit that compares and analyzes the facial feature point information of the subject with pre-stored reference facial feature point information for each personality type to determine the personality type of the subject; A questionnaire providing unit that provides a questionnaire for a recommended work survey corresponding to the personality type of the subject determined in and an information input module to which response information is input, and a task recommendation module for recommending a task suitable for the subject to be inspected based on the response information input from the information input module.

The task recommendation module includes a questionnaire score calculation unit that calculates a score distribution for each task by calculating the scores allocated to the items of the questionnaire for recommended work research based on the response information input from the information input module, and in the questionnaire score calculation unit A recommendation selection unit is provided that recommends the task with the highest score as a task suitable for the subject to be inspected based on the calculated score for each task.

On the other hand, the task recommendation system according to the present invention analyzes facial feature point information and personality types for a plurality of subjects to generate reference face feature point information for each personality type, and analyzes the generated reference face feature point information for each personality type. It may further include a sample providing unit for providing the unit.

The sample providing unit determines the personality types of the subjects based on the response input module to which the response information of the subjects is input to the questions of the propensity analysis questionnaire for examining the personality type, and the response information input from the response input module a personality determination module; a sample input module to which the face images of the subjects are input; and an information generating module for classifying the facial feature points of the subjects provided in , by personality type of the subject, and generating reference facial feature point information for each personality type based on the classified facial feature points of the subjects for each personality type.

The disposition analysis questionnaire preferably includes at least one of the Enneagram questionnaire, Myers-Briggs Type Indicator (MBTI) questionnaire, and DISC (Dominance, Influence, Steadiness, Conscientiousness) questionnaire. do.

The response input module further includes a monitor capable of displaying the questions of the disposition analysis questionnaire, and an input member for allowing the examinee to input response information to the question, and the sample input module is configured to hold the edge of the monitor. a photographing camera which is installed movably along an edge of the monitor to photograph the face of the subject to input the response information by manipulating the input member; and an image selection unit that provides an image of the front face of the subject from among the photographed images to the face analysis unit.

The response input module further includes a monitor capable of displaying the questions of the disposition analysis questionnaire, and an input member for the subject to input response information for the question, and the sample input module has one end of the edge of the monitor. A rotating rod rotatably installed in the monitor and extended by a predetermined length in the central direction of the monitor, is installed at the other end of the rotating rod, and operates the input member to photograph the face of the subject to input the response information A photographing camera, a rotation unit for rotating the rotation rod every predetermined unit time so that the photographing camera is located in the center of the monitor, and an image photographed of the front face of the subject from among the images photographed by the photographing camera, the face An image selection unit provided to the analysis unit is provided.

On the other hand, the work recommendation method according to the present invention includes an image input step in which the face image of the subject is collected through an image input module, and the feature points of the subject's face are analyzed based on the face image of the subject, and the analyzed subject's The face analysis step of comparing and analyzing the facial feature point information with the pre-stored reference facial feature point information for each personality type to determine the personality type of the subject, and the face analysis step of the pre-stored recommended job survey questionnaires for business recommendation. An information input step of collecting response information of an examinee to a questionnaire for recommended task research corresponding to the personality type of the examinee, and a task recommendation step of recommending a task suitable for the subject by analyzing the response information collected in the information input step includes

The task recommendation system and the task recommendation method using the same according to the present invention determine the personality type according to the facial characteristics of the examinee, and provide a questionnaire corresponding to the determined personality type to the examinee to analyze the subject's response information to recommend work. It has the advantage of being able to recommend a job suitable for the subject more accurately.

1 is a block diagram of a work recommendation system according to the present invention;
2 is a flowchart for a work recommendation method according to the present invention;
3 is a block diagram of a work recommendation system according to another embodiment of the present invention;
4 is a perspective view of a sample input module of a work recommendation system according to another embodiment of the present invention;
5 is a block diagram of the work recommendation system of FIG. 4;
6 is a perspective view of a sample input module according to another embodiment of the present invention.

Hereinafter, a work recommendation system and a work recommendation method using the same according to an embodiment of the present invention will be described in detail with reference to the accompanying drawings. Since the present invention can have various changes and can have various forms, specific embodiments are illustrated in the drawings and described in detail in the text. However, this is not intended to limit the present invention to the specific disclosed form, it should be understood to include all modifications, equivalents and substitutes included in the spirit and scope of the present invention. In describing each figure, like reference numerals have been used for like elements. In the accompanying drawings, the dimensions of the structures are enlarged than the actual size for clarity of the present invention.

Terms such as first, second, etc. may be used to describe various elements, but the elements should not be limited by the terms. The above terms are used only for the purpose of distinguishing one component from another. For example, without departing from the scope of the present invention, a first component may be referred to as a second component, and similarly, a second component may also be referred to as a first component.

The terms used in the present application are only used to describe specific embodiments, and are not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly dictates otherwise. In the present application, terms such as “comprise” or “have” are intended to designate that a feature, number, step, operation, component, part, or combination thereof described in the specification exists, but one or more other features It is to be understood that it does not preclude the possibility of the presence or addition of numbers, steps, operations, components, parts, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical and scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present application. does not

1 illustrates a work recommendation system 100 according to the present invention.

Referring to the drawings, the task recommendation system 100 includes an image input module 110 to which a face image of a subject is input, and a feature point of the subject's face based on the face image input to the image input module 110 . A face analysis unit 120 that analyzes and compares and analyzes the analyzed facial feature point information with the pre-stored reference facial feature point information for each personality type to determine the personality type of the subject, and a pre-stored recommendation task group for business recommendation Among the questionnaires used, the questionnaire providing unit 130 that provides a questionnaire for a recommended task research corresponding to the personality type of the subject identified by the face analysis unit 120 to the subject, and the questionnaire providing unit 130 The information input module 140 into which the subject's response information to the questions of the corresponding recommended task survey questionnaire provided to the subject is input, and the task suitable for the subject based on the response information input from the information input module 140 A recommended work recommendation module 150 is provided.

The image input module 110 is an information processing device such as a computer for the subject to input his or her face image is applied. The image input module 110 provides the input face image to the face analysis unit 120 . In this case, it is preferable that the image of the face of the subject is applied as the face image.

The face analysis unit 120 analyzes the facial feature points of the subject based on the face image provided from the image input module 110 . Here, the facial feature points include the shape of eyes, eyebrows, nose, mouth, or the shape of the face. On the other hand, the face analysis unit 120 further includes a database 121 in which feature point information of the reference face for each type of disposition is stored. Here, the corresponding feature point information includes the shape of eyes, eyebrows, nose, mouth, or face.

In this case, it is preferable that the characteristic point information of the reference face is stored in the database 121 for each propensity type of the personality diagnosis tool. The personality diagnosis tool includes the Enneagram, Myers-Briggs Type Indicator (MBTI), Dominance, Influence, Steadiness, Conscientiousness (DISC), and the like.

That is, when the Enneagram is applied as a personality diagnosis tool, information on the feature points of the reference face is stored in the database 121 for each of the nine personality types (Types 1 to 9) of the Enneagram. In addition, when the MBTI is applied as a personality diagnosis tool, the database 121 contains 16 personality types (introverted sensing type, introverted intuition type, introverted thinking type, introverted emotional type, extraverted sensing type, extroverted intuition type, and extroverted type). Feature point information of the reference face is stored for each thinking type, extroverted emotional type). In addition, when the DISC is applied as a personality diagnosis tool, the database 121 stores information on the characteristic points of the reference face for each of the four personality types of the DISC (initiative, sociable, cautious, and stable).

At this time, the face analysis unit 120 compares the analyzed facial feature point information of the subject with the feature point information of the reference face for each personality type stored in the database 121, and calculates the similarity between the reference facial feature point for each personality type and the facial feature point of the subject. . Here, the face analysis unit 120 determines a personality type having the highest similarity among personality types as the personality type of the subject.

The questionnaire providing unit 130 includes a questionnaire storage unit (not shown) in which a plurality of recommended business survey questionnaires are stored. Here, the questionnaire for recommendation work research is prepared for each personality type. That is, each of the questionnaires for the recommendation work survey includes different items according to a preset personality type. The recommended task survey questionnaires have recommended tasks for each personality type, and include questions for examining the suitability of the examinee for the recommended tasks.

The questionnaire providing unit 130 selects a questionnaire for recommended work investigation corresponding to the personality type of the subject determined by the face analysis unit 120 from among the questionnaires stored in the questionnaire storage unit, and applies the selected recommended work investigation questionnaire to the subject. provide to Here, although not shown in the drawing, the questionnaire providing unit 130 may further include a display unit for displaying a corresponding recommended task research questionnaire to the examinee.

The information input module 140 is applied with an information processing device for inputting the subject's response information to the questionnaire for the recommended task research. Here, the information input module 140 applies an input means such as a keyboard or mouse for the subject to input response information to the questions of the questionnaire for recommended work research provided by the questionnaire providing unit 130 . The examinee may select any one number from 1 to 5 as a response to the question of the corresponding recommended work survey questionnaire and write it in the response item.

The task recommendation module 150 recommends a task to the subject based on the response information input from the information input module 140 , and includes a questionnaire score calculation unit 151 and a recommendation selection unit 152 .

The questionnaire score calculation unit 151 calculates a score distribution for each job by calculating the scores allocated to the items of the questionnaire for recommended job research based on the response information input from the information input module 140 . Here, the questionnaire score calculation unit 151 provides the score distribution data for each recommended task according to the response information to the recommendation selection unit 152 .

The recommendation selection unit 152 recommends a job having the highest score as a job suitable for the subject, based on the score for each recommended job calculated by the questionnaire score calculation unit 151 . The recommendation selection unit 152 may transmit information on the recommendation task to a terminal or display unit of a preset manager.

2 is a flowchart of a work recommendation method using the work recommendation system according to the present invention.

Referring to the drawings, the work recommendation method includes an image input step (S101), a face analysis step (S102), an information input step (S103), and a work recommendation step (S104).

The image input step S101 is a step in which a face image of the subject is collected through the image input module 110 . The image input module 110 provides the face image input by the subject to the face analysis unit 120 . In this case, it is preferable that the image of the face of the subject is applied as the face image.

The face analysis step (S102) analyzes the feature points of the subject's face based on the face image of the subject, and compares and analyzes the analyzed facial feature point information with the pre-stored reference facial feature point information for each personality type to analyze the personality of the subject This is the stage to determine the type. Here, the face analysis unit 120 compares the analyzed facial feature point information of the subject with the feature point information of the reference face for each personality type stored in the database 121 to calculate the similarity between the reference facial feature point for each personality type and the facial feature point of the subject. . Here, the face analysis unit 120 determines a personality type having the highest similarity among personality types as the personality type of the subject.

The information input step (S103) is a step of collecting the response information of the examinee to the recommended task survey questionnaire corresponding to the personality type of the examinee determined in the face analysis step among the pre-stored recommended task survey questionnaires for business recommendation am. Here, the questionnaire providing unit 130 selects a questionnaire for recommended work research corresponding to the personality type of the examinee determined by the face analysis unit 120 from among the questionnaires stored in the questionnaire storage unit, and corresponds to the selected recommended work research questionnaire. provided to the examinee. The examinee may input response information for the corresponding recommended task research questionnaire through the information input module 140 .

The task recommendation step (S104) is a step of analyzing the response information collected in the information input step (S103) to recommend a task suitable for the subject. Based on the response information input from the information input module 140, the task recommendation module 150 recommends a task to the subject. The questionnaire score calculation unit 151 of the task recommendation module 150 provides the score distribution data for each recommended task according to the response information to the recommendation selection unit 152, and the recommendation selection unit 152 is the questionnaire score calculation unit 151 Based on the score for each recommended task calculated in

The task recommendation system according to the present invention configured as described above and the task recommendation method using the same determine the personality type according to the facial features of the examinee, and provide a questionnaire corresponding to the determined personality type to the examinee to analyze the examinee's response information This has the advantage of being able to recommend a job suitable for the subject more accurately because it recommends the job.

Meanwhile, FIG. 3 shows a work recommendation system 200 according to another embodiment of the present invention.

Elements having the same function as in the drawings shown above are denoted by the same reference numerals.

Referring to the drawings, the task recommendation system 200 analyzes facial feature point information and personality types for a plurality of subjects to generate reference face feature point information for each personality type, and the generated reference face feature point information for each personality type. and a sample providing unit 210 provided to the face analysis unit.

The sample providing unit 210 includes a response input module 211 into which response information of the subjects to the questions of a disposition analysis questionnaire for examining a personality type is input, and response information input from the response input module 211 . A personality determination module 212 that determines the personality types of the subjects based on A sample analysis unit 214 that analyzes the facial feature points of the examinee based on the sample analysis unit 214, and classifies the facial features of the subjects provided by the sample analysis unit 214 according to the personality type of the subject, and the subject according to the classified personality type and an information generating module 215 that generates information on the feature points of the reference face for each personality type based on the feature points of their faces.

The response input module 211 is an information processing device for inputting response information of a subject to the disposition analysis questionnaire. Here, the information input module 140 may include a monitor capable of displaying the questions of the disposition analysis questionnaire, and an input member for the subject to input response information to the questions. In this case, it is preferable that an input means for inputting information such as a keyboard or a mouse is applied to the input member.

Here, the disposition analysis questionnaire includes questionnaire items according to the personality diagnosis tool used in the face analysis unit 120 . That is, the disposition analysis questionnaire includes any one of the Enneagram questionnaire questions, the Myers-Briggs Type Indicator (MBTI) questionnaire questions, or the DISC (Dominance, Influence, Steadiness, Conscientiousness) questionnaire questions. . For each question of the disposition analysis questionnaire, a response item may be provided in which the form of the testee's response to the corresponding question can be entered numerically. The examinee may select any number from 1 to 5 as a response to the question and write it in the response item. According to the subject's response to the corresponding disposition analysis questionnaire, the subject is determined as one of the propensity types classified by the personality diagnosis tool.

That is, if the propensity analysis questionnaire includes the enneagram questionnaire, the subject is selected as one of the nine types (types 1 to 9) of the Enneagram according to the subject's response to the propensity analysis questionnaire. to determine In addition, if the propensity analysis questionnaire contains questions from the MBTI, 16 types of MBTI (introverted sensing type, introverted intuition type, introverted thinking type, introverted feeling type, extraverted sensing type, Extroverted intuition type, extraverted thinking type, extroverted feeling type), the subject is determined by any one personality type. In addition, if the questionnaire includes DISC questionnaires, the subject is identified as one of the four types of DISC (initiative, sociable, cautious, and stable) according to the respondent's response information.

The personality determination module 212 calculates a score distribution for each personality type by calculating the scores assigned to the questions of the disposition analysis questionnaire based on the response information input from the response input module 211 . Then, the personality determination module 212 determines the personality type having the highest score as the personality type of the subject based on the calculated score distribution.

The sample input module 213 is an information processing device such as a computer for the subject to input his or her face image is applied. The sample input module 213 provides the input face image to the sample analyzer 214 . In this case, it is preferable that the image of the face of the subject is applied as the face image.

The sample analyzer 214 analyzes the facial feature points of the subject based on the face image provided from the sample input module 213 . Here, the facial feature points include the shape of eyes, eyebrows, nose, mouth, or the shape of the face. Then, the sample analysis unit 214 transmits information on the facial feature points of the subject to the information generating module 215 together with information on the personality type of the subject.

The information generation module 215 classifies the information provided by the sample analysis unit 214 by personality type. That is, the information generating module 215 classifies the facial feature points of the subjects provided by the sample analysis unit 214 according to personality types of the subjects. In addition, the information generating module 215 generates the reference facial feature point information for each personality type based on the facial feature points of the subjects for each classified personality type. That is, the information generating module 215 calculates an average of the facial feature points of the investigated subjects classified for each personality type, and selects the calculated average value as the feature point information of the reference face of the corresponding personality type.

The corresponding information generating module 215 provides the generated feature point information of the reference face for each personality type to the face analysis unit 120 . The sample providing unit 210 configured as described above analyzes the faces and personalities of a plurality of subjects to generate feature point information of the reference face, so that the accuracy of the analysis result by the face analyzer 120 can be improved.

On the other hand, although not shown in the drawing, the sample providing unit 210 determines the condition of the subject based on the thermal imaging camera 221 that takes a thermal image of the subject and the thermal image provided by the thermal imaging camera 221 . It further includes a reliability determining unit 222 to discriminate.

The thermal imaging camera 221 is installed adjacent to the monitor 231 of the response input module 211 to capture a thermal image of the face of a subject who inputs response information to the response input modules 211 and 230 . The thermal imaging camera 221 provides the photographed thermal image to the reliability determining unit 222 .

The reliability determining unit 222 analyzes the thermal image provided by the thermal imaging camera 221 and determines that the inspected person is in a suspicious reliability state when the body temperature of the subject's face increases above a preset reference range. Here, it is desirable for the manager to set the reference range according to the questions of the questionnaire or the purpose of analyzing the tendency. The face temperature of the person who lied rises, and the reliability determining unit 222 determines that when the body temperature of the subject rises above the reference range, it is determined that the subject has intentionally entered incorrect information on the questions in the questionnaire, is determined to be a reliability questionable state.

Meanwhile, the information generating module 215 may exclude facial feature point information of the subject, determined by the reliability determining unit as a suspicious reliability state, when generating the reference face feature point information for each personality type.

Meanwhile, a sample input module 240 according to another embodiment of the present invention is illustrated in FIGS. 4 and 5 .

Referring to the drawings, the sample input module 240 is installed movably along the edge of the monitor 231, and operates the input member 232 to photograph the face of the subject to input the response information. A photographing camera 241, a driving unit (not shown) for reciprocally moving the photographing camera 241 along the edge of the monitor 231, and the front face of the subject among the images photographed by the photographing camera 241 and an image selection unit 242 that provides the captured image to the sample analysis unit 214 .

Here, although not shown in the drawing, a moving rail 244 is formed on the edge of the monitor 231 so that the photographing camera 241 can be movably supported. The moving rail 244 is preferably formed to extend in the left-right direction and the vertical direction along the edge of the monitor (231).

The photographing camera 241 photographs the front of the monitor 231 so as to photograph the face of the subject looking at the personality analysis questionnaire displayed through the monitor 231 . Since the corresponding photographing camera 241 is a camera generally used in the prior art to photograph an image, a detailed description thereof will be omitted.

Although not shown in the drawing, the driving unit has an outer peripheral surface in contact with the moving rail 244 , a plurality of driving wheels rotatably installed in the photographing camera 241 , and a rotation installed on the driving wheels to rotate the driving wheel provided with a motor. Meanwhile, the driving unit is not limited thereto, and any driving means capable of moving the photographing camera 241 along the moving rail 244 may be applied.

The image selection unit 242 selects an image in which the front face of the subject is photographed from among the photographed images provided from the photographing camera 241 . Here, the image selection unit 242 recognizes the positions of the eyes, nose, mouth, etc. of the subject in the image captured by the photographing camera 241, and determines whether the image is the front face of the subject based on the recognized information Thus, an image of the subject's frontal face is selected. Also, the image selection unit 242 provides the sample analysis unit 214 with a photographed image of the selected subject's front face.

The sample input module 240 configured as described above captures the subject's face from various angles through the photographing camera 241 moving along the edge of the monitor 231, and takes an image of the front face from the photographed image. Since it is selected and provided to the sample analyzers 214 and 130 , it is possible to improve the accuracy of analyzing the propensity type through the face of the subject.

Meanwhile, FIG. 6 illustrates a sample input module 250 according to another embodiment of the present invention.

Referring to the drawings, one end of the sample input module 250 is rotatably installed on the edge of the monitor 231 , and includes a rotation rod 251 extending a predetermined length in the central direction of the monitor 231 , and the A photographing camera 241 installed at the other end of the rotating rod 251 and photographing the face of the subject who inputs the response information by manipulating the input member 232, and the photographing camera 241 is the monitor A rotating unit 253 for rotating the rotating rod 251 for each predetermined unit time to be located in the central portion of 231, and an image in which the front face of the subject is photographed among the images photographed by the photographing camera 241 An image selection unit 242 provided to the sample analysis unit 214 is provided.

The rotating rod 251 is formed in a bar shape extending by a predetermined length, and is preferably formed of a transparent material so that the examinee can easily see the questionnaire displayed on the monitor 231 .

The photographing camera 241 is installed at the other end of the rotating rod 251 to photograph the front of the monitor 231 . Since the corresponding photographing camera 241 is a camera generally used in the prior art to photograph an image, a detailed description thereof will be omitted.

Although not shown in the drawing, the rotation unit 253 is installed at one end of the rotation rod 251 and includes a rotation motor for rotating the rotation rod 251 and the photographing camera 241 is located in the center of the monitor 231 . A control unit for controlling the rotation motor so that the rotation rod 251 is rotated every predetermined unit time so as to be provided. The control unit initially operates the rotation motor so that the other end of the rotation rod 251 is located on the edge side of the monitor 231, and after the initial unit time has elapsed, the other end of the rotation rod 251 The rotation motor is operated to be located in the center of the monitor 231 , and the subject's face is photographed through the photographing camera 241 . When the photographing camera 241 completes the image capture, the controller operates the rotation motor so that the other end of the rotation rod 251 returns to the edge of the monity.

The image selection unit 242 selects an image in which the front face of the subject is photographed from among the photographed images provided from the photographing camera 241 . Here, the image selection unit 242 recognizes the positions of the eyes, nose, mouth, etc. of the subject in the image captured by the photographing camera 241, and determines whether the image is the front face of the subject based on the recognized information Thus, an image of the subject's frontal face is selected. Also, the image selection unit 242 provides the sample analysis unit 214 with a photographed image of the selected subject's front face.

The description of the presented embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the scope of the invention. Thus, the present invention is not to be limited to the embodiments presented herein, but is to be construed in the widest scope consistent with the principles and novel features presented herein.

100: work recommendation system
110: image input module
120: face analysis unit
121: database
130: questionnaire providing unit
140: information input module
150: work recommendation module
151: survey score calculation unit
152: recommendation selection unit

Claims (8)

an image input module to which a face image of a subject is input;
Based on the facial image input to the image input module, the facial feature points of the subject are analyzed, and the analyzed facial feature point information is compared and analyzed with pre-stored reference face feature information for each personality type to determine the personality type of the subject. a face analysis unit that determines;
a questionnaire providing unit that provides a questionnaire for recommended work research corresponding to the personality type of the examinee determined by the face analysis unit among the pre-stored recommended work survey questionnaires for work recommendation to the subject;
an information input module for inputting response information of a subject to the items of a questionnaire for a corresponding recommended task research provided to the subject by the questionnaire providing unit; and
A task recommendation module for recommending a task suitable for the subject to be inspected based on the response information input from the information input module;
work recommendation system.
According to claim 1,
The task recommendation module is
a questionnaire score calculation unit for calculating a score distribution for each job by calculating the scores allocated to the items of the questionnaire for recommended job research based on the response information input from the information input module; and
A recommendation selection unit for recommending a task with the highest score as a task suitable for the subject to be tested based on the score for each task calculated by the questionnaire score calculation unit;
work recommendation system.
According to claim 1,
A sample providing unit that analyzes facial feature point information and personality types for a plurality of subjects to generate reference face feature point information for each personality type, and provides the generated reference face feature point information for each personality type to the face analysis unit; provided,
work recommendation system.
4. The method of claim 3,
The sample provider
a response input module into which response information of the subjects to the questions of a disposition analysis questionnaire for examining personality types is input;
a personality determination module for determining personality types of the subjects based on the response information input from the response input module;
a sample input module to which face images of the subjects are input;
a sample analysis unit for analyzing the feature points of the subject's faces based on the face images of the subjects input from the sample input module;
an information generation module for classifying the facial feature points of the subjects provided by the sample analysis unit by personality type of the subject, and generating reference facial feature point information for each personality type based on the classified facial feature points for each personality type; provided with
work recommendation system.
5. The method of claim 4,
The disposition analysis questionnaire includes at least one questionnaire item among the Enneagram questionnaire, Myers-Briggs Type Indicator (MBTI) questionnaire, and DISC (Dominance, Influence, Steadiness, Conscientiousness) questionnaire.
work recommendation system.
5. The method of claim 4,
The response input module is
a monitor capable of displaying the questions of the disposition analysis questionnaire; and
Further comprising; an input member for the subject to input response information to the question;
The sample input module is
a photographing camera installed movably along the edge of the monitor and photographing the face of the subject to which the response information is input by manipulating the input member;
a driving unit for reciprocating the photographing camera along an edge of the monitor; and
An image selection unit for providing an image of the front face of the subject from among the images captured by the photographing camera to the face analysis unit;
work recommendation system.
5. The method of claim 4,
The response input module is
a monitor capable of displaying the questions of the disposition analysis questionnaire; and
Further comprising; an input member for the subject to input response information to the question;
The sample input module is
a rotation rod having one end rotatably installed at the edge of the monitor and extending a predetermined length in the central direction of the monitor;
a photographing camera installed at the other end of the rotating rod and photographing the face of the subject to input the response information by manipulating the input member;
a rotating unit for rotating the rotating rod for each preset unit time so that the photographing camera is located in the center of the monitor; and
An image selection unit for providing an image of the front face of the subject from among the images captured by the photographing camera to the face analysis unit;
work recommendation system.
an image input step of collecting the face image of the subject through an image input module;
A face analysis step of analyzing the feature points of the subject's face based on the face image of the subject, and comparing and analyzing the analyzed facial feature point information with pre-stored reference facial feature information for each personality type to determine the personality type of the subject ;
an information input step of collecting response information of the examinee to the questionnaire for recommended task research corresponding to the personality type of the examinee determined in the face analysis step from among the pre-stored recommended task research questionnaires for business recommendation; and
Including; a task recommendation step of analyzing the response information collected in the information input step to recommend a task suitable for the subject to be tested;
How to recommend work.

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