Analytical device, analytical system, analytical method, program, and workwear

Abstract

To provide an analytical device, an analytical system, an analytical method, a program, and workwear capable of suppressing occurrence of errors in associating a worker with a work content.SOLUTION: The analytical device includes: image acquisition means for acquiring an image that includes a worker and a marker attached to the worker and indicating an identifier unique to the worker; identification means for identifying the worker based on the identifier; specification means for specifying a work content based on a position of the marker; and output means for outputting data that includes the identified worker and the specified work content associated with each other.SELECTED DRAWING: Figure 6

Description

[Technical Field]

[0001] The present disclosure relates to an analysis device, an analysis system, an analysis method, a program, and work clothes. [Background technology]

[0002] Patent Document 1 discloses an image processing device that identifies the work content of a worker by attaching a marker to the worker, determining the trajectory of the marker's movement, and comparing the characteristics of the trajectory with the characteristics of a reference trajectory that is stored in advance for each work. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent Publication No. 2000-180162 Summary of the Invention [Problem to be solved by the invention]

[0004] In a workplace where many workers come and go and each perform a wide variety of tasks simultaneously, workers often wear the same or similar work clothes, which can lead to errors in identifying workers based on their appearance. As a result, there is a problem of errors in linking workers to their tasks. However, Patent Document 1 does not disclose a method for identifying workers.

[0005] An example of an object of the present disclosure is to provide an analysis device, an analysis system, an analysis method, a program, and work clothes that solve the above-mentioned problems. [Means for solving the problem]

[0006] An analysis device according to one aspect of the present disclosure includes an image acquisition means for acquiring an image including a worker and a marker attached to the worker that indicates an identifier unique to the worker, an identification means for identifying the worker based on the identifier, an identification means for identifying work content based on the position of the marker, and an output means for outputting data including the identified worker and the identified work content that are linked to each other.

[0007] An analysis system according to one aspect of the present disclosure includes an imaging device that photographs a worker and acquires an image including the worker and a marker attached to the worker that indicates an identifier unique to the worker; an analysis device that identifies the worker based on the identifier, specifies the work content based on the position of the marker, and outputs data including the identified worker and the specified work content that are linked to each other; and a terminal that presents the data to a user.

[0008] An analysis method according to one aspect of the present disclosure includes acquiring an image including a worker and a marker attached to the worker that indicates an identifier unique to the worker, identifying the worker based on the identifier, specifying a work content based on a position of the marker, and presenting data including the identified worker and the specified work content that are linked to each other.

[0009] A program according to one aspect of the present disclosure is a program for causing a computer to perform the following operations: acquiring an image including a worker and a marker attached to the worker that indicates an identifier unique to the worker; identifying the worker based on the identifier; specifying a work content based on the position of the marker; and presenting data including the identified worker and the specified work content that are linked to each other.

[0010] A work suit according to one aspect of the present disclosure comprises a suit body to be worn by a worker, and a marker attached to the suit body and indicating an identifier unique to the worker. [Effects of the Invention]

[0011] According to some embodiments of the present disclosure, a worker is identified based on an identifier unique to the worker, thereby making it possible to prevent errors from occurring in linking a worker to work content. [Brief explanation of the drawings]

[0012] [Figure 1] 1 illustrates an analysis system according to some embodiments of the present disclosure. [Figure 2] An example will be shown in which an analysis system according to some embodiments of the present disclosure is applied to an application in which the work content, efficiency, etc. of a worker performing multiple tasks in a work area of ​​a logistics warehouse is analyzed. [Figure 3] FIG. 10 illustrates an example in which the marker is a two-dimensional barcode according to some embodiments of the present disclosure. [Figure 4] FIG. 10 illustrates another example in which the marker is a two-dimensional barcode according to some embodiments of the present disclosure. [Figure 5] FIG. 1 illustrates a hardware configuration of an analysis device according to some embodiments of the present disclosure. [Figure 6] FIG. 1 is a block diagram illustrating an analysis device according to some embodiments of the present disclosure. [Figure 7] FIG. 10 is a diagram illustrating an example structure of ID data according to some embodiments of the present disclosure. [Figure 8] FIG. 10 illustrates an example structure of task data according to some embodiments of the present disclosure. [Figure 9] FIG. 1 is a diagram showing a flow of an analysis process performed by an analysis device according to some embodiments of the present disclosure. [Figure 10] 1A and 1B are diagrams illustrating examples of analysis results obtained by an analysis device according to some embodiments of the present disclosure. [Figure 11] FIG. 10 is a diagram illustrating a flow for identifying work content by an analysis device according to some embodiments of the present disclosure. [Figure 12] FIG. 1 is a schematic diagram of a process for identifying work content according to some embodiments of the present disclosure. [Figure 13]10A and 10B are diagrams illustrating an example in which the markers are LEDs according to some embodiments of the present disclosure. [Figure 14] FIG. 1 illustrates an example configuration of an analysis device according to some embodiments of the present disclosure. [Figure 15] FIG. 1 is a diagram illustrating a process flow by an analysis device according to some embodiments of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0013] Hereinafter, several embodiments of the present disclosure will be described with reference to the drawings.

[0014] 1 shows an analysis system 1 according to some embodiments of the present disclosure. The analysis system 1 includes an analysis device (task analysis device) 10, a user terminal (operation unit, terminal) 20, and an imaging device (image acquisition unit) 30.

[0015] The imaging device 30 may be a camera. The imaging device 30 may be placed in a workplace so as to capture the entire area in which a worker moves. The imaging device captures an object to be analyzed, such as a worker, and acquires video data including a plurality of image frames (images) arranged in chronological order.

[0016] The analysis device 10 may be an information processing device such as a server. The analysis device 10 acquires video data from the imaging device 30. The analysis device 10 analyzes the video data and obtains an analysis result that links the worker with the work content. The analysis device 10 outputs the analysis result to the user terminal 20.

[0017] The user terminal 20 may be a personal computer configured with a keyboard, mouse, monitor, etc. The user terminal 20 acquires information input by the user U by operating the keyboard, mouse, etc. The user terminal 20 also presents information such as analysis results to the user U via a monitor, etc.

[0018] FIG. 2 shows an example in which the analysis system 1 is applied to analyze the work content and efficiency of workers P1 and P2 who perform multiple tasks in a work area of ​​a logistics warehouse S. In the example of FIG. 2, shelves and work desks are arranged in the logistics warehouse S. Workers P1 and P2 are working in the logistics warehouse S. Worker P1 is working to carry packages. Worker P2 is working to store the packages on the shelves. Two imaging devices 30A (30) and 30B (30) are arranged in the logistics warehouse S. In the example of FIG. 2, imaging device 30A is photographing worker P1, who is the subject of analysis. Imaging device 30B is photographing worker P2, who is another subject of analysis. Imaging device 30A may photograph both worker P1 and worker P2.

[0019] The analysis device 10 analyzes image data that shows the worker P1, identifies the worker P1, locates the position of the worker P1, and determines that the work being performed by the worker P1 is carrying luggage. Similarly, the analysis system 1 analyzes image data that shows the worker P2, identifies the worker P2, locates the position of the worker P2, and determines that the work being performed by the worker P2 is storing luggage on a shelf. The analysis device 10 may analyze image data that shows the workers P1 and P2.

[0020] The analysis system 1 is not limited to application to a work site in a logistics warehouse, but may also be applied to other work sites where many workers come and go and each perform a wide variety of tasks simultaneously, such as an assembly plant or a construction site.

[0021] FIG. 3 shows details of worker P1 shown in FIG. 2. FIG. 4 shows details of worker P2 shown in FIG. 2. FIGS. 3 and 4 show examples where the markers are two-dimensional barcodes according to some embodiments of the present disclosure. Two-dimensional barcodes T1R and T1L are attached to worker P1. Two-dimensional barcodes T2R and T2L are attached to worker P2. The two-dimensional barcodes T1R, T1L, T2R, and T2L will be referred to as two-dimensional barcode T unless otherwise distinguished.

[0022] The two-dimensional barcode T1R is attached to the right shoulder of the worker P1, i.e., a position corresponding to the right shoulder of the work uniform (main body, clothing) E1 worn by the worker P1. The two-dimensional barcode T1L is attached to the left shoulder of the worker P1, i.e., a position corresponding to the left shoulder of the work uniform E1 worn by the worker P1. More specifically, the two-dimensional barcode T1R is attached to a position corresponding to the right shoulder joint of the worker P1. Furthermore, the two-dimensional barcode T1L is attached to a position corresponding to the left shoulder joint of the worker P1.

[0023] The two-dimensional barcode T2R is attached to the right shoulder of the worker P2, i.e., a position corresponding to the right shoulder of the work uniform (main body, clothing) E2 worn by the worker P2. The two-dimensional barcode T2L is attached to the left shoulder of the worker P2, i.e., a position corresponding to the left shoulder of the work uniform E2 worn by the worker P2. More specifically, the two-dimensional barcode T2R is attached to a position corresponding to the right shoulder joint of the worker P2. The two-dimensional barcode T2L is attached to a position corresponding to the left shoulder joint of the worker P2.

[0024] The position at which the two-dimensional barcode T is attached is not limited to the position corresponding to the shoulder joint. The two-dimensional barcode T may be attached to a position corresponding to another joint, such as the elbow or knee. The position of the two-dimensional barcode T may be another position that serves as a feature point for the worker's posture recognition processing. The two-dimensional barcodes T1 and T2 may be QR Code (registered trademark). The two-dimensional barcodes T1 and T2 each have a different unique pattern. Information indicating a worker ID (identifier, worker identifier) ​​and a joint ID (feature point identifier, joint identifier) ​​is embedded in the two-dimensional barcode T.

[0025] The worker ID is an identifier specific to each worker and is different for each worker. Therefore, the worker can be identified from the worker ID. The joint ID indicates the type of joint where the two-dimensional barcode T is attached.

[0026] For example, the two-dimensional barcode T1R has embedded therein a worker ID indicating worker P1 and a joint ID indicating the right shoulder (right shoulder joint). The two-dimensional barcode T1L has embedded therein a worker ID indicating worker P1 and a joint ID indicating the left shoulder (left shoulder joint). The worker ID in the two-dimensional barcode T1L is the same as the worker ID in the two-dimensional barcode T1R. That is, the two-dimensional barcodes T1 and T2 each contain the same identifier for identifying worker P1.

[0027] The two-dimensional barcode T2R has embedded therein a worker ID indicating worker P2 and a joint ID indicating the right shoulder (right shoulder joint). The two-dimensional barcode T2L has embedded therein a worker ID indicating worker P2 and a joint ID indicating the left shoulder (left shoulder joint). The worker ID in the two-dimensional barcode T2L is the same as the worker ID in the two-dimensional barcode T2R. The worker IDs in the two-dimensional barcodes T2R and T2L are different from the worker IDs in the two-dimensional barcodes T1R and T1L.

[0028] Fig. 5 is a diagram showing the hardware configuration of an analysis device 10 according to some embodiments of the present disclosure. As shown in Fig. 5, the analysis device 10 is a computer including various pieces of hardware such as a CPU (Central Processing Unit) 101, a ROM (Read Only Memory) 102, a RAM (Random Access Memory) 103, an HDD (Hard Disk Drive) 104, a communication module 105, and a database 106. The user terminal 20 may also have a similar hardware configuration.

[0029] 6 illustrates an analysis device 10 according to some embodiments of the present disclosure. The analysis device 10 includes a control unit 11 and a storage unit 12. The control unit 11 includes a video data acquisition unit 111, an ID identification unit 112, an operation identification unit 113, a recording unit 114, a determination unit 115, an analysis unit 116, and an input / output unit 117.

[0030] The analysis device 10 performs the functions of a video data acquisition unit 111, an ID identification unit 112, a task identification unit 113, a recording unit 114, a determination unit 115, an analysis unit 116, and an input / output unit (output unit) 117 by having the CPU execute a processing program stored in the memory. The memory unit 12 may be configured as a storage device such as a hard disk. The memory unit 12 has an ID data memory area 121 that stores ID data, and a task data memory area 122 that stores task data.

[0031] The video data acquisition unit 111 acquires video data from the imaging device 30 .

[0032] The ID identification unit 112 analyzes the video data to identify the position of the two-dimensional barcode attached to the worker. The ID identification unit 112 also analyzes the video data to recognize information embedded in the two-dimensional barcode and identify ID information including the worker ID and the joint ID. The ID identification unit 112 generates ID data including the positions of the two-dimensional barcodes and the ID information that are linked to each other. The ID data may include only one of the position of the two-dimensional barcode and the ID information. The ID data may also include at least one of the position of the two-dimensional barcode and the ID information, as well as other information.

[0033] The task identification unit 113 identifies the location of the worker and the task content of the worker from the video data and the ID data. The task identification unit 113 may identify only one of the location of the worker and the task content of the worker. More specifically, the task identification unit 113 identifies the task content based at least on the position of the two-dimensional barcode. The task identification unit 113 identifies the type of joint based on the joint ID. The task identification unit 113 identifies the positions of the worker's joints from the video data by image recognition. The task identification unit 113 identifies the task content based on at least some of the positions of the worker's joints identified by image recognition and the positions of the worker's joints identified based on the position of the two-dimensional barcode. The task identification unit 113 replaces, among the positions of the worker's joints identified by image recognition, positions that indicate the same joints as the joints of the worker identified based on the position of the two-dimensional barcode with the positions of the worker's joints identified based on the position of the two-dimensional barcode.

[0034] The task identification unit 113 uses the worker ID to distinguish the positions of the joints identified from the video data for each worker. The task identification unit 113 generates task data including the positions of the workers and the task details of the workers that are linked to each other. The task data may include only one of the positions of the workers and the task details of the workers. The task data may also include at least one of the positions of the workers and the task details of the workers, as well as other information.

[0035] The recording unit 114 records the ID data in the ID data storage area 121 of the storage unit 12. The recording unit 114 records the work data in the work data storage area 122 of the storage unit 12.

[0036] The determination unit 115 determines whether the analysis of the video data is complete.

[0037] The analysis unit 116 analyzes the work content of the workers from the ID data and the work data, and generates analysis results such as data in which the work content for each worker is arranged in chronological order.

[0038] The input / output unit 117 transmits and receives various information to and from the user terminal 20. The input / output unit 117 transmits data indicating the analysis results to the user terminal 20. A user who uses the user terminal 20 can analyze the efficiency of the workers and the like based on the analysis results.

[0039] 7 is a diagram illustrating an example of the structure of ID data according to some embodiments of the present disclosure. As described above, the ID data indicates the position of the two-dimensional barcode and ID information, and is generated based on the identification result by the ID identification unit 112.

[0040] In the example of FIG. 7, the frame number is a number for identifying a frame image in the video data. The time indicates the time when the frame image was captured. The position X and position Y indicate the position of the two-dimensional barcode, i.e., the position of the worker. The position X may be longitude. The position Y may be latitude. The position X and position Y may be coordinates in one direction with a specific position as the origin and coordinates in a direction perpendicular to the one direction with the specific position as the origin, respectively. The worker ID is an identifier indicating the worker. The worker ID may be a number indicating the worker. The worker ID may be the name of the worker.

[0041] 8 is a diagram illustrating an example structure of task data according to some embodiments of the present disclosure. As described above, the task data indicates the location of the worker and the task content, and is generated based on the identification result by the task identification unit 113.

[0042] In the example of FIG. 8, the frame number, time, position X, and position Y are the same as those shown in the example of FIG. 3. Height H indicates the height position of the two-dimensional barcode, i.e., the height position of the worker. Position H may be altitude. Position H may also be a height coordinate with a specific position as the origin. The work type indicates the type of work content. Positions X and Y may be the position of the worker (for example, the intersection of the central axis of the body and the floor), width W may be the width of the worker (for example, shoulder width), and height H may be the height of the worker (for example, height). The work identification unit 113 may identify positions X and Y and width W of the worker from the video data by image recognition.

[0043] The flow of analysis processing according to some embodiments of the present disclosure will be described with reference to Fig. 9. Fig. 9 is a diagram showing the flow of analysis processing by the analysis device 10 according to some embodiments of the present disclosure. The analysis processing may be executed in response to a start instruction from a user via the user terminal 20.

[0044] First, the control unit 11 (video data acquisition unit 111) acquires video data including a plurality of frame images showing the worker to be analyzed from the imaging device 30 (step S1).

[0045] Next, the control unit 11 (ID identification unit 112, task identification unit 113) acquires one frame of image data from the acquired video data in the order of shooting time (step S2). In addition, the control unit 11 (recording unit 114) stores the time when the acquired one frame image was captured in the ID data storage area 121 and task data storage area 122 of the storage unit 12.

[0046] Next, the control unit 11 (ID identification unit 112) applies image recognition technology or the like to the acquired one frame image to identify the position of the two-dimensional barcode and the ID information (step S3). The control unit 11 (recording unit 114) stores the identification result in the ID data storage area 121 of the storage unit 12.

[0047] Next, the control unit 11 (task identification unit 113) applies image recognition technology or the like to the acquired one frame image to identify the worker's position and the task content (step S4). The control unit 11 (recording unit 114) stores the identification result in the task data storage area 122 of the storage unit 12.

[0048] Next, control unit 11 (determination unit 115) determines whether analysis of all frame images included in the video data has been completed (step S5). If control unit 11 determines that analysis of all frame images has not been completed (NO in step S5), it repeats the processes of steps S2 to S4. If control unit 11 determines that analysis of all frame images to be analyzed has been completed (YES in step S5), the process proceeds to step S6.

[0049] Next, the control unit 11 (analysis unit 116) analyzes the work of the worker based on the ID data and the work data (step S6).

[0050] Next, the control unit 11 (input / output unit 117) transmits the analysis results to the user terminal 20 (step S7). When steps S1 to S7 are completed, the analysis process ends.

[0051] An example of an analysis result by the analysis device 10 according to some embodiments of the present disclosure will be described with reference to FIG. 10. FIG. 10 shows an example of the analysis result displayed on the user terminal 20. In the example of FIG. 10, the analysis result includes graphs G1 and G2 that chronologically arrange the work contents. The graphs G1 and G2 are created for each worker. The graph G1 shows that worker P1 performed work A, work B, work C, work A, and work C in that order from 9:00 AM to 6:00 PM. The graph G2 shows that worker P2 performed work B, work A, work C, work B, and work A in that order from 9:00 AM to 6:00 PM.

[0052] Next, the process for identifying the work content in step S4 of Fig. 9 will be described in more detail with reference to Figs. 11 and 12. Fig. 11 is a diagram showing a flow for identifying the work content by the analysis device 10 according to some embodiments of the present disclosure. Fig. 12 is a schematic diagram of the process for identifying the work content according to some embodiments of the present disclosure.

[0053] First, the task identification unit 113 applies image recognition technology or the like to an image of the worker appearing in a frame image included in the video data to identify the positions of multiple joints of the worker (step S41). The number of joints identified by the task identification unit 113 is not particularly limited. The task identification unit 113 may identify all of the joints included in the image of the worker, or may identify some of the joints included in the image of the worker. In the example of part (A) of FIG. 12, circles indicate the positions of joints identified by image recognition. A square indicates a two-dimensional barcode attached to a position corresponding to the worker's right shoulder joint.

[0054] Next, the task identification unit 113 replaces, among the positions of the worker's multiple joints identified by image recognition, the positions that indicate the same joints as the joints of the worker identified based on the positions of the two-dimensional barcodes included in the ID data with the positions of the worker's joints identified based on the positions of the two-dimensional barcodes (step S42). Using the positions of the worker's joints identified based on the positions of the two-dimensional barcodes improves the accuracy of identifying the joint positions. Furthermore, because the type of joint can be identified using the joint ID, the occurrence of errors in identifying the joints can be reduced. In the example of part (B) of FIG. 12, the star indicates the position of the worker's right shoulder joint identified based on the position of the two-dimensional barcode. The dotted circle indicates the position of the worker's right shoulder joint identified by image recognition. The position of the worker's right shoulder joint identified by image recognition is excluded and therefore will not be used in subsequent processing.

[0055] Next, the task identification unit 113 generates a human figure by connecting the positions of the joints identified in step S42, and identifies the posture of the worker based on the shape of the generated human figure (step S43). The task identification unit 113 may further identify the position of the worker based on the ID information in the ID data. Part (C) of Figure 12 shows an example of a human figure formed by connecting the positions of the joints.

[0056] Next, the task identification unit 113 identifies the task content (task type) of the worker based on the posture characteristics identified in step S43 (step S44). The task identification unit 113 may compare the identified posture with a plurality of reference posture patterns, and identify the task content associated with the posture pattern that is closest to the identified posture as the task content of the worker. When steps S41 to S44 are completed, the process for identifying the task content ends.

[0057] Several embodiments of the present disclosure have been described above. According to several embodiments of the present disclosure, workers are identified using ID information from two-dimensional barcodes rather than appearance features, thereby reducing errors in identifying workers even when workers are wearing the same or similar work clothes. Furthermore, joint points are linked to a human figure for each worker based on the position and ID information of the two-dimensional barcode, and the position and posture of each worker are recognized. This makes it easy to identify the work content of each worker, even when workers are in close proximity to each other. Therefore, in a workplace where many workers are coming and going and each worker is performing a variety of tasks simultaneously, it is possible to improve the accuracy of work content recognition while reducing errors in linking workers to their work content by a device that analyzes the worker's work content.

[0058] In some embodiments of the present disclosure, the task identification unit 113 may not need to identify the positions of the joints by applying image recognition technology, etc. In this case, the task identification unit 113 may generate a human figure by connecting the positions of multiple joints identified by the positions of multiple two-dimensional barcodes, and identify the task content based on the shape of the generated human figure.

[0059] The marker is not limited to a two-dimensional barcode, but may be in any other form that can indicate the worker ID and joint ID that can be recognized by an imaging device such as a camera.

[0060] 13 illustrates an example in which the markers are LEDs according to some embodiments of the present disclosure. In the example of FIG. 13, LED 51 is attached to a position corresponding to the right shoulder joint of work clothing (clothing main body, clothing) E3 worn by worker P3. LED 52 is attached to a position corresponding to the left shoulder joint of work clothing (clothing main body, clothing) E3 worn by worker P3.

[0061] Each of the LEDs 51 and 52 may alternately emit light in a unique color indicating a worker ID and a unique color indicating a joint ID. More specifically, the LED 51 may alternately emit light in a unique color indicating a worker ID of worker P3 and a unique color indicating a joint ID of the right shoulder. The LED 52 may alternately emit light in a unique color indicating a worker ID of worker P3 and a unique color indicating a joint ID of the left shoulder. Each of the LEDs 51 and 52 may have two or more LEDs, one of which may emit light in a unique color indicating a worker ID and the other may emit light in a unique color indicating a joint ID. The color indicating the worker ID of worker P3 is different from the color indicating the joint ID of the right shoulder and the color indicating the joint ID of the left shoulder. Furthermore, the color indicating the joint ID of the right shoulder is different from the color indicating the joint ID of the left shoulder.

[0062] Each of the LEDs 51 and 52 may alternately flash a pattern indicating the worker ID and a unique color pattern indicating the joint ID. More specifically, the LED 51 alternately flashes a unique pattern indicating the worker ID of worker P3 and a unique color pattern indicating the joint ID of the right shoulder. The LED 52 alternately flashes a unique pattern indicating the worker ID of worker P3 and a unique color pattern indicating the joint ID of the left shoulder. Each of the LEDs 51 and 52 may have two or more LEDs, one of which flashes in a pattern indicating the worker ID and the other flashes in a pattern indicating the joint ID. The pattern indicating the worker ID of worker P3 is different from the patterns indicating the joint IDs of the right and left shoulders. The pattern indicating the joint ID of the right shoulder is different from the pattern indicating the joint ID of the left shoulder.

[0063] Each of the LEDs 51 and 52 may emit light in a unique color indicating the worker ID and flash in a unique pattern of colors indicating the joint ID. Conversely, each of the LEDs 51 and 52 may flash in a unique pattern indicating the worker ID and emit light in a unique color indicating the joint ID.

[0064] Fig. 14 is a diagram illustrating an example of the configuration of an analysis device 10 according to some embodiments of the present disclosure. Fig. 15 is a diagram illustrating an example of a processing flow performed by the analysis device 10 illustrated in Fig. 14.

[0065] Analysis device 10 realizes the functions of at least a video data acquisition unit (image acquisition means) 111, an ID identification unit (identification means) 112, a task specification unit (specification means) 113, and an input / output unit (output means) 117.

[0066] The video data acquisition unit 111 acquires an image including a worker and a marker attached to the worker that indicates an identifier unique to the worker (step S101). The ID identification unit 112 identifies the worker based on the identifier unique to the worker (step S102). The task identification unit 113 identifies the task content based on the position of the marker (step S103). The input / output unit 117 outputs data including the identified worker and the identified task content that are linked to each other (step S104).

[0067] Each of the above-mentioned devices has a computer system built in. The steps of each of the above-mentioned processes are stored in the form of a program on a computer-readable recording medium, and the computer reads and executes this program to perform the above-mentioned processes. Here, computer-readable recording medium refers to a magnetic disk, magneto-optical disk, CD-ROM, DVD-ROM, semiconductor memory, etc. Alternatively, the computer program may be distributed to a computer via a communication line, and the computer that receives the program may execute the program.

[0068] The program may also be a program for realizing some of the functions described above, or may be a so-called differential file (differential program) that can realize the functions described above in combination with a program already recorded in the computer system.

[0069] Although the present disclosure has been described above with reference to the embodiments, the present disclosure is not limited to the above-described embodiments. Various modifications that can be understood by those skilled in the art can be made to the configuration and details of the present disclosure within the scope of the present disclosure. Furthermore, each embodiment can be combined with other embodiments as appropriate.

[0070] Some or all of the above-described embodiments can be described as, but are not limited to, the following supplementary notes.

[0071] (Appendix 1) an image acquisition means for acquiring an image including a worker and a marker attached to the worker that indicates an identifier unique to the worker; an identification means for identifying the worker based on the identifier; an identification means for identifying a task content based on the position of the marker; an output means for outputting data including the identified workers and the specified work contents that are linked to each other; An analytical device comprising:

[0072] (Appendix 2) the identification means identifies the type of joint based on the marker, which further indicates the type of joint at the attachment position; 2. The analytical device of claim 1.

[0073] (Appendix 3) the specifying means specifies the positions of the joints of the worker based on the positions of the markers attached to the positions corresponding to the joints of the worker. 3. The analytical device of claim 1 or 2.

[0074] (Appendix 4) the identifying means identifies positions of a plurality of joints of the worker from the image by image recognition; the identification means identifies the task content based on at least some of the positions of the joints of the worker identified by image recognition and the positions of the joints of the worker identified based on the positions of the markers. 4. The analytical device of claim 3.

[0075] (Appendix 5) the identification means replaces, among the positions of the joints of the worker identified by image recognition, a position indicating the same joint as the joint of the worker identified based on the position of the marker with the position of the joint of the worker identified based on the position of the marker. 5. The analytical device of claim 4.

[0076] (Appendix 6) 6. The analytical device of claim 1, wherein the marker is a two-dimensional barcode.

[0077] (Appendix 7) 6. The analytical device according to claim 1, wherein the marker is a light-emitting means that emits light in a color specific to the operator.

[0078] (Appendix 8) 6. The analytical device according to claim 1, wherein the marker is a light-emitting means that emits light in a pattern specific to the operator.

[0079] (Appendix 9) an imaging device that photographs a worker and acquires an image including the worker and a marker attached to the worker that indicates an identifier unique to the worker; an analysis device that identifies the worker based on the identifier, specifies the work content based on the position of the marker, and outputs data including the identified worker and the specified work content that are linked to each other; a terminal that presents the data to a user; A system comprising:

[0080] (Appendix 10) acquiring an image including a worker and a marker attached to the worker indicating a unique identifier for the worker; identifying the worker based on the identifier; Identifying a task based on the position of the marker; Presenting data including the identified workers and the specified work contents linked to each other; Analytical methods including:

[0081] (Appendix 11) acquiring an image including a worker and a marker attached to the worker indicating a unique identifier for the worker; identifying the worker based on the identifier; Identifying a task based on the position of the marker; Presenting data including the identified workers and the specified work contents linked to each other; A program that causes a computer to execute the following.

[0082] (Appendix 12) A clothing body to be worn by a worker; a marker attached to the clothing body and indicating an identifier unique to the worker; Work clothes equipped with.

[0083] Supplements corresponding to Supplements 2 to 8 subordinate to Supplement 1 may also be added to each of Supplements 9 to 11 by appropriately modifying the wording. [Explanation of symbols]

[0084] 1: Analysis system 10: Analyzer 11: Control unit 11 12: Storage section 12 20: User terminal 30, 30A, 30B: Imaging device 51, 52: LED 11: Control unit 101:CPU 102:ROM 103:RAM 104: HDD 105: Communication module 106: Database 111: Video data acquisition unit 112: ID identification unit 113: Work Specification Department 114: Recording section 115: Judgment section 116: Analysis Department 117: Input / output section 121: ID data storage area 122: Working data storage area E1, E2, E3: Work clothes P, P1, P2: Worker S:Logistics warehouse T, T1R, T1L, T2R, T2L: 2D barcode U:User

Claims

1. an image acquisition means for acquiring an image including a worker and a marker attached to the worker that indicates an identifier unique to the worker; an identification means for identifying the worker based on the identifier; an identification means for identifying a task content based on the position of the marker; an output means for outputting data including the identified workers and the specified work contents that are linked to each other; An analytical device comprising:

2. the identification means identifies the type of joint based on the marker, which further indicates the type of joint at the attachment position; The analytical device of claim 1 .

3. the specifying means specifies the positions of the joints of the worker based on the positions of the markers attached to the positions corresponding to the joints of the worker. The analytical device according to claim 1 or 2.

4. the identifying means identifies positions of a plurality of joints of the worker from the image by image recognition; the identification means identifies the task content based on at least some of the positions of the joints of the worker identified by image recognition and the positions of the joints of the worker identified based on the positions of the markers. The analytical device according to claim 3 .

5. the identification means replaces, among the positions of the joints of the worker identified by image recognition, a position indicating the same joint as the joint of the worker identified based on the position of the marker with the position of the joint of the worker identified based on the position of the marker. The analytical device according to claim 4 .

6. The analysis device according to claim 1 or 2, wherein the marker is a two-dimensional barcode.

7. an imaging device that photographs a worker and acquires an image including the worker and a marker attached to the worker that indicates an identifier unique to the worker; an analysis device that identifies the worker based on the identifier, specifies the work content based on the position of the marker, and outputs data including the identified worker and the specified work content that are linked to each other; a terminal that presents the data to a user; An analysis system comprising:

8. acquiring an image including a worker and a marker attached to the worker indicating a unique identifier for the worker; identifying the worker based on the identifier; Identifying a task based on the position of the marker; Presenting data including the identified workers and the specified work contents linked to each other; Analytical methods including:

9. acquiring an image including a worker and a marker attached to the worker indicating a unique identifier for the worker; identifying the worker based on the identifier; Identifying a task based on the position of the marker; Presenting data including the identified workers and the specified work contents linked to each other; A program that causes a computer to execute the following.

10. A clothing body to be worn by a worker; a marker attached to the clothing body and indicating an identifier unique to the worker; Work clothes equipped with.

Images