VIDEO MANAGEMENT SYSTEM, VIDEO MANAGEMENT METHOD, AND VIDEO MANAGEMENT PROGRAM

Abstract

In the present invention, a video analysis system comprises an acquisition unit, a work information acquisition unit, an identification unit, a conversion unit, and an output unit. The acquisition unit acquires a video obtained by capturing a work area. The work information acquisition unit acquires information on work contents. The identification unit identifies an article and / or work by a worker shown in the video. The conversion unit, on the basis of the identification result and the information on work contents, converts the video into a video obtained by processing at least a portion of a body part with which the worker can be identified. The output unit outputs the converted video.

Description

Video management system, video management method, and recording medium

[0001] The present disclosure relates to a video management system and the like.

[0002] In factories, for example, analysis of work within a manufacturing process is conducted to improve work efficiency, quality, and safety. The results of the work analysis are used, for example, by a manager who manages the manufacturing process to improve work procedures. Work analysis is performed, for example, by the manager viewing video footage of the work and confirming whether the work is being performed correctly in accordance with the work procedures. Furthermore, when video is used to analyze work, it may be required that individuals not be identified in the video footage in order to protect the personal information of workers.

[0003] The motion analysis system of Patent Document 1 extracts scenes in which a worker performs the motion indicated by the motion information from a video captured of the worker's motion, and then displays the extracted video.

[0004] The monitoring system of Patent Document 2 reduces the ability to identify individual workers by reducing the image quality of images showing the workers.

[0005] JP 2019-125023 A JP 2016-111603 A

[0006] With the techniques described in Patent Documents 1 and 2, when work analysis is enabled, it may be difficult to prevent identification of the worker.

[0007] In order to solve the above-mentioned problems, the present disclosure aims to provide a video management system and the like that enables analysis of work while obtaining video that does not identify workers.

[0008] In order to solve the above problems, the video management system of the present disclosure includes an acquisition means for acquiring video footage of a work area, a work information acquisition means for acquiring information regarding the work content, an identification means for identifying at least one of the work performed by the worker and the item shown in the video, a conversion means for converting the video into a video in which at least a part of the body part that can identify the worker has been processed based on the results of the identification and the information regarding the work content, and an output means for outputting the converted video.

[0009] The video management method disclosed herein acquires video footage of a work area, acquires information about the work content, identifies at least one of the work being performed by the worker and the items shown in the video, and, based on the results of the identification and the information about the work content, converts the video into video in which at least some of the body parts that can identify the worker have been processed, and outputs the converted video.

[0010] The recording medium of the present disclosure non-temporarily records a video management program that causes a computer to execute the following processes: acquiring video footage of a work area; acquiring information about the work content; identifying at least one of the work being performed by the worker and the item being captured in the video; converting the video into video that has been processed to remove at least a portion of the body part that can identify the worker based on the results of the identification and the information about the work content; and outputting the converted video.

[0011] According to the present disclosure, it is possible to obtain video that does not identify the worker while enabling analysis of the work.

[0012] FIG. 1 is a diagram illustrating an example of the configuration of a video management system according to an embodiment of the present disclosure. FIG. 2 is a diagram illustrating an example of a video captured of a work area according to an embodiment of the present disclosure. FIG. 3 is a diagram illustrating an example of a video obtained by processing a video captured of a work area according to an embodiment of the present disclosure. FIG. 4 is a diagram illustrating an example of a video captured of a work area according to an embodiment of the present disclosure. FIG. 5 is a diagram illustrating an example of a video obtained by processing a video captured of a work area according to an embodiment of the present disclosure. FIG. 6 is a diagram illustrating an example of an operation flow of a video management system according to an embodiment of the present disclosure. FIG. 7 is a diagram illustrating an example of the hardware configuration of a video management system according to an embodiment of the present disclosure.

[0013] An embodiment of the present disclosure will be described in detail with reference to the drawings. Fig. 1 is a diagram showing an example of the configuration of a video management system 10. The video management system 10 basically includes an acquisition unit 11, a work information acquisition unit 12, a recognition unit 13, a conversion unit 14, and an output unit 15. The video management system 10 also includes, for example, a storage unit 16.

[0014] The video management system 10 is a system that converts, for example, video of a work area into video in which body parts that can identify a worker are processed while still allowing the work to be analyzed. For example, the video management system 10 converts video of a work area into video in which body parts that can identify a worker are not visible. That is, the video management system 10 converts video of a work area into video in which body parts that can identify a worker are hidden. For example, the video management system 10 converts video of a work area into video in which body parts that can identify a worker are replaced with objects, masked, or have reduced image quality. Video in which body parts that can identify a worker are replaced with line drawings may also include video in which the worker's body is replaced with a line drawing. A line drawing is, for example, an image in which the outline of a worker is depicted in the video. By converting video of a work area into video in which body parts that can identify a worker are not visible, it becomes difficult for a person viewing the video to identify the person in the video.

[0015] FIG. 2 is a diagram showing an example of a frame image included in a video of a work area. FIG. 3 is a diagram showing an example of an image of a frame included in a video of a work area before processing is performed to make the worker unidentifiable. In other words, the example image of FIG. 2 is an image before processing is performed to hide body parts that could identify the worker. In the example image of FIG. 2, a worker is assembling a product placed on a workbench. In the example image of FIG. 2, for example, the worker can be identified from the worker's face shown in the image.

[0016] FIG. 3 is a diagram showing an example of an image in which an image of a frame included in a video of a work area has been processed to make it impossible to identify the worker. The example image in FIG. 3 is an image in which the image in FIG. 2 has been processed to make it impossible to identify the worker. In the example image in FIG. 3, processing has been performed to replace the worker's body parts with line drawings. Therefore, in the example image in FIG. 3, a person viewing the image will not be able to identify the worker from the worker's face shown in the image. Furthermore, in the example image in FIG. 3, when analyzing the worker's hand movements, only the hand parts may be left in their unprocessed state.

[0017] For example, the video management system 10 uses image recognition to identify at least one of the worker's work and the object from the video of the work area. Then, based on the identification result and information on the work content, the video of the work area is converted into a video in which at least a part of the body part that can identify the worker is processed. Furthermore, for example, if the worker can be identified from the identified object, the video management system 10 converts the video of the work area into a video in which the body part where the worker is wearing the identifiable object is processed.

[0018] For example, if the work involves product assembly and all that is required for the analysis is the worker's hand movements, the video management system 10 converts the video of the work area into video in which parts other than the worker's hands are masked. Alternatively, if all that is required is to analyze that the work is being performed, the video management system 10 may convert the video of the work area into video in which the worker's body is replaced with a line drawing. For example, if the work procedure can be analyzed by knowing changes in standing position within the work area, the video management system 10 may convert the video of the work area into video in which the worker's body is replaced with a line drawing. In this way, by converting the video into video in which body parts not used in the analysis are hidden based on information about the content of the work, it is possible to convert the video into video in which the worker cannot be identified while still being able to analyze the work by viewing the video.

[0019] Here, a specific example of the configuration of the video management system 10 will be described.

[0020] The acquisition unit 11 acquires video of a work area. The video of work is, for example, video captured to capture work performed by a worker in the work area. The work area is, for example, an area in a factory manufacturing process where one or more workers perform designated work. The work performed by the worker is, for example, work related to product manufacturing. Work related to product manufacturing includes, for example, product assembly, product processing, product inspection, product packaging, product transportation, equipment operation, and storage shelf organization. The work performed by the worker may also include equipment inspection, equipment repair, or equipment assembly. Work related to product manufacturing may also include food preparation. Work related to product manufacturing is not limited to the above. Work performed by the worker may also include cleaning, driving, exercise, instructing others, guiding, security, medical procedures, dispensing medicine, and equipment operation. The work performed by the worker is not limited to the above.

[0021] The acquisition unit 11 acquires, for example, video of the work area captured by a camera installed in a position where the work area can be captured. If a monitoring system is present that monitors the work area, the acquisition unit 11 may acquire the video of the work area via a server of the monitoring system. Alternatively, the acquisition unit 11 may acquire the video of the work area via a storage medium.

[0022] The work information acquisition unit 12 acquires information related to work content. The work information acquisition unit 12 acquires information related to work content, for example, from a production management server that manages the work area. The information related to work content is, for example, information that makes it possible to extract what kind of video may be required when performing analysis using video. The information related to work content is, for example, information that makes it possible to identify at least one of the work to be analyzed and the body part to be analyzed. In other words, the information related to work content is, for example, information that makes it possible to identify the items that a person viewing the video wants to check from the video.

[0023] The information on the work content is, for example, information on at least one of the following: the purpose of the work, the type of work, the product to be worked on, the person performing the work, the tools used for the work, and the work procedure. The purpose of the work is information that can identify the body part to be analyzed, such as preparing parts to prepare for the work, assembling parts to create an intermediate product, obtaining inspection results, or transporting and storing on a shelf. For example, the purpose of the work is not limited to the above. The type of work is information that can identify the body part to be analyzed from the work content, such as preparation, reporting, assembly, inspection, transport, cleaning, or repair. The type of work is not limited to the above. The information on the work content may include at least one of the target of analysis and the purpose of the analysis using video footage of the work area. The target of analysis is, for example, information on at least one of the product to be analyzed, the person performing the work to be analyzed, the body part to be analyzed, the tools to be analyzed, and the work to be analyzed. The purpose of the analysis is, for example, information that can determine which body part and what movement to analyze from the purpose. The information on the work content is not limited to the above.

[0024] The identification unit 13 identifies at least one of the tasks and the objects captured in the video of the work area. For example, the identification unit 13 detects a worker captured in the video of the work area. Then, the identification unit 13 identifies the tasks being performed by the worker based on the time-series movements of the detected worker. For example, the identification unit 13 uses an identification model to identify the areas in which the tasks and the objects are captured in each frame image included in the video, and at least one of the tasks and the objects captured in the video of the work area. The identification unit 13 may also use the identification model to identify the positions in which each body part of the worker is captured in each frame image included in the video. For example, the identification unit 13 uses the identification model to identify the sections in which the tasks and the objects are captured in the video of the work area.

[0025] The identification unit 13 may identify at least one of the tasks and the items shown in the video of the work area based on the information on the work content. For example, the identification unit 13 may refer to the information on the work content and identify whether at least one of the tasks and the items indicated in the information on the work content is shown in the video of the work area. For example, if the information on the work content is a work procedure, the identification unit 13 may identify the tasks indicated in the work procedure from each frame image included in the video of the work area. Furthermore, the identification unit 13 may, for example, identify a section in the video of the work area where each task indicated in the work procedure is shown. Furthermore, the identification unit 13 may, for example, identify an item indicated in the work procedure from each frame image included in the video of the work area. For example, the identification unit 13 may identify a section in the video of the work area where each item indicated in the work procedure is shown.

[0026] The identification model may identify the outline of the worker's body shown in the video. Alternatively, the identification model may identify the position where a specific body part of the worker is shown in the video. The identification model may identify both the outline of the worker's body shown in the video and the position where the specific body part is shown. The specific body part is, for example, a body part that allows a person viewing the video to identify the worker shown in the video. The specific body part is, for example, the worker's face. The specific body part is not limited to the worker's face. The specific body part is set, for example, by the operator of the video management system 10 or the manager of the work area.

[0027] The identification model may identify an item worn by the worker. For example, the identification model identifies an item that can identify the worker from among the items worn by the worker. Examples of items that can identify the worker include a nameplate, the worker's identification number, a mark indicating a qualification held, a mark indicating a rank, apparel indicating a qualification held, and apparel indicating a rank. Examples of apparel indicating a rank include an armband, a badge, and a hat. The apparel indicating a rank is not limited to the above. An item that can identify the worker may also be a watch or an accessory that can make it possible to identify the individual from the owner. Furthermore, the items that can identify the worker are not limited to the above.

[0028] The identification model may identify the tools used by the worker. The identification model may also identify the product or equipment on which the worker is working. For example, if a worker can be identified from the tools he or she is using, the identification model may identify the tools he or she is using.

[0029] The discrimination model is, for example, a machine learning model using a neural network. The discrimination model is generated, for example, by learning the relationship between an image showing a worker and information indicating the area in which the worker is shown. The discrimination model may also be generated, for example, by learning the relationship between an image showing a worker and information indicating the area in which each of the worker's body parts is shown. The discrimination model may also be generated by learning the relationship between an image showing a worker, information indicating the area in which the worker is shown, and the type of work the worker is performing. The training data used to generate the discrimination model may be selected as appropriate depending on the discrimination target of the discrimination model. The discrimination model is generated, for example, in a system external to the video management system 10.

[0030] The identification unit 13 may use multiple identification models to identify the work and the object shown in the video. For example, the identification unit 13 uses an identification model that identifies an area in the video where the worker's body is shown to identify the area in the framed image where the worker is shown. Then, for example, the identification unit 13 identifies the position of the worker's hand in the framed image using an identification model that identifies the position of the worker's body part in the video. For example, the identification unit 13 identifies the position of the worker's hand in the framed image using an identification model that identifies the position of the worker's body in the video. Furthermore, the identification unit 13 identifies the object held by the worker at the identified position using an identification model that identifies the type of object. Furthermore, the identification unit 13 may use a different identification model for each work included in the workflow to identify at least one of the work performed by the worker and the object shown in the video.

[0031] The conversion unit 14 converts the video of the work area into video in which at least a portion of the body parts that can identify the worker have been processed, based on the identification result and information about the work content. The conversion unit 14, for example, converts the video of the work area into video in which at least a portion of the body parts that can identify the worker have been processed to hide at least a portion of the body parts that can identify the worker. The conversion unit 14 determines, for example, the body parts to be processed and the degree of processing, based on the identification result and information about the work content. Then, the conversion unit 14 converts the video of the work area into video in which at least a portion of the body parts that can identify the worker have been processed, based on the determined body parts to be processed and the degree of processing. Determining the degree of processing means, for example, determining at least one of the extent to which the body parts should be processed and the extent to which the body parts should be made invisible.

[0032] The conversion unit 14 converts the video of the work area into video in which at least some of the body parts that can identify the worker have been processed, for example, based on criteria for processing the body parts that can identify the worker. The criteria for processing the body parts that can identify the worker are set, for example, based on information about the work content. The criteria for processing the body parts that can identify the worker are set by the operator of the video management system 10 or the manager of the work area.

[0033] The criteria for processing body parts that can identify a worker are, for example, criteria for the body parts to be hidden by processing and the degree of processing to hide the body parts. The body parts to be hidden by processing may be multiple body parts. For example, if the work indicated in the work content is a work for which the purpose of analysis can be achieved if the worker's hand movements are known, the conversion unit 14 processes parts of the worker's body other than the hands. Furthermore, if the work indicated in the work content is a work that cannot be analyzed unless the entire body movements of the work are known, the conversion unit 14 processes, for example, the face of the worker's body.

[0034] Furthermore, the conversion unit 14 may determine a criterion for processing body parts that can identify a worker based on the identification result by the identification unit 13 and information about the work content. For example, when the information about the work content is a work procedure, the conversion unit 14 identifies body parts necessary for each work included in the work procedure. Then, the conversion unit 14 identifies body parts that are not necessary for the work as targets to be hidden by processing. For example, the conversion unit 14 determines a criterion for processing body parts that can identify a worker by identifying body parts that are not necessary for the work as targets to be hidden by processing.

[0035] Furthermore, when the information regarding the work content is the purpose or target of the analysis, the conversion unit 14 determines, for example, criteria for editing body parts that can identify the worker based on body parts that need to be confirmed based on the purpose or target of the analysis. The purpose of the analysis is, for example, information indicating which work to analyze and how. The purpose of the analysis is information indicating checking detailed hand movements during assembly work. The purpose of the analysis is not limited to the above. The target of the analysis is information indicating at least one of the worker, the worker's body parts, and the product that are the target of the video analysis. The target of the analysis is not limited to the above. For example, when the purpose of the analysis is to check detailed hand movements during assembly work, the conversion unit 14 determines, for example, criteria for editing body parts that can identify the worker so that the hands are not hidden. When the purpose of the analysis is to determine the order of work tasks, and the order of work tasks can be determined from the product to be assembled or the tools used, the conversion unit 14 may determine, for example, criteria for editing body parts that can identify the worker so that the worker's hands are hidden.

[0036] The conversion unit 14 also determines the degree of processing to hide the worker's body parts. The conversion unit 14 determines the range of the worker's body parts to be hidden by processing and the extent to which the body parts are made invisible. The conversion unit 14 determines the degree of processing to hide the worker's body parts based on, for example, whether the body parts that can identify the worker are body parts that are necessary for analyzing the work content. For example, if the body parts that can identify the worker are body parts that are not necessary for analyzing the work content, the conversion unit 14 determines, for example, to convert the body parts that can identify the worker into objects. In this case, the conversion unit 14 determines, for example, the range of body parts to be converted into objects. For example, in the case of assembly work using a screwdriver, the conversion unit 14 determines the range of body parts other than the hands to be converted into objects. For example, in the case of assembly work using a screwdriver while wearing a magnifying glass, the conversion unit 14 may determine the range of body parts to be converted into objects, excluding the body parts wearing the magnifying glass. When converted into objects, the body parts hidden by processing are made invisible to viewers of the video.

[0037] Furthermore, if a body part that can identify a worker is, for example, a body part necessary for analyzing the work content, the conversion unit 14 may determine, for example, to reduce the resolution of the body part that can identify the worker. In this case, the conversion unit 14 may determine, for example, the range and degree of resolution reduction. Furthermore, for example, if a worker is performing assembly work using a screwdriver while wearing a magnifying glass, the conversion unit 14 may determine the degree of resolution reduction so that the body part where the magnifying glass is worn is included in the range of resolution reduction. The conversion unit 14 may reduce the resolution to different degrees for the part of the face where the magnifying glass is worn and the part where the magnifying glass is not worn. For example, by reducing the resolution of the part of the face where the magnifying glass is worn by a smaller amount than for the part where the magnifying glass is not worn, it is possible to prevent the identification of the individual while still enabling analysis of the state of wearing the magnifying glass. Furthermore, the criteria indicating the degree of resolution reduction may be set, for example, by the operator of the video management system 10 or the work area manager. For example, the conversion unit 14 may determine the degree to which the resolution of a body part that can identify the worker is to be reduced based on the level of personal information that can be identified from the body part.

[0038] The conversion unit 14 may process at least a portion of the body parts that can identify the worker, with a degree of processing based on the identification result of the identification unit 13. That is, the conversion unit 14 may change the degree of processing of at least a portion of the body parts that can identify the worker, based on the identification result of the identification unit 13. For example, even if the resolution is reduced to hide the body parts that can identify the worker, it may be possible to identify an individual by a combination of items that can identify the worker and are visible even at low resolution. For this reason, the conversion unit 14, for example, reduces the resolution of the part where an item that can identify the worker is worn compared to the part where the item is not worn.

[0039] The conversion unit 14 may determine at least one of the body parts to be concealed by editing in an image of a frame included in a video of the work area and the degree to which the body parts are concealed by editing, based on the attributes of the worker. Furthermore, the conversion unit 14 may determine at least one of the body parts to be concealed by editing and the degree to which the body parts are concealed, based on the attributes of the worker, based on the rank or affiliation of the worker. For example, if a worker in the manufacturing process is an equipment maintenance contractor, the conversion unit 14 determines a standard for the body parts to be concealed such that a greater proportion of the body parts are concealed than if the worker is a worker belonging to the manufacturing process. Furthermore, the conversion unit 14 determines a standard for the degree to which the body parts are concealed such that a greater proportion of the body parts are concealed than if the worker is a worker belonging to the manufacturing process.

[0040] The conversion unit 14 may determine at least one of the body parts to be processed and the degree to which the body parts are to be processed in the image of a frame included in the video captured of the work area based on the personal information protection level. The personal information protection level is set, for example, by the administrator of the work area. The conversion unit 14 may determine the criteria for the body parts to be processed and the degree to which the body parts are to be processed based, for example, on the personal information protection level set for the work area. The conversion unit 14 may also determine the criteria for processing the body parts based on the personal information protection level set for the information indicated by the worker's clothing detected by the identification unit 13. For example, the conversion unit 14 determines the processing criteria such that the range of body parts to be hidden and the degree to which the body parts are hidden increase as the personal information protection level increases. For example, when a high level of personal information protection is required, the conversion unit 14 determines the processing criteria so that all body parts that can identify an individual are hidden. Furthermore, when affiliation can be determined but the individual must not be identified, the conversion unit 14 determines the processing criteria so that the body parts wearing the clothing that can determine affiliation are visible. In addition, when the protection level of personal information is set in multiple stages, the conversion unit 14 may determine the range of body parts to be processed and the degree to which the body parts are to be processed by selecting a stage set according to the protection level of the personal information.

[0041] The conversion unit 14 may determine at least one of the body parts to be hidden and the degree to which the body parts are hidden in the image of a frame included in the video of the work area based on the attributes of the person viewing the converted video. For example, when the viewer of the video is a general worker, the conversion unit 14 determines a standard for processing the body parts so that the range of the body parts to be hidden and the degree to which the body parts are hidden are greater than when a supervisor views the video.

[0042] When the criteria for processing body parts that can identify a worker are determined, the conversion unit 14 processes each of the frame images included in the video of the work area based on the determined criteria to hide body parts that can identify a worker. For example, the conversion unit 14 processes each of the frame images included in the video of the work area in a section in which the identification unit 13 detected work, based on the determined criteria to hide body parts that can identify a worker. For example, the conversion unit 14 processes each of the body parts identified by the identification unit 13 based on the determined criteria to hide body parts that can identify a worker. For example, the conversion unit 14 converts the video of the work area by processing each of the frame images included in the video of the section in which the identification unit 13 detected work, based on the determined criteria.

[0043] The conversion unit 14 converts the video of the work area by, for example, processing the video to hide the body parts that can identify the worker, based on the positions of the body parts identified by the identification unit 13 and the criteria for processing the body parts that can identify the worker. For example, the conversion unit 14 converts the video of the work area into an image in which the body parts that can identify the worker are replaced with objects, a masked image, or an image with reduced image quality.

[0044] For example, the conversion unit 14 replaces body parts that can identify a worker with objects in an image of a frame included in a video of a work area. For example, the conversion unit 14 replaces body parts that can identify a worker with line drawings. The conversion unit 14 may convert body parts that can identify a worker into shapes that are determined according to each body part. The conversion unit 14 may convert body parts that can identify a worker into shapes that are determined in colors that are determined according to each body part. For example, the conversion unit 14 may convert body parts that can identify a worker into illustrations that depict each body part. The conversion unit 14 may convert body parts that can identify a worker into shapes that are determined in colors that are determined according to the work. The manner in which body parts are replaced with objects is not limited to the above.

[0045] For example, the conversion unit 14 masks an area including a body part that can identify the worker in an image of a frame included in a video of the work area. For example, the conversion unit 14 performs masking by superimposing a mosaic pattern on the area including the body part that can identify the worker. For example, the conversion unit 14 may mask the area including the body part that can identify the worker by filling it with a color determined according to the body part. The manner of masking the area including the body part that can identify the worker is not limited to the above.

[0046] For example, the conversion unit 14 processes an image of a frame included in a video of the work area to reduce the resolution of an area including a body part that can identify the worker. The conversion unit 14 may vary the degree to which the resolution is reduced depending on the body part. For example, the conversion unit 14 reduces the resolution of an area that includes a body part that can easily identify the worker, such as the worker's face, to a greater extent than areas that include other body parts. The manner in which the resolution of an area including a body part that can identify the worker is reduced is not limited to the above. Furthermore, the manner in which an area including a body part that can identify the worker is processed in an image of a frame included in a video of the work area is not limited to the above.

[0047] The conversion unit 14 may use a conversion model to convert a video of the work area into an image in which at least a portion of a body part that can identify the worker has been processed. The conversion model is, for example, a learning model that processes a portion of an image frame included in the video. The conversion model processes the portion of the image in which the body part to be processed is shown by replacing it with a line drawing, replacing it with an object, masking it, or reducing the resolution. The conversion unit 14 receives the position of the body part in the image, a conversion criterion, and the image, and outputs an image converted into an image in which the body part that can identify the worker has been hidden. The conversion model is generated, for example, by deep learning using a neural network. The conversion model is generated, for example, by learning the relationship between the conversion criterion and the image before processing and the converted image. The conversion model is generated, for example, in a system external to the video management system.

[0048] The conversion unit 14 may process the body part where the worker is wearing an item that can identify the worker in each of the images of the frames included in the video based on the identification result of the identification unit 13. For example, when an item that can identify the worker is shown in the identification result of the identification unit 13, the conversion unit 14 may reduce the resolution of the body part where the item that can identify the worker is wearing. Furthermore, for example, when an item that can identify the worker is shown in the identification result of the identification unit 13, the conversion unit 14 may replace the area where the item that can identify the worker is wearing with an object defined according to the item.

[0049] FIG. 4 is a diagram showing an example of a frame image included in a video captured of a work area. The example image in FIG. 4 is an image before processing is performed to hide body parts that could identify the worker. In the example image in FIG. 4, a worker is standing next to a workbench, holding cleaning tools, with his back visible in the image. In addition, in the example image in FIG. 4, a nameplate showing the worker's name is attached. Therefore, in the example image in FIG. 4, for example, the worker can be identified from the nameplate visible in the image.

[0050] FIG. 5 is a diagram showing an example of an image in which an image of a frame included in a video of a work area has been processed to make it impossible to identify the worker. The example image in FIG. 5 is an image in which the image in the example of FIG. 4 has been processed to make it impossible to identify the worker. In the example image in FIG. 5, processing has been performed to reduce the resolution of the portion showing the nameplate. Therefore, in the example image in FIG. 5, a person viewing the image will not be able to identify the worker from the nameplate shown in the image.

[0051] The conversion unit 14 may process the video of the work area to hide the tools used by the worker. The conversion unit 14 may also process the video of the work area to hide the product or device on which the worker is working. For example, when a worker can be identified from the tools he or she is using, the conversion unit 14 processes the video of the work area to hide the tools he or she is using.

[0052] The conversion unit 14 may process frame images included in a section of the video of the work area where the identification unit 13 has not identified any work, so that the worker cannot be identified. Furthermore, the conversion unit 14 may process frame images included in a section of the video of the work area where the identification unit 13 has not identified any work, so that the entire image cannot be seen.

[0053] The output unit 15 outputs, for example, the video converted by the conversion unit 14. The output unit 15 outputs, for example, the video converted by the conversion unit 14 to a storage means connected to the video management system via a network. The output unit 15 may also output the video converted by the conversion unit 14 to the storage unit 16.

[0054] The output unit 15 may output information indicating the content of the conversion performed by the conversion unit 14. For example, the output unit 15 outputs information regarding the section in the video on which the conversion unit 14 performed the conversion, the part on which the conversion unit 14 performed the processing, and the degree of the processing.

[0055] The storage unit 16 stores, for example, video captured of the work area. The storage unit 16 also stores an identification model. The identification model may be stored in a storage means external to the video management system 10. The storage unit 16 may also store a conversion model. The conversion model may be stored in a storage means external to the video management system 10. The storage unit 16 may also store video converted by the conversion unit 14. The storage unit 16 may also store information indicating the content of the conversion performed by the conversion unit 14.

[0056] An example of the operation of the video management system 10 to convert a video of a work area into a video in which body parts that can identify a worker have been processed will be described below. Fig. 6 shows an example of the operation flow when the video management system 10 converts a video of a work area into a video in which body parts that can identify a worker have been processed.

[0057] The acquisition unit 11 acquires a video of the work area (step S11). For example, the acquisition unit 11 acquires a video of the work area captured by a camera installed so as to be able to capture the work area.

[0058] Furthermore, the work information acquisition unit 12 acquires information about the work content (step S12).

[0059] When the video of the work area and information about the work content are acquired, the identification unit 13 identifies at least one of the work performed by the worker and the object that appears in the video of the work area (step S13). The identification unit 13 identifies at least one of the work performed by the worker and the object that appears in the video of the work area using, for example, an identification model.

[0060] If the result of the identification indicates that there is a section in the video to be converted (Yes in step S14), the conversion unit 14 determines at least one of the body parts to be processed in the video of the work area and the degree to which the body parts will be processed, based on the result of the identification and information about the work content (step S15). After determining at least one of the body parts to be processed and the degree to which the body parts will be processed, the conversion unit 14 converts the video of the work area into an image in which at least some of the body parts that can identify the worker have been processed, based on the determination (step S16).

[0061] When the video of the work area is converted into a video in which the body parts that can identify the worker are processed, the output unit 15 outputs the video converted by the conversion unit 14 (step S17).

[0062] If, as a result of the identification in step S13, there is a section in the video that needs to be converted (No in step S14), the video management system 10 terminates the process of converting, for example, video footage of a work area into video that has been processed to identify the worker's body parts.

[0063] The video management system 10 identifies at least one of the work performed by the worker and the object captured in the video of the work area. Then, based on the identification result and information regarding the work content, the video management system 10 converts the video of the work area into video in which at least a portion of the body parts that could identify the worker are removed. By converting the video of the work area based on the identification result and information regarding the work content, the video management system 10 can, for example, convert the video of the work area into video in which the body parts that could identify the worker are obscured while leaving the areas necessary for work analysis. When analyzing work in a work area using video, it may be necessary to protect the personal information of the worker while still enabling the analysis of the work. By converting the video into video in which the body parts that could identify the worker are obscured while leaving the areas necessary for work analysis, the video management system 10 can protect the personal information while still allowing the work captured in the video to be analyzed. In this way, by using the video management system 10, video in which the worker is not identified can be obtained while still enabling the analysis of the work.

[0064] Furthermore, the video management system 10 can more appropriately maintain a balance between protecting personal information about work and maintaining video content suitable for analyzing work, for example, by varying the degree to which body parts that can identify workers are processed based on the identification results of video footage of the work area.

[0065] Furthermore, the video management system 10 can prevent a worker from being identified from the items he or she is wearing, for example, by processing the body parts on which the worker is wearing items that can identify him or her in the video taken of the work area.

[0066] Each process in the video management system 10 can be realized by executing a computer program on a computer. Fig. 7 shows an example of the configuration of a computer 100 that executes a computer program that performs each process in the video management system 10. The computer 100 includes a CPU (Central Processing Unit) 101, a memory 102, a storage device 103, an input / output I / F (Interface) 104, and a communication I / F 105.

[0067] The CPU 101 reads and executes computer programs for performing each process from the storage device 103. The CPU 101 may be configured as a combination of multiple CPUs. The CPU 101 may also be configured as a combination of a CPU and another type of processor. For example, the CPU 101 may be configured as a combination of a CPU and a graphics processing unit (GPU). The memory 102 is configured with a dynamic random access memory (DRAM) or the like, and temporarily stores computer programs executed by the CPU 101 and data being processed. The storage device 103 stores computer programs executed by the CPU 101. The storage device 103 is configured with, for example, a non-volatile semiconductor storage device. Other storage devices such as a hard disk drive may also be used for the storage device 103. The input / output I / F 104 is an interface that receives input from an operator and outputs display data, etc. The communication I / F 105 is an interface that transmits and receives data to and from other information processing devices.

[0068] The computer program used to execute each process can also be stored and distributed on a computer-readable recording medium that non-temporarily stores data. Examples of recording media that can be used include magnetic tapes for recording data and magnetic disks such as hard disks. Optical disks such as CD-ROMs (Compact Disc Read Only Memory) can also be used as recording media. Non-volatile semiconductor storage devices can also be used as recording media.

[0069] A part or all of the above-described embodiments can be described as, but not limited to, the following supplementary notes.

[0070] [Supplementary Note 1] A video management system comprising: an acquisition means for acquiring video footage of a work area; a work information acquisition means for acquiring information relating to the work content; an identification means for identifying at least one of the work performed by the worker and the item shown in the video; a conversion means for converting the video into a video in which at least a part of the body part that can identify the worker has been processed, based on the result of the identification and the information relating to the work content; and an output means for outputting the converted video.

[0071] [Supplementary Note 2] The video management system according to Supplementary Note 1, wherein the conversion means converts the video into a processed video that conceals at least a part of a body part that can identify the worker.

[0072] [Supplementary Note 3] The video management system according to Supplementary Note 1 or 2, wherein the conversion means changes the degree of processing of at least a part of a body part that can identify the worker based on the result of the identification.

[0073] [Supplementary Note 4] The video management system according to any one of Supplementary Notes 1 to 3, wherein the information about the work content includes information that identifies at least one of the work to be analyzed and the body part to be analyzed.

[0074] [Supplementary Note 5] The video management system according to any one of Supplementary Notes 1 to 4, wherein the conversion means converts the video into at least one of a video in which at least a part of a body part that can identify the worker is replaced with an object, a masked video, and a video in which the image quality is reduced.

[0075] [Supplementary Note 6] The video management system according to any one of Supplementary Notes 1 to 4, wherein the conversion means converts the video into an image in which a body part on which an item that can identify the worker is attached is processed.

[0076] [Supplementary Note 7] The video management system according to any one of Supplementary Notes 1 to 6, wherein at least one of the body part to be processed and the degree of processing of the body part is set based on an attribute of the worker.

[0077] [Supplementary Note 8] The video management system according to any one of Supplementary Notes 1 to 6, wherein at least one of the body part to be processed and the degree to which the body part is processed is set based on the attributes of the person viewing the converted video.

[0078] [Supplementary Note 9] The video management system according to any one of Supplementary Notes 1 to 6, wherein at least one of the body part to be processed and the degree to which the body part is processed is set based on a protection level of personal information.

[0079] [Supplementary Note 10] The video management system according to any one of Supplementary Notes 1 to 9, wherein the output unit outputs information indicating the content of the conversion performed by the conversion unit.

[0080] [Supplementary Note 11] A video management method comprising: acquiring a video of a work area; acquiring information related to the work content; identifying at least one of the work performed by a worker and an item shown in the video; converting the video into a video in which at least a part of a body part that can identify the worker is processed based on the result of the identification and the information related to the work content; and outputting the converted video.

[0081] [Supplementary Note 12] A recording medium that non-temporarily records a video management program that causes a computer to execute the following processes: acquiring video of a work area; acquiring information about the work content; identifying at least one of the work performed by the worker and the item that appears in the video; converting the video into a video in which at least a part of a body part that can identify the worker is processed based on the result of the identification and the information about the work content; and outputting the converted video.

[0082] The present disclosure has been described above using the above-described embodiments as examples. However, the present disclosure is not limited to the above-described embodiments. That is, the present disclosure can be applied in various aspects that can be understood by a person skilled in the art within the scope of the present disclosure.

[0083] REFERENCE SIGNS LIST 10 Video management system 11 Acquisition unit 12 Work information acquisition unit 13 Identification unit 14 Conversion unit 15 Output unit 16 Storage unit 100 Computer 101 CPU 102 Memory 103 Storage device 104 Input / output I / F 105 Communication I / F

Claims

1. An acquisition means for acquiring an image of a work area; a work information acquisition means for acquiring information related to work content; an identification means for identifying at least one of the work performed by the worker and the item shown in the video; a conversion means for converting the image into an image in which at least a part of a body part that can identify the worker is processed based on the result of the identification and information about the work content; an output means for outputting the converted video; A video management system comprising:

2. The conversion means converts the image into an image that has been processed to hide at least a part of a body part that can identify the worker. The video management system according to claim 1 .

3. The conversion means changes the degree of processing of at least a part of a body part that can identify the worker based on the result of the identification.

3. The video management system according to claim 1 or 2.

4. The information about the work content includes information that identifies at least one of the work to be analyzed and the body part to be analyzed.

3. The video management system according to claim 1 or 2.

5. the conversion means converts the video into at least one of a video in which at least a part of a body part that can identify the worker is replaced with an object, a masked video, and a video in which the image quality is reduced; 3. The video management system according to claim 1 or 2.

6. The conversion means converts the video into an image in which a body part on which an item that can identify the worker is attached is processed.

3. The video management system according to claim 1 or 2.

7. At least one of the body part to be processed and the degree of processing the body part is set based on attributes of the worker.

3. The video management system according to claim 1 or 2.

8. At least one of the body part to be processed and the degree to which the body part is processed is set based on the attributes of a person viewing the converted video.

3. The video management system according to claim 1 or 2.

9. Obtain footage of the work area, Get information about your work, Identifying at least one of the work performed by the worker and the item shown in the video; converting the image into an image in which at least a part of a body part that can identify the worker is processed based on the result of the identification and information about the work content; Output the converted video. Video management methods.

10. Acquiring video of the work area; A process for obtaining information about the work content; A process for identifying at least one of an operation performed by a worker and an item captured in the video; A process of converting the video into a video in which at least a part of a body part that can identify the worker is processed based on the result of the identification and information about the work content; The process of outputting the converted video A video management program that runs on a computer.