Video processing device, video processing system, video processing method, and video processing program

Abstract

To provide a video processing device capable of efficiently supporting evaluation for a prescribed action of an evaluation object person.SOLUTION: A video processing device includes: an acquisition unit which acquires video data in which an object person in a living room is photographed; an analysis unit which analyzes the video data acquired by the acquisition unit, and extracts first information regarding persons including the object person and second information regarding articles present in the living room; and a tag adding processing unit which adds a plurality of tags regarding the first information and the second information extracted by the analysis unit in association with the video data in order to support evaluation for a prescribed action performed by the object person.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present disclosure relates to a technology for supporting medical and nursing care administration. [Background technology]

[0002] In an aging society like Japan, the number of people who require nursing care or care due to illness, injury, old age, etc. is expected to increase further in the future. These people who require nursing care or care are admitted to facilities such as hospitals and elderly welfare facilities, where they receive nursing care or care. In such facilities, nurses and caregivers make regular rounds to check on the safety and well-being of the residents.

[0003] In this regard, in facilities and other settings, it is common to evaluate the activities of daily living (ADL) of rehabilitation recipients, elderly people, etc. Such evaluations are often carried out by, for example, directly visually checking the ADL of the person being evaluated or by checking video recordings of the ADL.

[0004] However, at facilities such as day care centers, there may not be staff (such as physical therapists) on-site who have the knowledge to evaluate activities of daily living, making it difficult to visually evaluate the activities of daily living of the person being evaluated.

[0005] In response to this, the activities of daily living of the person being evaluated can be recorded, and the video data created by the recording can be provided to a physical therapist or the like, and the person's activities of daily living can be evaluated. However, in this case, it is preferable to have a system that can easily provide information such as what type of activity was performed, when, and who performed it, along with the video data, and various proposals have been made (Patent Documents 1-3). [Prior art documents] [Patent documents]

[0006] [Patent Document 1] Japanese Patent Application Publication No. 2018-185729 [Patent Document 2] Japanese Patent Application Publication No. 2019-160228 [Patent Document 3] Japanese Patent Application Publication No. 2020-190871 Summary of the Invention [Problem to be solved by the invention]

[0007] In this regard, it is desirable to efficiently support the evaluation of a predetermined action of an evaluation subject. The present disclosure is intended to solve the above-mentioned problems, and to provide a video processing device, a video processing system, a video processing method, and a video processing program that can efficiently support the evaluation of specified actions of a person being evaluated. [Means for solving the problem]

[0008] A video processing device according to one aspect of the present disclosure includes an acquisition unit that acquires video data of a subject in a room, an analysis unit that analyzes the video data acquired by the acquisition unit and extracts first information about people including the subject and second information about objects in the room, and a tagging processing unit that associates and assigns multiple tags related to the first information and second information extracted by the analysis unit to the video data to assist in evaluating a predetermined action performed by the subject.

[0009] Preferably, the first information includes information relating to the number of people and their actions. Preferably, the information relating to behavior includes information relating to the subject's behavior and the caregiver's behavior.

[0010] Preferably, the second information includes information relating to care products. Preferably, the tagging processing unit assigns a tag based on a combination of tags related to the first information and / or the second information in association with the video data.

[0011] Preferably, the system further includes a video storage unit that stores multiple video data to which tags have been assigned by the tagging processing unit, a tag name input receiving unit that receives tag names input by the user, and a display control unit that displays on a display unit a list of video data to which tags with the names input in the tag input receiving unit have been assigned from the multiple video data stored in the video storage unit.

[0012] Preferably, the device further includes a statistical processing unit that performs statistical processing based on at least one of a plurality of tags assigned to video data over a predetermined period and a behavioral trajectory of the subject obtained by analyzing the video data, and calculates a predetermined statistical value.

[0013] Preferably, the predetermined statistical values include values relating to assistance, walking, and transfer. Preferably, the device further includes an index calculation unit that calculates an index related to ADL evaluation or care level determination based on at least one of the first information, the second information, and the statistical value.

[0014] A video processing system according to one aspect of the present disclosure includes an acquisition unit that acquires video data of a subject in a room, an analysis unit that analyzes the video data acquired by the acquisition unit and extracts first information about people including the subject and second information about objects in the room, and a tagging processing unit that associates and assigns multiple tags related to the first information and the second information extracted by the analysis unit to the video data to assist in evaluating a predetermined action performed by the subject.

[0015] A video processing method according to an aspect of the present disclosure includes the steps of acquiring video data of a subject in a room, analyzing the video data acquired by the acquisition unit to extract first information about people including the subject and second information about objects in the room, and associating and assigning multiple tags related to the first information and second information extracted by the analysis unit to the video data to assist in evaluating a predetermined action performed by the subject.

[0016] A video processing program according to an aspect of the present disclosure includes a step of acquiring video data of a subject in a room, a step of analyzing the video data acquired by the acquisition unit and extracting first information about people including the subject and second information about objects in the room, and a step of associating and assigning multiple tags related to the first information and second information extracted by the analysis unit to the video data to assist in evaluating a predetermined action performed by the subject.

[0017] A video processing device according to another aspect of the present disclosure includes an acquisition unit that acquires video data of a subject in a room, an analysis unit that analyzes the video data acquired by the acquisition unit, and a tagging processing unit that associates and assigns multiple tags to the video data based on analysis results of the analysis unit to assist in evaluation of a predetermined action performed by the subject. Based on the analysis results of the analysis unit, the tagging processing unit assigns to the video data a first classification tag related to the subject, a second classification tag related to an object in the room, and a third classification tag based on a combination of the first classification tag and / or the second classification tag.

[0018] A video processing system according to another aspect of the present disclosure includes an acquisition unit that acquires video data of a subject in a living room, an analysis unit that analyzes the video data acquired by the acquisition unit, and a tagging processing unit that associates and assigns multiple tags to the video data based on analysis results of the analysis unit to assist in evaluation of a predetermined action performed by the subject. Based on the analysis results of the analysis unit, the tagging processing unit assigns to the video data a first classification tag related to the subject, a second classification tag related to an object in the room, and a third classification tag based on a combination of the first classification tag and / or the second classification tag.

[0019] A video processing method according to another aspect of the present disclosure includes the steps of acquiring video data of a subject in a room, analyzing the video data acquired by the acquisition unit, and associating and assigning multiple tags to the video data based on the analysis results to assist in evaluation of a predetermined action performed by the subject. The assigning step includes the steps of assigning, to the video data, a first classification tag related to the subject, a second classification tag related to an object in the room, and a third classification tag based on a combination of the first classification tag and / or the second classification tag, based on the analysis results.

[0020] A video processing program according to another aspect of the present disclosure includes the steps of acquiring video data of a subject in a room, analyzing the video data acquired by the acquisition unit, and associating and assigning multiple tags to the video data based on the analysis results to assist in evaluation of a predetermined action performed by the subject. The assigning step executes processing including the steps of assigning, to the video data, a first classification tag related to the subject, a second classification tag related to an object in the room, and a third classification tag based on a combination of the first classification tag and / or the second classification tag, based on the analysis results. [Effects of the Invention]

[0021] The video processing device, video processing method, and video processing program are capable of efficiently supporting evaluation of a predetermined motion of a subject to be evaluated.

[0022] The above and other objects, features, aspects and advantages of the present invention will become apparent from the following detailed description of the invention taken in conjunction with the accompanying drawings. [Brief explanation of the drawings]

[0023] [Figure 1] 1 is a diagram illustrating an example of a configuration of a monitoring system 100 according to an embodiment. [Figure 2] 1 is a block diagram showing an outline of the configuration of a monitoring system 100 according to an embodiment. [Figure 3] FIG. 2 is a block diagram showing a functional configuration of a management terminal 200 according to the embodiment. [Figure 4] 10A to 10C are diagrams illustrating analysis of moving image data by an analysis unit 12 according to an embodiment. [Figure 5] 10A and 10B are diagrams illustrating generation of another tag by tagging processing unit 14 according to the embodiment. [Figure 6] FIG. 10 is a diagram illustrating a flow of tagging processing by a management terminal 200 according to an embodiment. [Figure 7] FIG. 10 is a diagram illustrating an example of a management screen displayed on a display 226 of a management terminal 200 according to an embodiment. [Figure 8] FIG. 10 is a diagram illustrating an example of a processing flow for calculating an index by an index calculation unit 20 according to the embodiment. [Figure 9] FIG. 10 is a diagram illustrating another example of a management screen displayed on the display 226 of the management terminal 200 according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0024] Hereinafter, embodiments of the technical concept according to the present disclosure will be described with reference to the drawings. In the following description, the same components are denoted by the same reference numerals. The names and functions of the components are also the same. Therefore, detailed descriptions thereof will not be repeated.

[0025] [The overall system that forms the technological concept] First, an overview of the technical concept disclosed in this specification will be described. In a certain aspect, a photographed image is acquired by photographing the room of a subject, such as a resident of a facility, using a camera. By analyzing the photographed image, the subject's daily condition can be accurately grasped. The photographing can be performed for a predetermined period of time (for example, 24 hours), or it can be performed in response to a specific event.

[0026] [Configuration of monitoring system] Fig. 1 is a diagram showing an example of the configuration of a monitoring system 100 according to an embodiment. Referring to Fig. 1, the targets of monitoring are, for example, residents in each room provided in a room area 180 of a facility. In the monitoring system 100 of Fig. 1, a room 110 is provided in the room area 180. The room 110 is assigned to a resident 111. In the example of Fig. 1, the number of rooms included in the monitoring system 100 is one, but the number is not limited to this.

[0027] In the monitoring system 100, a sensor box 119 installed in a room 110 and a management terminal 200 are connected via a network 190. The network 190 may include both an intranet and the Internet.

[0028] In the monitoring system 100, the sensor box 119 and the management terminal 200 are provided so as to be able to communicate with each other via a network 190. Note that they may also be able to communicate with a cloud server (not shown).

[0029] The living room 110 includes, as its facilities, a chest of drawers 112 and a bed 113. However, the facilities are not limited to these, and other facilities such as a television, a toilet, and the like may also be provided.

[0030] The sensor box 119 has a built-in sensor for detecting the behavior of an object in the living room 110. An example of the sensor is a camera. The sensor box 119 may include other sensors in addition to the camera.

[0031] 2 is a block diagram showing an outline of the configuration of the monitoring system 100 according to the embodiment. The components of the monitoring system 100 will be described with reference to FIG.

[0032] The sensor box 119 includes a control device 101, a ROM (Read Only Memory) 102, a RAM (Random Access Memory) 103, a communication interface 104, a camera 105, and a storage device 108.

[0033] The control device 101 controls the sensor box 119. The control device 101 is configured, for example, by at least one integrated circuit. The integrated circuit is configured, for example, by at least one CPU (Central Processing Unit), MPU (Micro Processing Unit) or other processor, at least one ASIC (Application Specific Integrated Circuit), at least one FPGA (Field Programmable Gate Array), or a combination thereof.

[0034] An antenna (not shown) and the like are connected to the communication interface 104. The sensor box 119 exchanges data with external communication devices via the antenna. The external communication devices include, for example, a management terminal.

[0035] In one implementation, the camera 105 is a near-infrared camera. The near-infrared camera includes an IR (Infrared) projector that projects near-infrared light. By using a near-infrared camera, an image showing the interior of the room 110 can be captured even at night. In another implementation, the camera 105 is a surveillance camera that receives only visible light. In still another implementation, a 3D sensor or a thermography camera may be used as the camera 105. The sensor box 119 and the camera 105 may be configured as an integrated unit or as separate units.

[0036] The storage device 108 is, for example, a fixed storage device such as a flash memory or a hard disk, or a recording medium such as an external storage device. The storage device 108 stores programs executed by the control device 101 and various data used to execute the programs. The various data may include behavioral information of the resident 111.

[0037] At least one of the above programs and data may be stored in a storage device other than storage device 108 (for example, a storage area of control device 101 (for example, cache memory, etc.), ROM 102, RAM 103, external device (for example, management terminal 200, etc.)) as long as it is a storage device accessible by control device 101.

[0038] The management terminal 200 includes a control device 221 , a ROM 222 , a RAM 223 , a communication interface 224 , a display 226 , a storage device 228 , and an input device 229 .

[0039] The control device 221 controls the management terminal 200. The control device 221 is configured, for example, by at least one integrated circuit. The integrated circuit is configured, for example, by at least one CPU, at least one ASIC, at least one FPGA, or a combination thereof.

[0040] An antenna (not shown) and the like are connected to the communication interface 224. The management terminal 200 exchanges data with external communication devices via the antenna and access point, etc. External communication devices include, for example, the sensor box 119 and the like.

[0041] The display 226 is realized by, for example, a liquid crystal display, an organic EL (Electro Luminescence) display, etc. The input device 229 is realized by, for example, a touch sensor provided on the display 226, a keyboard, a mouse, etc.

[0042] The storage device 228 is realized by, for example, a flash memory, a hard disk or other fixed storage device, or a removable data recording medium.

[0043] [Functional configuration of management terminal 200] 3 is a block diagram showing the functional configuration of management terminal 200 according to the embodiment. The functional configuration of management terminal 200 will be described with reference to FIG.

[0044] The management terminal 200 includes an acquisition unit 10 , an analysis unit 12 , a tagging processing unit 14 , a display control unit 16 , a statistical processing unit 18 , an index calculation unit 20 , and an image data storage unit 22 .

[0045] The acquisition unit 10 acquires video data captured by a subject who is a resident of a room. The acquisition unit 10 may acquire video data stored in the storage device 228 of the management terminal 200, or may acquire video data acquired from the storage device 108 of the sensor box 119.

[0046] The analysis unit 12 analyzes the video data acquired by the acquisition unit 10, and extracts first information about people including the subject and second information about objects in the room.

[0047] The tagging processing unit 14 associates and assigns multiple tags related to the first information and second information extracted by the analysis unit 12 to the video data in order to assist in the evaluation of a predetermined action performed by the subject. The first information includes information related to the number of people and actions. The information related to actions includes information related to the actions of the subject and the actions of the caregiver. The second information includes information related to care products. The tagging processing unit 14 associates and assigns tags based on a combination of tags related to the first information and / or the second information to the video data.

[0048] The image data storage unit 22 stores a plurality of video data to which tags have been added by the tagging processing unit 14. The image data storage unit 22 may be provided as a partial area of the storage device 228, or may be provided in the RAM 223. However, the present invention is not limited to this, and the image data storage unit 22 may be stored outside the management terminal 200.

[0049] The display control unit 16 displays on the display unit a list of moving image data tagged with the input name from among the plurality of moving image data stored in the image data storage unit 22.

[0050] The statistical processing unit 18 performs statistical processing on the analysis results of the video data for a predetermined period. The statistical processing unit 18 performs statistical processing based on at least one of the multiple tags assigned to the video data and the subject's behavioral trajectory obtained as a result of analyzing the video data, and calculates predetermined statistical values. The predetermined statistical values include values related to assistance, walking, and transfers.

[0051] The index calculation unit 20 calculates an index related to the ADL evaluation or the care level determination based on at least one of the first information, the second information, and the statistical value.

[0052] The processing of the management terminal 200 is realized by software executed by each piece of hardware and the control device 221. Such software may be pre-stored in the storage device 228. Alternatively, the software may be stored on a CD-ROM or other recording medium and distributed as a computer program. Alternatively, the software may be provided as a downloadable application program by an information provider connected to the Internet. Such software is read from the recording medium by an optical disk drive or other reading device, or downloaded via the communication interface 224, and then temporarily stored on the hard disk 5. The software is read from the storage device 228 by the control device 221 and stored in the RAM 223 in the form of an executable program. The control device 221 executes the program.

[0053] [Example of analysis processing] 4 is a diagram illustrating analysis of video data by analysis unit 12 according to an embodiment. Referring to FIG. 4, in this example, analysis unit 12 analyzes scenes of the video data to extract first information about a person and second information and basic information about an object.

[0054] The extracted first information includes information about the number of people and their behavior. Furthermore, the information about the number of people includes information about 0 to 2 people. In the case of two people, the information about the calculated distance between the two people includes information about whether the distance between the two people is far or close based on a comparison between the calculated information about the distance between the two people and a predetermined threshold value.

[0055] Furthermore, the information about behavior includes information about walking, turning, getting out of bed, getting up, and turning over in bed. In the case of walking, the information includes information about speed and unsteadiness. The analysis unit 12 acquires the person's behavior trajectory from scenes in the video data and calculates information about speed and unsteadiness. The speed is calculated based on the distance traveled / travel time traveled as the behavior trajectory. As an example, the unsteadiness information can be calculated from the amount of deviation based on a linear movement trajectory as the person's behavior trajectory. For example, when the start and end points of the person's behavior trajectory are indicated, the degree of unsteadiness may be determined based on the amount of deviation between the linear distance connecting the start and end points and the actual distance traveled. In determining the degree of unsteadiness, a position where the person remains stationary for a certain period of time (e.g., 10 seconds) or more may be used as the start point, and a position where the person remains stationary for a certain period of time (e.g., 10 seconds) or more after starting movement from the start point may be used as the end point. The deviation amount may be compared with a predetermined threshold value, and if the deviation amount is equal to or greater than the predetermined threshold value, the degree of fluctuation may be determined to be large, and if the deviation amount is less than the predetermined threshold value, the degree of fluctuation may be determined to be small.

[0056] The extracted second information includes information about location and assistive devices. The information about location includes information about bed, toilet, television, etc. The information about assistive devices includes information about none, walker, cane, chair, and wheelchair.

[0057] The basic information includes information about the time period and the year and month. The information about the time period includes information about morning, evening, daytime, and night. The information about the year and month includes information about the year and month.

[0058] The tagging processing unit 14 uses the first information, the second information, and the basic information extracted by the analysis unit 12 to associate and assign a plurality of tags to the video data.

[0059] For example, tags representing the number of people, "0 people" to "2 people," are assigned to the video data. In the case of the tag "2 people," distance-related tags, "far" and "near," are further assigned to the video data based on the calculated distance information.

[0060] As another example of tags, action tags "walking," "turning," "getting out of bed," "getting up," and "turning over" are associated with and assigned to video data. In the case of the tag "walking," speed-related tags "fast" and "slow" are further associated with and assigned to the video data based on information about the calculated walking speed. Furthermore, unsteadiness-related tags "small" and "large" are associated with and assigned to the video data based on information about the calculated degree of sway.

[0061] As another example of tags, location tags such as "bed," "toilet," "television," and "other" are associated with video data, and assistive device tags such as "none," "walking frame," "cane," "chair," and "wheelchair" are associated with video data.

[0062] As another example of tags, tags for basic information are associated with video data and assigned. Tags relating to time periods such as "morning," "evening," "night," and "daytime" are associated with video data and assigned. Tags relating to the year and month such as "year" and "month" are associated with video data and assigned.

[0063] The tagging processing unit 14 uses the assigned tag to further assign another tag based on the combination to the video data in association with the tag.

[0064] 5 is a diagram illustrating generation of another tag by tagging processing unit 14 according to an embodiment. Seven combination patterns PT0 to PT6 are shown in FIG. 5. However, the present invention is not limited to these, and other combination patterns may be provided.

[0065] Specifically, pattern PT0 shows a case where a tag "with or without assistance" is assigned based on a combination of tags "two people" and "close."

[0066] Pattern PT1 shows a case where a tag "transfer or not" is assigned based on a combination of tags "turning" and "wheelchair."

[0067] Pattern PT2 shows a case where a tag "walking (walking alone)" is assigned based on a combination of tags "alone", "walking", and "none".

[0068] Pattern PT3 shows a case where the tag "walking (walking along)" is assigned based on a combination of the tags "one person," "walking," and "large."

[0069] Pattern PT4 shows a case where a tag "transfer (without assistance)" is assigned based on a combination of tags "one person," "rotation," and "wheelchair."

[0070] Pattern PT5 shows a case where the tag "transfer (full assistance)" is assigned based on a combination of the tags "two people," "rotation," "wheelchair," and "close."

[0071] Pattern PT6 shows a case where the tag "walking (walker)" is assigned based on a combination of the tags "one person," "walking," and "walker."

[0072] FIG. 6 is a diagram illustrating the flow of tagging processing by management terminal 200 according to the embodiment.

[0073] 6, the acquiring unit 10 acquires video data (step S2). The acquiring unit 10 acquires video data stored in the storage device 228 of the management terminal 200. For example, video data for every two minutes is stored in the storage device 228. Note that this time is not limited to two minutes and can be set to any time.

[0074] Next, the analysis unit 12 executes an analysis process for analyzing the video data (step S4). The analysis unit 12 executes an analysis process for analyzing every two minutes of video data as one scene.

[0075] The analysis unit 12 extracts first information about people including the subject and second information about objects in the room based on the analysis processing result (step S6). As an example, the analysis unit 12 extracts the first information, the second information, and the basic information according to the method described in FIG.

[0076] The tagging processing unit 14 executes a first tag output process to output tags based on the extracted first information and second information (step S8). Specifically, the tagging processing unit 14 outputs tags for the number of people, actions, locations, assistive devices, and basic information.

[0077] Next, the tagging processing unit 14 executes a tag analysis process to analyze the combination of tags related to the first information and the second information output in the first tag output process (step S10). Specifically, the tagging processing unit 14 executes the tag analysis process to analyze the combination of tags according to the method described in FIG.

[0078] Next, the tagging processing unit 14 executes a second tag output process to output a tag based on the result of the tag analysis process (step S12). The tagging processing unit 14 outputs a tag of the corresponding pattern PT according to the method described in FIG.

[0079] Next, the tagging processing unit 14 executes a tagging process to associate the output tag with the video data and assign it to the video data (step S14). The tagging processing unit 14 assigns the tag and stores the associated video data in the image data storage unit 22.

[0080] Then, the process ends (END). The tagging processing unit 14 may store not only the tags but also the extracted first and second information and basic information together with the tags in the image data storage unit 22 as detailed information associated with the video data.

[0081] 7 is a diagram illustrating an example of a management screen displayed on display 226 of management terminal 200 according to the embodiment. Referring to FIG. 7, a management screen 300 is provided.

[0082] The management screen 300 is provided with a tag input acceptance field 302 for accepting input of tag information, and a moving image list field 304. The moving image list field 304 displays thumbnail images of multiple moving image data.

[0083] By selecting a thumbnail image of each video data, the video data can be enlarged and played back. Alternatively, by selecting a thumbnail image of each video data, detailed information about the video data can be displayed. For example, tag data associated with the video data can be displayed.

[0084] The tag input acceptance column 302 is provided with check boxes corresponding to a plurality of tags, and the check boxes are provided so that check input can be accepted.

[0085] As an example, in this example, the following items are provided as tags: "Getting out of bed," "Fall," "Walker," "Wheelchair," "Assistance," "Walking," "Walking independently," and "Transfer," and checkboxes are provided so that they can be checked via the input device 229. However, this is not limiting, and it is also possible to provide checkboxes for multiple tags.

[0086] By checking the checkbox, video data associated with the tag stored in the image data storage unit 22 is searched for, and a list of the video data is displayed in the video list field 304.

[0087] In this example, the check box for the tag "Getting out of bed" is checked, and a list of multiple video data items associated with the tag "Getting out of bed" is displayed.

[0088] This makes it possible to easily search for desired video data based on tags. In this example, not only tags related to people but also tags related to objects are associated with and saved in video data, making it possible to tag from multiple perspectives and efficiently support the evaluation of a specific action of a subject.

[0089] 8 is a diagram illustrating an example of a processing flow for index calculation by index calculation unit 20 according to the embodiment. A case where the levels of the basic operation stages of ICF staging are classified will be described.

[0090] 8, the index calculation unit 20 calculates an index related to the ADL evaluation or the care level determination based on at least one of the first information, the second information, and the statistical value. The index calculation unit 20 also calculates an index related to the ADL evaluation or the care level determination for video data within a predetermined period. The predetermined period can be set to one hour, one day, one month, or one year.

[0091] The index calculation unit 20 determines whether or not there is an independent walking tag based on the tags assigned to the video data, and if it determines that there is an independent walking tag, determines the walking speed.

[0092] The index calculation unit 20 uses the first information to determine whether the walking speed is 1 m / sec or more. If the index calculation unit 20 determines that the walking speed is 1 m / sec or more, the level of the basic movement stage is set to level 5.

[0093] If the index calculation unit 20 determines that the walking speed is not 1 m / sec or more, the level of the basic movement stage is set to level 4.

[0094] If the index calculation unit 20 determines that there is no independent walking tag based on the tags assigned to the video data, it uses statistical values to determine the transfer rate. If the statistical value of the transfer rate is 20% or more, the index calculation unit 20 sets the basic movement stage level to level 4.

[0095] If the statistical value of the transfer rate is less than 20%, the index calculation unit 20 sets the level of the basic operation stage to level 3. If the statistical value of the transfer rate is 0%, the index calculation unit 20 determines whether or not there is a turning-over tag based on the tags attached to the video data. If it determines that there is a turning-over tag, the index calculation unit 20 sets the level of the basic operation stage to level 2. If it determines that there is no turning-over tag based on the tags attached to the video data, the index calculation unit 20 sets the level of the basic operation stage to level 1.

[0096] The levels of the basic operation stages can be classified according to the processing flow. Note that this processing is just an example, and other parameters can be combined, and the levels may be classified into multiple stages rather than five.

[0097] 9 is a diagram illustrating another example of a management screen displayed on display 226 of management terminal 200 according to an embodiment. Referring to FIG. 9, a management screen 310 is provided.

[0098] The management screen 310 displays data on the transition of walking speed as statistical values calculated by the statistical processing unit 18, a status 312 of the number of posture frames, and data on a basic movement stage 314 as an index calculated by the index calculation unit 20. The data on the basic movement stage 314 indicates a case where the stage is at level 4. The management screen 310 also displays video data of the subject. However, this is not limiting, and multiple other statistical data and index values may be displayed. Specifically, the statistical processing unit 18 performs statistical processing based on at least one of multiple tags assigned to the video data and the subject's behavioral trajectory over a predetermined period (e.g., one week) to calculate predetermined statistical values. The predetermined statistical values include values related to assistance, walking, and transfer. The statistical processing unit 18 may perform statistical processing on the transfer status, the degree of assistance, the walking status, etc. based on multiple tags assigned to the video data to calculate statistical values. For example, as the transfer status, statistical values of the proportion of people not receiving assistance (transfer time), the proportion of people receiving supervision, the proportion of people receiving partial assistance, and the proportion of people receiving full assistance may be calculated based on tags attached to video data within a predetermined period. As the walking status, statistical values of the proportion of people walking independently (average walking speed, average degree of unsteadiness), the proportion of people walking with support, and the proportion of people receiving assistance may be calculated based on tags attached to video data within a predetermined period. Note that the predetermined period is not limited to this, and can also be in units of one hour, one day, one month, or one year.

[0099] Based on this data, it is possible to efficiently support the evaluation of the predetermined behavior of the person being evaluated.

[0100] The embodiments disclosed herein should be considered to be illustrative in all respects and not restrictive. The scope of the present invention is defined by the claims, not by the above description, and is intended to include all modifications within the meaning and scope of the claims. [Industrial Applicability]

[0101] The technique is applicable to information acquired in hospitals, nursing homes, care homes and other facilities. [Explanation of symbols]

[0102] 5 Hard disk, 104,224 Communication interface, 10 Acquisition unit, 12 Analysis unit, 14 Tagging processing unit, 16 Display control unit, 18 Statistical processing unit, 20 Index calculation unit, 22 Image data storage unit, 100 Monitoring system, 101,221 Control device, 102,222 ROM, 103,223 RAM, 105 Camera, 108,228 Storage device, 110 Room, 111 Resident, 112 Dresser, 113 Bed, 119 Sensor box, 180 Room area, 190 Network, 200 Management terminal, 226 Display, 229 Input device, 300,310 Management screen.

Claims

1. an acquisition unit that acquires video data of a subject in a room; an analysis unit that analyzes the video data acquired by the acquisition unit and extracts first information about people including the subject and second information about objects in the room; a tagging processing unit that associates a plurality of tags related to the first information and the second information extracted by the analysis unit with the video data in order to assist in evaluation of the predetermined action performed by the subject; A video processing device comprising: a statistical processing unit that performs statistical processing based on at least one of the multiple tags assigned to the video data over a predetermined period and the subject's behavioral trajectory obtained by analyzing the video data, and calculates predetermined statistical values.

2. The video processing device according to claim 1 , wherein the first information includes information on the number of people and their actions.

3. The video processing device according to claim 2 , wherein the information relating to the behavior includes information relating to the behavior of the subject and information relating to the behavior of a caregiver.

4. 4. The video processing device according to claim 1, wherein the second information includes information relating to nursing care products.

5. The video processing device according to claim 1 , wherein the tagging processing unit assigns a tag based on a combination of tags related to the first information and / or the second information to the video data in association with the tag.

6. a video storage unit that stores a plurality of video data items tagged by the tagging processing unit; a tag name input receiving unit that receives an input of the tag name by a user; The video processing device according to any one of claims 1 to 5, further comprising a display control unit that displays on a display unit a list of video data tagged with the name input in the tag name input receiving unit from among the plurality of video data stored in the video storage unit.

7. The video processing device according to claim 1, wherein the predetermined statistical values include values relating to assistance, walking, and transfer.

8. The video processing device according to any one of claims 1 to 7, further comprising an index calculation unit that calculates an index related to an ADL evaluation or a care level determination based on at least one of the first information, the second information, and the statistical value.

9. an acquisition unit that acquires video data of a subject in a room; an analysis unit that analyzes the video data acquired by the acquisition unit and extracts first information about people including the subject and second information about objects in the room; a tagging processing unit that associates a plurality of tags related to the first information and the second information extracted by the analysis unit with the video data in order to assist in evaluation of the predetermined action performed by the subject; A video processing system comprising: a statistical processing unit that performs statistical processing based on at least one of the multiple tags assigned to the video data over a predetermined period and the subject's behavioral trajectory obtained by analyzing the video data, and calculates predetermined statistical values.

10. A video processing method executed by a computer of a video processing device, comprising: acquiring video data of a subject in a room; analyzing the acquired video data to extract first information about people including the subject and second information about objects in the room; assigning a plurality of tags relating to the extracted first information and the extracted second information to the video data in association with the video data in order to assist in evaluation of the predetermined action performed by the subject; A video processing method comprising a step of performing statistical processing based on at least one of the plurality of tags assigned to the video data over a predetermined period of time and the subject's behavioral trajectory obtained by analyzing the video data, and calculating a predetermined statistical value.

11. acquiring video data of a subject in a room; analyzing the acquired video data to extract first information about people including the subject and second information about objects in the room; assigning a plurality of tags relating to the extracted first information and the extracted second information to the video data in association with the video data in order to assist in evaluation of the predetermined action performed by the subject; A video processing program that causes a computer to execute processing, the program comprising: a step of performing statistical processing based on at least one of the plurality of tags assigned to the video data over a predetermined period of time and the subject's behavioral trajectory obtained by analyzing the video data, and calculating a predetermined statistical value.

12. an acquisition unit that acquires video data of a subject in a room; an analysis unit that analyzes the video data acquired by the acquisition unit; a tagging processing unit that assigns a plurality of tags to the video data in association with the tags based on an analysis result of the analysis unit in order to assist in evaluation of the predetermined action performed by the subject, the tagging processing unit assigns, to the video data, a first classification tag related to the subject, a second classification tag related to an object in the room, and a third classification tag based on a combination of the first classification tag and / or the second classification tag based on the analysis result of the analysis unit; The video processing device further includes a statistical processing unit that performs statistical processing based on at least one of the tags of the first to third classifications assigned to the video data during a predetermined period and the behavioral trajectory of the subject obtained by analyzing the video data, and calculates predetermined statistical values.

13. an acquisition unit that acquires video data of a subject in a room; an analysis unit that analyzes the video data acquired by the acquisition unit; a tagging processing unit that assigns a plurality of tags to the video data in association with the tags based on an analysis result of the analysis unit in order to assist in evaluation of the predetermined action performed by the subject, the tagging processing unit assigns, to the video data, a first classification tag related to the subject, a second classification tag related to an object in the room, and a third classification tag based on a combination of the first classification tag and / or the second classification tag based on the analysis result of the analysis unit; The video processing system further includes a statistical processing unit that performs statistical processing based on at least one of the tags of the first to third classifications assigned to the video data during a predetermined period and the behavioral trajectory of the subject obtained by analyzing the video data, and calculates predetermined statistical values.

14. A video processing method executed by a computer of a video processing device, comprising: acquiring video data of a subject in a room; analyzing the acquired video data; and assigning a plurality of tags to the video data based on the analysis results in order to assist in evaluation of the predetermined motion performed by the subject. the assigning step includes a step of assigning, to the video data, a first classification tag related to the subject, a second classification tag related to an object in the room, and a third classification tag based on a combination of the first classification tag and / or the second classification tag, based on the analysis result; The video processing method further comprises a step of performing statistical processing based on at least one of the tags of the first to third classifications assigned to the video data during a predetermined period and the behavioral trajectory of the subject obtained by analyzing the video data, and calculating a predetermined statistical value.

15. acquiring video data of a subject in a room; analyzing the acquired video data; and assigning a plurality of tags to the video data based on the analysis results in order to assist in evaluation of the predetermined motion performed by the subject. the assigning step includes a step of assigning, to the video data, a first classification tag related to the subject, a second classification tag related to an object in the room, and a third classification tag based on a combination of the first classification tag and / or the second classification tag, based on the analysis result; A video processing program that causes a computer to execute processing, further comprising a step of performing statistical processing based on at least one of the tags of the first to third classifications assigned to the video data over a predetermined period and the behavioral trajectory of the subject obtained by analyzing the video data, and calculating a predetermined statistical value.

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