US-20260127954-A1 - INFORMATION PROCESSING SYSTEM, INFORMATION PROCESSING METHOD, AND NON-TRANSITORY COMPUTER READABLE MEDIUM

Abstract

An information processing system includes a processor configured to: continuously capture images that include a monitored person; perform skeletal estimation of the person in a captured image to detect whether or not the person is in an abnormal pose; if an abnormal pose is detected, input the image in which the abnormal pose of the person is detected into a large language model that converts the content of an inputted image into text information and outputs the text information, and thereby acquire text information pertaining to the state of the person in the inputted image; and provide a notification indicating that an abnormal pose of the monitored person has occurred, together with the acquired text information and the image in which the abnormal pose is detected, to a preset destination.

Inventors

• Shohei KAWAKAMI

Assignees

• FUJIFILM BUSINESS INNOVATION CORP.

Dates

Publication Date

20260507

Application Date

20250512

Priority Date

20241105

Claims (7)

1. 1 . An information processing system comprising: a processor configured to: continuously capture images that include a monitored person; perform skeletal estimation of the person in a captured image to detect whether or not the person is in an abnormal pose; if an abnormal pose is detected, input the image in which the abnormal pose of the person is detected into a large language model that converts the content of an inputted image into text information and outputs the text information, and thereby acquire text information pertaining to the state of the person in the inputted image; and provide a notification indicating that an abnormal pose of the monitored person has occurred, together with the acquired text information and the image in which the abnormal pose is detected, to a preset destination.
2. 2 . The information processing system according to claim 1 , wherein: the abnormal pose to be detected by skeletal estimation is a fall by the monitored person.
3. 3 . The information processing system according to claim 2 , wherein: the processor is configured to input the image in which the fall by the monitored person is detected and images before and after the fall into the large language model, and thereby acquire text information containing information pertaining to the state of the monitored person before and after the fall.
4. 4 . The information processing system according to claim 1 , wherein the processor is configured to: if an abnormal pose of the person is detected by skeletal estimation, determine whether or not the detected abnormal pose is a fall by the monitored person; if the detected abnormal pose is determined not to be a fall by the monitored person, input the image in which the abnormal pose is detected into the large language model, and thereby acquire text information pertaining to the state of the person in the inputted image; and provide a notification indicating that an abnormal pose of the monitored person has occurred, together with the acquired text information and the image in which the abnormal pose is detected, to a preset destination.
5. 5 . The information processing system according to claim 4 , wherein the processor is configured to: if the detected abnormal pose is determined to be a fall by the monitored person, input the image in which the fall by the monitored person is detected and images before and after the fall into the large language model, and thereby acquire text information containing information pertaining to the state of the monitored person before and after the fall; and provide a notification indicating that a fall by the monitored person has occurred, together with the acquired text information and the image in which the fall is detected, to a preset destination.
6. 6 . An information processing method comprising: continuously capturing images that include a monitored person; performing skeletal estimation of the person in a captured image to detect whether or not the person is in an abnormal pose; if an abnormal pose is detected, inputting the image in which the abnormal pose of the person is detected into a large language model that converts the content of an inputted image into text information and outputs the text information, and thereby acquiring text information pertaining to the state of the person in the inputted image; and providing a notification indicating that an abnormal pose of the monitored person has occurred, together with the acquired text information and the image in which the abnormal pose is detected, to a preset destination.
7. 7 . A non-transitory computer readable medium storing a program causing a computer to execute a process comprising: continuously capturing images that include a monitored person; performing skeletal estimation of the person in a captured image to detect whether or not the person is in an abnormal pose; if an abnormal pose is detected, inputting the image in which the abnormal pose of the person is detected into a large language model that converts the content of an inputted image into text information and outputs the text information, and thereby acquiring text information pertaining to the state of the person in the inputted image; and providing a notification indicating that an abnormal pose of the monitored person has occurred, together with the acquired text information and the image in which the abnormal pose is detected, to a preset destination.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS This application is based on and claims priority under 35 USC 119 from Japanese Patent Application No. 2024-193398 filed Nov. 5, 2024. BACKGROUND (i) Technical Field The present disclosure relates to an information processing system, an information processing method, and a non-transitory computer readable medium. (ii) Related Art International Publication No. WO 2022/249635 discloses an action detection system that provides a notification regarding the detection of an action by a person included in an image to a prescribed destination when both of the following conditions are met: a first notification condition set specifically for an action class identified on the basis of the action; and a second notification condition, such as the duration of the action, the level of congestion around the person, and the time of day when the image was captured. SUMMARY In recent years, the advancement of artificial intelligence (AI) technology has led to AI technology being utilized in various fields. For example, a proposed system uses a camera to capture a monitored person to be monitored and applies AI technology to the captured image to detect falls by the person. A goal in the fields of medicine and nursing care is to quickly notice a fall and issue an alert, leading to rapid aid efforts. In other cases, AI technology is being utilized to stop machines when a fall or other dangerous behavior is detected in places such as factories where dangerous work is performed. However, even if an image of a monitored person is captured and a notification is provided to a preset destination upon detecting that the person in the captured image has fallen, a person who receives the notification may need to check the captured image, and may not be able to easily ascertain what kind of state the monitored person is in. Aspects of non-limiting embodiments of the present disclosure relate to facilitating the ascertaining of a detected abnormal pose state, as compared to the case in which a monitored person is detected to be in an abnormal pose from a captured image of the person and only a notification is provided. Aspects of certain non-limiting embodiments of the present disclosure address the above advantages and/or other advantages not described above. However, aspects of the non-limiting embodiments are not required to address the advantages described above, and aspects of the non-limiting embodiments of the present disclosure may not address advantages described above. According to an aspect of the present disclosure, there is provided an information processing system including a processor configured to: continuously capture images that include a monitored person; perform skeletal estimation of the person in a captured image to detect whether or not the person is in an abnormal pose; if an abnormal pose is detected, input the image in which the abnormal pose of the person is detected into a large language model that converts the content of an inputted image into text information and outputs the text information, and thereby acquire text information pertaining to the state of the person in the inputted image; and provide a notification indicating that an abnormal pose of the monitored person has occurred, together with the acquired text information and the image in which the abnormal pose is detected, to a preset destination. BRIEF DESCRIPTION OF THE DRAWINGS Exemplary embodiments of the present disclosure will be described in detail based on the following figures, wherein: FIG. 1 is a diagram illustrating a system configuration of an information processing system according to an exemplary embodiment of the present disclosure; FIG. 2 is a block diagram illustrating a hardware configuration of a management server 10 according to an exemplary embodiment of the present disclosure; FIG. 3 is a block diagram illustrating a functional configuration of a management server 10 according to an exemplary embodiment of the present disclosure; FIG. 4 is a diagram for explaining an example of processing in an LLM 16; FIG. 5 is a flowchart for explaining operations by an information processing system according to an exemplary embodiment of the present disclosure; FIG. 6 is a diagram illustrating an example of a notification in the case of an ongoing fallen state of a monitored person 21; FIG. 7 is a diagram illustrating an example of a notification in the case where a monitored person 21 falls and then gets back up; FIG. 8 is a flowchart for explaining operations by an information processing system in the case where an abnormal pose other than a fall is also detected and a notification is provided to a terminal device 40; FIG. 9 is a diagram illustrating notification example 1 for the case where an abnormal pose other than a fall is detected; and FIG. 10 is a diagram illustrating notification example 2 for the case where an abnormal pose other than a fall is detected. DETAILED DESCRIPTION The following de