The present invention provides a processing apparatus (10) including: an acquisition unit (11) that acquires an image generated by a camera; an extraction unit (12) that extracts, from the image, an independently acting person being a person taking independent action; a decision unit (13) that decides whether the independently acting person belongs to any of groups, based on group information in which a feature value of an appearance of a person who takes group action is registered; and an output unit (14) that outputs notification information when it is decided that the independently acting person belongs to any of the groups.

A people flow prediction device includes a training data selection unit configured to select, in accordance with a prediction condition including a target prediction period subject to prediction, training data related to people flow data of a plurality of dates and times corresponding to the target prediction period, a prediction model creation unit configured to train, in accordance with the training data being selected, and store, in a model storage unit, a prediction model having a predetermined feature and for predicting people flow data of a predetermined date and time, and a prediction unit configured to select the prediction model from the model storage unit in accordance with the prediction condition and a permission condition related to a feature of the prediction model, and to predict people flow data under the prediction condition in accordance with the prediction model being selected.

Methods and systems for crowd level estimation are provided. The system for crowd level estimation includes an input module and a crowd level estimation module. The input module receives an input image of a crowd and the crowd level estimation module estimates a crowd level of the crowd in the input image in response to a crowd density level.

A non-transitory computer-readable recording medium having stored therein an information processing program that causes a computer to execute a process including specifying, a first image area which includes a person who visits a store and a second image area which includes a container containing commodity products, specifying, positional relationship between each of a plurality of persons belonging to a first group and a specific machine placed in the store, identifying, from among the plurality of persons belonging to the first group, a first person who use the specific machine based on the positional relationship, specifying, a second person who carries the container in which the commodity products are contained from among the plurality of persons belonging to the first group, and performing authentication processing of the commodity products contained in the container carried by the second person has been completed.

Disclosed herein are systems, methods, and non-transitory computer readable mediums directed to identifying persons monitored on video frames of a video feed, determining if the number of people on a monitored video frame is above a prescribed group threshold, and if so, calculating distances between each respective person in the monitored video frame. The calculated distances between each respective person are then compared to a prescribed distance threshold and alerts are generated in response to any calculated distance not satisfying the prescribed threshold. Identification of persons in a monitored video frame may be performed by, for example, facial recognition software. Calculation of distance between persons in a monitored video frame may be performed, for example, by using bounding boxes, machine learning, or other classification techniques.

A display control apparatus includes a processor configured to: obtain detection information from a detector that detects a user; obtain a movement mode of the user based on the detection information; estimate a being time during, which the user is in a predetermined viewing area of a display apparatus based on the movement mode; and control display of video data displayed on the display apparatus so that a playback time of the video data becomes less than or equal to the being time.

The present disclosure relates to methods and systems for identifying an individual in a crowd. The method comprises the steps of capturing a plurality of crowd-viewing images using multiple image-capturing devices. For each image, a reference point within a facial contour of a person in the image is selected. The reference point is selected based on a facial feature on the facial contour of the person. The method further comprises the step of processing the image to obtain one or more angular measurements associated with a posture displayed by the person in the image. Based on the obtained angular measurements, location data of a predetermined body point of the person relative to the reference point is extracted.

The present invention relates to a method for perceiving an event tagging-based situation and a system for same which recognize a plurality of objects by using camera images and apply technology for tracking the movements of the plurality of recognized objects to enable the perception of various situations.

A system for perceiving an event tagging-based situation according to an embodiment of the present invention is characterized by including: an object recognition unit which recognizes objects by receiving video captured by a camera, and extracts information about the objects; an object tracking unit which receives the video captured by the camera, receives information about the objects from the object recognition unit, analyzes frames of the received video and tracks the movements of the recognized objects to figure out the locations of the objects, and extracts location information about each of the objects; an event tagging unit which senses whether or not a predesignated event occurs while an object moves, records event tagging information or an event tag when the event occurs, and outputs event tagging information for each object or an event tag list; and an action generation unit which classifies events into combinations of predesignated events on the basis of the event tagging information for each object or the tagged event list received from the event tagging unit, generates an action allocated for each classified group, and outputs the action.

A user can confirm the congestion degree of a congestion confirmation area at the present moment by a congestion confirmation system which includes mobile communication devices and a congestion confirmation server. The mobile communication device periodically detects and transmits the current location information to the congestion confirmation server. Receiving the current location information, the congestion confirmation server stores the current location information in a database in association with a current time. The mobile communication device sends a congestion confirmation request designating one of the congestion confirmation areas. In response to this request, the congestion confirmation server refers to the database and transmits the location information of mobile communication devices currently located in the congestion confirmation area as designated. Receiving the location information of the mobile communication devices, the mobile communication device which has sent the congestion confirmation request displays a map including the mobile communication devices.

A control system for controlling a plurality of robots using artificial intelligence includes a communication unit configured to receive user information of each of a plurality of unit zones in which the plurality of robots is disposed, and a processor configured to calculate a plurality of densities respectively corresponding to the plurality of unit zones based on the user information of each unit zone, calculate average densities of a plurality of group zones using the plurality of calculated densities, determine respective priorities of the plurality of group zones based on the calculated average densities, and control movement of one or more of the plurality of robots based on the determined priorities.