Disclosed are method and apparatus to recognize actors during normal system operation. The method includes defining actor input such as hand gestures, executing and detecting input, and identifying salient features of the actor therein. A model is defined from salient features, and a data set of salient features and/or model are retained, and may be used to identify actors for other inputs. A command such as “unlock” may be executed in response to actor input. Parameters may be applied to further define where, when, how, etc. actor input is executed, such as defining a region for a gesture. The apparatus includes a processor and sensor, the processor defining actor input, identifying salient features, defining a model therefrom, and retaining a data set. A display may also be used to show actor input, a defined region, relevant information, and/or an environment. A stylus or other non-human actor may be used.

[Problem] To provide a motion condition estimation device, a motion condition estimation method and a motion condition estimation program capable of accurately estimating the motion condition of monitored subjects even in a crowded environment. [Solution] A motion condition estimation device according to the present invention is provided with a quantity estimating means 81 and a motion condition estimating means 82. The quantity estimating means 81 uses a plurality of chronologically consecutive images to estimate a quantity of monitored subjects for each local region in each image. The motion condition estimating means 82 estimates the motion condition of the monitored subjects from chronological changes in the quantities estimated in each local region.

A device includes a memory configured to store instructions and a processor configured to execute the instructions to obtain image data of a region of interest included in an image frame. The processor may also be configured to compare the image data of the region of interest with image data of a background to detect a change in the region of interest. The processor may further be configured to detect the object in image frame based on the detected change.

The present disclosure relates to a method and system for recommending optimal ergonomic position for a user of a computing device by a recommendation system. The recommendation system receives user data from one or more data sources and extracts a profile of the user from a repository based on the user data. The recommendation system identifies one or more critical areas of the user, where each of the critical areas are associated with a plurality of pre-defined position parameters and also monitor the plurality of pre-defined position parameters of the user to determine corresponding values. The recommendation system compare the values of the plurality of pre-defined position parameters with predefined values of the pre-defined position parameters and identify deviations in one or more of the plurality of pre-defined position parameters based on the comparison and provide recommendations for correcting the deviations from the pre-defined position parameters to the user.

An abnormality processing system is provided capable of executing appropriate processing in cases where an abnormality occurs in a worker's living body. A management computer 300, if determining that an abnormality is present in a worker's living body, transmits an abnormality signal to an administrator terminal 100, a work device 200, a worker camera 20 and a surveillance camera 50. When receiving the abnormality signal, the administrator terminal 100 displays an image showing that an abnormality has occurred. When receiving the abnormality signal, the work device 200 stops operation. When receiving the abnormality signal, the worker camera 20 and the surveillance camera 50 transmit to the management computer 300 imaging data containing at least data of images before and after a timing at which the abnormality has occurred in the worker's living body.

In embodiments of augmenting a moveable entity with a hologram, an alternate reality device includes a tracking system that can recognize an entity in an environment and track movement of the entity in the environment. The alternate reality device can also include a detection algorithm implemented to identify the entity recognized by the tracking system based on identifiable characteristics of the entity. A hologram positioning application is implemented to receive motion data from the tracking system, receive entity characteristic data from the detection algorithm, and determine a position and an orientation of the entity in the environment based on the motion data and the entity characteristic data. The hologram positioning application can then generate a hologram that appears associated with the entity as the entity moves in the environment.

Systems, devices, and methods are presented for segmenting an image of a video stream with a client device by receiving one or more images depicting an object of interest and determining pixels within the one or more images corresponding to the object of interest. The systems, devices, and methods identify a position of a portion of the object of interest and determine a direction for the portion of the object of interest. Based on the direction of the portion of the object of interest, a histogram threshold is dynamically modified for identifying pixels as corresponding to the portion of the object of interest. The portion of the object of interest is replaced with a graphical interface element aligned with the direction of the portion of the object of interest.

Techniques for detecting attributes and/or gestures associated with pedestrians in an environment are described herein. The techniques may include receiving sensor data associated with a pedestrian in an environment of a vehicle and inputting the sensor data into a machine-learned model that is configured to determine a gesture and/or an attribute of the pedestrian. Based on the input data, an output may be received from the machine-learned model that indicates the gesture and/or the attribute of the pedestrian and the vehicle may be controlled based at least in part on the gesture and/or the attribute of the pedestrian. The techniques may also include training the machine-learned model to detect the attribute and/or the gesture of the pedestrian.

A method for predicting a direction of movement of a target object, a method for training a neural network, a smart vehicle control method, a device, an electronic apparatus, a computer readable storage medium, and a computer program. The method for predicting a direction of movement of a target object comprises: acquiring an apparent orientation of a target object in an image captured by a camera device, and acquiring a relative position relationship of the target object in the image and the camera device in three-dimensional space (S100); and determining, according to the apparent orientation of the target object and the relative position relationship, a direction of movement of the target object relative to a traveling direction of the camera device (S110).

Provided are a product purchase support system (100), a product purchase support device (10), and a POS terminal device (20) that improve the efficiency of checkout processing for product sales and enhance the convenience of customers when purchasing a product. The product purchase support system (100) according to the present invention includes the product purchase support device (10) including a depth camera (12) and a first display device (13), and a POS terminal device (20) that performs checkout processing for a product. When the product purchase support device (10) detects a product selection motion of selecting a product by a customer, it identifies a product selected by the customer and generates product information related to this product, and displays the product information on the first display device (13). Further, the product purchase support device (10) outputs the product information to the POS terminal device (20).