A vehicular driver monitoring system includes a camera disposed within a vehicle and having a field of view interior of the vehicle, and an adjustable mirror disposed within the vehicle. The adjustable mirror includes a mirror reflector that reflects light incident thereat. The camera views the adjustable mirror and captures image data based on light reflected by the mirror reflector of the adjustable mirror toward the camera. With a driver of the vehicle sitting in a driver seat of the vehicle, light reflected off a portion of the driver is reflected by the mirror reflector of the adjustable mirror toward the camera. An electronic control unit (ECU), responsive to processing by an image processor of image data captured by the camera, adjusts the adjustable mirror to reflect the portion of the driver toward a region of the lens of the camera.

An AI robot for cleaning in consideration of a user's action includes a camera to acquire a first image data for the user, a cleaning unit including a suction unit and a mopping unit, a driving unit configured to drive the AI robot, and a processor to determine the user's action using the first image data, determine a cleaning schedule in consideration of the user's action, and control the cleaning unit and the driving unit based on the determined cleaning schedule.

An AI robot for cleaning in consideration of a user's action includes a camera to acquire a first image data for the user, a cleaning unit including a suction unit and a mopping unit, a driving unit configured to drive the AI robot, and a processor to determine the user's action using the first image data, determine a cleaning schedule in consideration of the user's action, and control the cleaning unit and the driving unit based on the determined cleaning schedule.

A model learning device provided with: an error-added movement locus generation unit for adding an error to movement locus data for action learning that represents the movement locus of a subject and to which is assigned an action label that is information representing the action of the subject, and thereby generating error-added movement locus data; and an action recognition model learning unit for learning a model, using at least the error-added movement locus data and learning data created on the basis of the action label, by which model the action of some subject can be recognized from the movement locus of the subject. Thus, it is possible to provide a model by which the action of a subject can be recognized with high accuracy on the basis of the movement locus of the subject estimated using a camera image.

Systems, methods, and non-transitory computer readable media for controlling perspective in an extended reality environment are disclosed. In one embodiment, a non-transitory computer readable medium contains instructions to cause a processor to perform the steps of: outputting for presentation via a wearable extended reality appliance (WER-appliance), first display signals reflective of a first perspective of a scene; receiving first input signals caused by a first multi-finger interaction with the touch sensor; in response, outputting for presentation via the WER-appliance second display signals to modify the first perspective of the scene, causing a second perspective of the scene to be presented via the WER-appliance; receiving second input signals caused by a second multi-finger interaction with the touch sensor; and in response, outputting for presentation via the WER-appliance third display signals to modify the second perspective of the scene, causing a third perspective of the scene to be presented via the WER-appliance.

Sign language information processing method and apparatus, an electronic device and a readable storage medium provided by the present disclosure, achieve real-time collection of language data in a current communication of a user by obtaining voice information and video information collected by a user terminal in real time; and then match a speaking person with his or her speaking content by determining, in the video information, a speaking object corresponding to the voice information; and finally, make it possible for the user to clarify the corresponding speaking object when the user sees AR sign language animation in a sign language video by superimposing and displaying an augmented reality AR sign language animation corresponding to the voice information on a gesture area corresponding to the speaking object to obtain a sign language video. Therefore, it is possible to provide a higher user experience.

A cleanup support system that supports a cleanup behavior includes: a first obtaining unit configured to obtain first information indicating a level of interest of a target person in cleanup; a second obtaining unit configured to obtain second information indicating a level of achievement of the cleanup performed by the target person; a determination unit configured to determine a content of control corresponding to the first information obtained and the second information obtained, with reference to a rule which associates the level of interest in the cleanup and the level of achievement of the cleanup with a content of control performed on a device; and a control unit configured to control the device according to the content of control determined.

A detection apparatus includes one or more processors. The processors set at least one time-period candidate. The processors input, to a first model that inputs a feature acquired from a plurality of time-series images and the time-period candidate and outputs at least one first likelihood indicating a likelihood of occurrence of at least one action previously determined as a detection target and correction information for acquisition of at least one correction time period resulting from correction of the at least one time-period candidate, the feature and the time-period candidate, and acquire the first likelihood and the correction information output from the first model. The processors detect, based on the at least one correction time period acquired based on the correction information and the first likelihood, the action included in the time-series images and a start time and a finish time of a time period of occurrence of the action.

A detection apparatus includes one or more processors. The processors set at least one time-period candidate. The processors input, to a first model that inputs a feature acquired from a plurality of time-series images and the time-period candidate and outputs at least one first likelihood indicating a likelihood of occurrence of at least one action previously determined as a detection target and correction information for acquisition of at least one correction time period resulting from correction of the at least one time-period candidate, the feature and the time-period candidate, and acquire the first likelihood and the correction information output from the first model. The processors detect, based on the at least one correction time period acquired based on the correction information and the first likelihood, the action included in the time-series images and a start time and a finish time of a time period of occurrence of the action.

A hearing aid and related systems and methods. In one implementation, a hearing aid system may comprise a wearable camera configured to capture images from an environment of a user, a microphone configured to capture sounds from the environment of the user, and a processor. The processor may be programmed to receive images captured by the camera; receive audio signals representative of sounds captured by the microphone; operate in a first mode to cause a first selective conditioning of a first audio signal; determine, based on analysis of at least one of the images or the audio signals, to switch to a second mode to cause a second selective conditioning of the first audio signal; and cause transmission of the first audio signal selectively conditioned in the second mode to a hearing interface device configured to provide sound to an ear of the user.