A processing apparatus includes a control unit that performs a control of performing, a plurality of times in parallel, a recognition operation in which a recognition unit recognizes a specific subject included in an imaging region based on a captured image obtained by imaging the imaging region by an imaging unit, and a distance measurement operation in which a distance measurement unit performs distance measurement by emitting light to the imaging region and receiving reflected light of the light from the imaging region, and a change unit that changes irradiation energy of the light to the imaging region for each distance measurement operation.

An emotion inference device includes: an obtainer that obtains a second evaluation value group and then a first evaluation value group each including evaluation values corresponding to emotion attributes of classified emotions of a subject; a processor that, when a difference under the same emotion attribute between corresponding evaluation values in the first and second evaluation value groups does not exceed a predetermined criterion, performs a correction process to reduce the evaluation value corresponding to the same emotion attribute in the first evaluation value group, and performs an inference process to infer the emotion of the subject based on the corrected first evaluation value group, in which an emotion attribute having a relatively higher evaluation value is inferred relatively more strongly as the emotion of the subject; and an outputter that outputs a result of the inference process performed by the processor.

Provided are an information processing system, an information processing method, and an information processing apparatus that can grasp an emotion transmission ability. An index of emotion of a person in a first area is measured. Map data representing the measured index in association with a position of the person in the first area is created. An emotion transmission ability of the person is estimated based on the created map data. Information on the estimated emotion transmission ability of the person is stored in a storage unit.

A wearable apparatus is provided for capturing and processing images from an environment of a user. In one implementation, a wearable apparatus for monitoring activities includes a wearable image sensor configured to capture a plurality of images from an environment of a user of the wearable apparatus. The wearable apparatus also includes at least one processing device programmed to analyze the plurality of images to identify in one or more of the plurality of images at least one indicator of an activity, and to transmit, to an external device, the at least one indicator of the activity.

Provided are an information processing system and an information processing method which can easily grasp a state of a person in a predetermined area. The information processing system includes a first imaging unit that images a performer, a second imaging unit that images a person in a predetermined area, a first recognition unit that recognizes a scene based on an image captured by the first imaging unit, a second recognition unit that recognizes expression of the person based on an image captured by the second imaging unit, a calculation unit that calculates a state index of the person according to the scene based on a recognition result of the scene and a recognition result of the expression of the person, a heat map creation unit that creates a heat map representing the state index of the person in association with a position of the person in the predetermined area, and an output unit that outputs the heat map.

A face posture analysis method, an electronic device, and a computer-readable storage medium are provided. The face posture analysis method includes: obtaining a face key point of a to-be-processed face image; and inputting the face key point of the to-be-processed face image into a neural network, to obtain face posture information of the to-be-processed face image output by the neural network.

A feedback button is configured to receive a feedback expression characterizing a user experience and submit information in a user interface with a single action. When the user hovers an input cursor near the feedback button, icons/text may be displayed that indicate different types of feedback expressions that may be submitted. As the user moves the cursor back and forth over the button, the icons for the different feedback expressions may be emphasized indicating locations where the button may be clicked to submit specific feedback. When the user is satisfied with the displayed feedback expression, the user may click the feedback button at the current location to submit the feedback expression and perform the final submit action for other data in the user interface.

In some aspects, one or more processors may perform an analysis of a processed image using an artificial intelligence module. Based on the analysis, the one or more processors may determine that the processed image includes one or more threats and determine details associated with individual threats of the one or more threats. The one or more processors may determine, based on the details associated with the one or more threats, that a particular threat threshold of a plurality of threat thresholds has been satisfied. The one or more processors may add one or more annotations to the image to create an annotated image that includes the one or more threats and at least a portion of the details associated with individual threats of the one or more threats. The one or more processors may send a notification to one or more designated recipients.

Systems and methods are described for presenting identifiers for media assets recommended to users identified using facial recognition. Each of a first and a second user in a vicinity of user equipment is identified, and a first recommended media asset and a second media asset are determined based on respective user profiles of the first user and the second user. A first identifier selectable to access the first recommended media asset and a second identifier selectable to access the second recommended media asset are generated for display, and a recommended media asset associated with a selected identifier is generated for display.

The present disclosure describes systems, non-transitory computer-readable media, and methods for utilizing a machine learning model trained to determine subtle pose differentiations to analyze a repository of captured digital images of a particular user to automatically capture digital images portraying the user. For example, the disclosed systems can utilize a convolutional neural network to determine a pose/facial expression similarity metric between a sample digital image from a camera viewfinder stream of a client device and one or more previously captured digital images portraying the user. The disclosed systems can determine that the similarity metric satisfies a similarity threshold, and automatically capture a digital image utilizing a camera device of the client device. Thus, the disclosed systems can automatically and efficiently capture digital images, such as selfies, that accurately match previous digital images portraying a variety of unique facial expressions specific to individual users.