The present disclosure relates to methods and apparatuses for identifying an object of interest of a user. One example method includes obtaining information about a line-of-sight-gazed region of the user and an environment image corresponding to the user, obtaining information about a first gaze region of the user in the environment image based on the environment image, where the first gaze region is used to indicate a sensitive region determined by using a physical feature of a human body, and obtaining a target gaze region of the user based on the information about the line-of-sight-gazed region and the information about the first gaze region. The gaze region is used to indicate a region in which a target object gazed by the user in the environment image is located.

An information processing apparatus according to the present invention includes: a display control unit that displays, on a screen, a map of a search area, a camera icon indicating a location of a surveillance camera in the map, and a person image of a search target person; an operation receiving unit that receives an operation of superimposing, on the screen, one of the person image or the camera icon on the other; and a processing request unit that requests a matching process between the person image and a surveillance video captured by the surveillance camera corresponding to the camera icon based on the operation.

A system is provided that includes a mobile user device (300) that executes an application and determines and transmits a recipe for generating a target cosmetic material that is based on a combination of a plurality of separate ingredients that are associated with the user. The system includes a dispensing device (100) configured to receive the transmitted recipe from the mobile user device 300) and dispense each of the plurality of separate ingredients onto a common dispensing surface such that when the dispensed amounts of each of the plurality of separate ingredients is blended on the dispensing surface, the target cosmetic material is achieved.

A system is provided that includes a mobile user device (300) that executes an application and determines and transmits a recipe for generating a target cosmetic material that is based on a combination of a plurality of separate ingredients that are associated with the user. The system includes a dispensing device (100) configured to receive the transmitted recipe from the mobile user device 300) and dispense each of the plurality of separate ingredients onto a common dispensing surface such that when the dispensed amounts of each of the plurality of separate ingredients is blended on the dispensing surface, the target cosmetic material is achieved.

An information processing system for obtaining an audio content file for video data providing video content representing a sport event, including: a receiver configured to receive a data stream including the video data; a preference data obtainer configured to obtain preference data, wherein the preference data indicate a selected competitor participating in the sport event; a category identifier obtainer configured to obtain a category identifier from a machine learning algorithm into which the video data is input, wherein the machine learning algorithm is trained to classify a scene represented in the video content into a category of a predetermined set of categories associated with the sport event, wherein the category identifier indicates the category into which the scene is classified; an audio content file obtainer configured to obtain, based on the obtained category identifier and the obtained preference data, the audio content file from a prestored set of audio content files, wherein the audio content file provides audio content associated with the category of the scene and the preference data; and a synchronizer configured to synchronize the audio content and the video content for synchronized play back of the scene by a media player configured to play back the video content and the audio content file.

A human-object interaction detection method, a neural network and a training method therefor is provided. The human-object interaction detection method includes: performing first target feature extraction on an image feature of an image; performing first interaction feature extraction on the image feature; processing a plurality of first target features to obtain target information of a plurality of detected targets; processing one or more first interaction features to obtain motion information of a motion, human information of a human target corresponding to each motion, and object information of an object target corresponding to each motion; matching the plurality of detected targets with one or more motions; and updating human information of a corresponding human target based on target information of a detected target matching the corresponding human target, and updating object information of a corresponding object target based on target information of a detected target matching the corresponding object target.

A human-object interaction detection method, a neural network and a training method therefor is provided. The human-object interaction detection method includes: performing first target feature extraction on image features of an image to obtain first target features; performing first interaction feature extraction on image features to obtain first interaction features and scores thereof; determining at least some first interaction features in the first interaction features based on the score of each of the first interaction features; determining first motion features based on the at least some first interaction features and the image features; processing the first target features to obtain target information of targets in the image; processing the first motion features to obtain motion information of one or more motions in the image; and matching the targets with the motions to obtain a human-object interaction detection result.

Systems, methods and non-transitory computer readable media for analyzing objects data to generate a textual content reporting events are provided. An indication of an event may be received. An indication of a group of one or more objects associated with the event may be received. For each object of the group of one or more objects, data associated with the object may be received. The data associated with the group of one or more objects may be analyzed to select an adjective. A particular description of the event may be generated. The particular description may be based on the group of one or more objects. The particular description may include the selected adjective. A textual content may be generated. The textual content may include the particular description. The generated textual content may be provided.

In one example, a method performed by a processing system including at least one processor includes obtaining video footage of a first subject, creating a profile for the first subject, based on features extracted from the video footage, obtaining video footage of a second subject different from the first subject, adjusting movements of the second subject in the video footage of the second subject to mimic movements of the first subject as embodied in the profile for the first subject, to create video footage of a modified second subject, verifying that the video footage of the modified second subject is consistent with a policy specified in the profile for the first subject, and rendering a media including the video footage of the modified second subject when the video footage of the modified second subject is consistent with the policy specified in the profile for the first subject.

A system, method, and apparatus for implementing workflows across multiple differing systems and devices is provided herein. During operation, a workflow is automatically generated based upon a high probability of overloading resources with a current workflow. In particular, a workstation (or server) detects a high probability that a resource will be overloaded if a particular trigger is implemented. The workstation (or server) then determines an alternate trigger to reduce the chances that a resource will be overloaded. The alternate trigger and action can then be implemented or suggested as a newly-created workflow.