A computer-implemented method for segmenting and recombining video segments of an input video based on prerequisites is disclosed. The computer-implemented method includes classifying video segments of an input video with respective activities associated with the video segments. The computer-implemented method further includes determining one or more prerequisites for performing classified activities associated with video segments of the input video. The computer-implemented method further includes determining respective users which satisfy the one or more determined prerequisites for performing the classified activities associated with the video segments of the input video. The computer-implemented method further includes generating a new video for a user based, at least in part, on merging those video segments in which the user satisfies the one or more determined prerequisites for performing a classified activity associated with a video segment.

Systems and methods disclosed herein use a first machine learning architecture and a second machine learning architecture where the first machine learning architecture executes on a first processor and receives a first image representing a mouth of a user, determines user feedback for outputting to the user based on a first machine learning model, and outputs the user feedback for capturing a second image representing the mouth of the user. The second machine learning architecture executes on a second processor and receives the first image and the second image, and generates a 3D model of at least a portion of a dental arch of the user based on the first image and the second image where the 3D model is generated based on a second machine learning model of the second machine learning architecture.

Systems, computer program products, and methods are described herein for preserving image and acoustic sensitivity using reinforcement learning. The present invention is configured to initiate a file editing engine on the audiovisual file to separate the audiovisual file into a video component and an audio component; initiate a convolutional neural network (CNN) algorithm on the video component to identify one or more sensitive portions in the one or more image frames; initiate an audio word2vec algorithm on the audio component to identify one or more sensitive portions in the audio component; initiate a masking algorithm on the one or more image frames and the audio component; generate a masked video component and a masked audio component based on at least implementing the masking action policy; and bind, using the file editing engine, the masked video component and the masked audio component to generate a masked audiovisual file.

Systems and methods for providing a universal platform for at-home health testing and diagnostics are provided herein. In particular, a health testing and diagnostic platform is provided to connect medical providers with patients and to generate a unique, private testing environment. In some embodiments, the testing environment may facilitate administration of a medical test to a patient with the guidance of a proctor. In some embodiments, the patient may be provided with step-by-step instructions for test administration by the proctor within a testing environment. The platform may display unique, dynamic testing interfaces to the patient and proctor to ensure proper testing protocols and accurate test result verification.

Broadly speaking, the present techniques generally relate to a method and apparatus for video recognition, and in particular relate to a computer-implemented method for performing video recognition using a transformer-based machine learning, ML, model. Put another way, the present techniques provide new methods of image processing in order to automatically extract feature information from a video.

The present disclosure provides video processing methods, apparatuses and systems. The method includes: obtaining a to-be-processed video, where the to-be-processed video is obtained by performing feature removal processing for one or more objects in an original video; obtaining a feature restoration processing request for one or more to-be-processed objects; according to the feature restoration processing request for the one or more to-be-processed objects, obtaining feature image information corresponding to the one or more to-be-processed objects, where the feature image information for one of the one or more to-be-processed objects includes pixel position information of all or part of features for the one of the one or more to-be-processed objects in the original video; according to the feature image information for the one or more to-be-processed objects, performing feature restoration processing for the one or more to-be-processed objects in the to-be-processed video.

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.

Systems and methods are provided herein for determining types of references within a content item and mapping them to particular applications. A content management application identifies an entity and a context of the entity at a location within the content item. The content management application may identify the entity and the context of the entity in real time as a first user device processes the content item, or the content management application may identify and store the entity and the context of the entity in a database before providing the content item. After determining a presence of a second user device associated with a profile, the content management application determines at least one application associated with the entity and the context of the entity on the second user device and launches the application to create an immersive content consumption experience.

A processing system having at least one processor may detect a first object in a first video of a first user and detect a second object in a second video of a second user, where the first video and the second video are part of a visual communication session between the first user and the second user. The processing system may further detect a first action in the first video relative to the first object, detect a second action in the second video relative to the second object, detect a difference between the first action and the second action, and provide a notification indicative of the difference.

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.