Abstract: Systems and methods are described for using a biometric response profile to predict a biometric response of a user to a future event in a content item and adjust the future event accordingly. An event occurring in the content item is determined. Biometric data of a user viewing the content item is received, the biometric data comprising a biometric response of the user to the event. A maximum acceptable biometric response is determined based on a user profile, and the future event is adjusted based on the maximum acceptable biometric response. The adjusting can include skipping the event or replacement the event with a replacement event.

Abstract: A media stream is accessed, and a classification model is selected for identifying objects in the media stream. Using the classification model, it is determined whether a content item of interest to the user is currently being received in the media stream. If the content item is currently being received in the media stream, at least a portion of the content item is recorded from the media stream. If the content item is not currently being received, then recording is paused or delayed until it is determined that the content item is being received.

Abstract: A first content type of a first media stream being output is determined, and at least one first classification model is selected based on the first content type. Objects are identified in the first media stream using the at least one first classification model and information related to the objects is generated for presentation. A change in output of media streams from the first media stream to a second media stream may then be detected. A second content type of the second media stream is then determined and at least one second classification model is selected based on the second content type. Objects are then identified in the second media stream using the at least one second classification model and information related to the objects in generated for presentation.

Abstract: Systems and methods are described for using a biometric response profile to predict a biometric response of a user to a future event. An event occurring in video content is determined. Biometric data of a user viewing the video content is received, the biometric data comprising a biometric response of the user to the event. A biometric response profile of the user indicating a predicted biometric response of the user to a future event corresponding to the event is generated based on the biometric data and the event.

Abstract: Systems and methods are described for using a biometric response profile to predict a biometric response of a user to a future event. An event occurring in video content is determined. Biometric data of a user viewing the video content is received, the biometric data comprising a biometric response of the user to the event. A biometric response profile of the user indicating a predicted biometric response of the user to a future event corresponding to the event is generated based on the biometric data and the event.

Abstract: Systems and methods are described for controlling a user device. Such methods and system may obtain, via an extended reality (XR) headset, a biometric response of a first user, determine, based on obtained location data, a location of the first user, and obtain, via a user device associated with a second user, a location of the second user. Methods and system may determine, using control circuitry, that the first user and the second user are co-located based on the location of the first user and the location of the second user, and, responsive to determining the first user and the second user are co located, determine, using control circuitry, a particular interest of the first user based on the biometric response of the first user. The methods and system may then generate, using control circuitry and based on determining the particular interest, a user notification indicating a presence of the first user.

Abstract: A first content type of a first media stream being output is determined, and at least one first classification model is selected based on the first content type. Objects are identified in the first media stream using the at least one first classification model and information related to the objects is generated for presentation. A change in output of media streams from the first media stream to a second media stream may then be detected. A second content type of the second media stream is then determined and at least one second classification model is selected based on the second content type. Objects are then identified in the second media stream using the at least one second classification model and information related to the objects in generated for presentation.

Abstract: A media stream is accessed, and a classification model is selected for identifying objects in the media stream. Using the classification model, it is determined whether a content item of interest to the user is currently being received in the media stream. If the content item is currently being received in the media stream, at least a portion of the content item is recorded from the media stream. If the content item is not currently being received, then recording is paused or delayed until it is determined that the content item is being received.

Abstract: A media stream is accessed, and one or more classification models are selected for the media stream. Using the selected classification models, at least one object in the media stream is identified. An input associated with an identified object is received and, in response, information related to the object is generated for presentation.

Abstract: At least one high-quality image of a speaker is captured. A low network quality condition may be detected between a client device and a video service node. In response to detecting the low network quality condition, a data stream comprising changes to the high-quality image of the speaker needed to recreate a representation of the speaker is generated. Transmission of the video stream of the speaker between the client device of the speaker and the video service node is stopped and, simultaneously, transmission of the data stream is begun. A digital twin of the speaker is then generated for display at the client device based on the data stream and the high-quality image of the speaker.

Abstract: At least one high-quality image of a speaker is captured. A low network quality condition may be detected between a client device and a video service node. In response to detecting the low network quality condition, a data stream comprising changes to the high-quality image of the speaker needed to recreate a representation of the speaker is generated. Transmission of the video stream of the speaker between the client device of the speaker and the video service node is stopped and, simultaneously, transmission of the data stream is begun. A digital twin of the speaker is then generated for display at the client device based on the data stream and the high-quality image of the speaker.

Abstract: At least one high-quality image of a speaker is captured. A low network quality condition may be detected between a client device and a video service node. In response to detecting the low network quality condition, a data stream comprising changes to the high-quality image of the speaker needed to recreate a representation of the speaker is generated. Transmission of the video stream of the speaker between the client device of the speaker and the video service node is stopped and, simultaneously, transmission of the data stream is begun. A digital twin of the speaker is then generated for display at the client device based on the data stream and the high-quality image of the speaker.