At&t Intellectual Property I, L.p.

Hyundai Motor Company

Kia Corporation

Raghuraman Gopalan

Eric Martin Zavesky

David Crawford Gibbon

Lee Begeja

Behzad Shahraray

Bernard S Renger

Zhu Liu

Yadong Mu

Amy Ruth Reibman

Tan Xu

Paul Triantafyllou

Eric Zevesky

Aspects of the subject disclosure may include, for example, a system and method for selecting media content for a group of persons located at a venue. The system and method identify a plurality of viewers in a vicinity of a venue that has one or more display devices from location data and extracts a content viewing preference of each viewer from their profile data. The process includes aggregating the content viewing preference of each of the plurality of viewers to generate an aggregated content profile. Based on the aggregated content profile, a list of content is generated. Next, a first group of viewers approaching a viewing range of a display device are sensed by imaging data. Any conflicts between content viewing preferences of the first group of viewers are detected and resolved based on weighting the viewing preferences of the group. Other embodiments are disclosed.

Automated content selection for groups

Aspects of the subject disclosure may include, for example, a method comprising obtaining, by a processing system including a processor, first and second models for a structure of an object, based respectively on ground-level and aerial observations of the object. Model parameters are determined for a three-dimensional (3D) third model of the object based on the first and second models; the determining comprises a transfer learning procedure. Data representing observations of the object is captured at an airborne unmanned aircraft system (UAS) operating at an altitude between that of the ground-level observations and the aerial observations. The method also comprises dynamically adjusting the third model in accordance with the operating altitude of the UAS; updating the adjusted third model in accordance with the data; and determining a 3D representation of the structure of the object, based on the updated adjusted third model. Other embodiments are disclosed.

Structure from Motion for drone videos

One example of a method includes receiving a plurality of video streams depicting a scene, wherein the plurality of video streams provides images of the scene from a plurality of different viewpoints, identifying a target that is present in the scene, wherein the target is identified based on a determination of a likelihood of being of interest to a viewer of the scene, determining a trajectory of the target through the plurality of video streams, wherein the determining is based in part on an automated visual analysis of the plurality of video streams, wherein the determining is based in part on a visual analysis of the plurality of video streams, rendering a volumetric video traversal that follows the target through the scene, wherein the rendering comprises compositing the plurality of video streams, receiving viewer feedback regarding the volumetric video traversal, and adjusting the rendering in response to the viewer feedback.

Selecting viewpoints for rendering in volumetric video presentations

Task delegation and cooperation for automated assistants is presented. A method comprises receiving, at a centralized support center that is in contact with a plurality of automated assistants including a first automated assistant and a second automated assistant, a request to perform a task on behalf of an individual, formulating, at the centralized support center, the task as a plurality of sub-tasks including a first sub-task and a second sub-task, delegating, at the centralized support center, the first sub-task to the first automated assistant, based on a determination at the centralized support center that the first automated assistant is capable of performing the first sub-task, and delegating, at the centralized support center, the second sub-task to the second automated assistant, based on a determination at the centralized support center that the second automated assistant is capable of performing the second sub-task.

Task delegation and cooperation for automated assistants

Aspects of the subject disclosure may include, for example, systems and methods aggregating video content and adjusting the aggregate video content according to a training model. The adjusted aggregate video content comprises a first subset of the images and does not comprise a second subset of the images. The first subset of the images is determined by the training model based on a plurality of categories corresponding to a plurality of events. The illustrative embodiments also include presenting the adjusted aggregate video content and receiving identifications for the first subset of the images in the aggregate video content. Further, the illustrative embodiments include adjusting the training model according to the identifications and providing the adjusted training model to a network device. Other embodiments are disclosed.

Method and system for aggregating video content

A method and apparatus for providing a recommended action are disclosed. For example, the method receives first data that is measured via at least one sensor deployed at a venue, receives second data from at least one user endpoint device present at the venue, wherein the second data comprises data that is measured via a sensor associated with the at least one user endpoint device, applies a perception model of the venue to the first data and the second data that are received, generates at least one recommended action when a threshold is reached, wherein the threshold is established for generating the at least one recommended action, and provides an update to the perception model of the venue based on the at least one recommended action that is generated.

Method and apparatus for providing a recommended action for a venue via a network

Structure from motion for drone videos

A wireless communication device includes a processor, a display device coupled to the processor, and a memory accessible to the processor. The memory includes instructions executable by the processor to perform operations. The operations include receiving a user input to play a media content item. The operations include sending a request for a summary of the media content item to a network device in response to the user input in lieu of sending a particular request for the media content item. The operations also include, in response to the reply including media content, sending the media content to the display device for display.

Providing a summary of media content to a communication device

In one example, the present disclosure describes a device, computer-readable medium, and method for adaptively clustering media content from multiple different domains in the presence of domain shift. For instance, in one example, a plurality of data content items is acquired from a plurality of different domains, wherein at least some data content items of the plurality of data content items are unlabeled. The plurality of data content items is encoded with a feature representing a domain shift variation that is assumed to be present in the plurality of data content items, wherein the domain shift variation comprises variation in a characteristic of the plurality of data content items. The plurality of data content items is clustered into a predefined number of content categories subsequent to the encoding.

Adaptive clustering of media content from multiple different domains

Aspects of the subject disclosure may include, for example, modifying a user profile associated with a user associated with a content service to generate an updated user profile according to consumption of media content by the user and user feedback information associated with the consumption of the media content, determining a user context according to information associated with user device, where the user context includes current activity of the user, modifying a set of media content according to the user context that is determined to generate an updated set of media content, where a type of media content is eliminated from the set of media content in the updated set of media content according to the user context, and presenting the updated set of content at a presentation device of the user via a personal media channel of the user associated with the content service. Other embodiments are disclosed.

Method and apparatus for content curation

Aspects of the subject disclosure may include, for example, embodiments for determining a media profile for media content. The media profile comprises a media metric for each of a plurality of portions of the media content. Further, embodiments include determining a price for advertising associated with the media content. In addition, embodiments include identifying an advertisement profile for each of a plurality of advertisements. The advertisement profile comprises an ad metric for each of a plurality of portions of an advertisement. Also, embodiments include selecting a first advertisement associated with a first advertisement profile from the plurality of advertisements according to the media profile, the first advertisement profile, and the price for the advertising associated with the media content. Further, embodiments include providing the first advertisement to be presented with the media content at a playback device. Other embodiments are disclosed.

Methods, systems and devices for selecting advertisements based on media profiles and advertisement profiles

In one example, the present disclosure describes a device, computer-readable medium, and method for enabling secure video sharing by exploiting data sparsity. In one example, the method includes applying a transformation to a video dataset containing a plurality of video samples, to produce a plurality of sparse vectors in a first dimensional space, wherein each sparse vector of the plurality of sparse vectors corresponds to one video sample of the plurality of video samples, and multiplying each sparse vector of the plurality of sparse vectors by a transformation matrix to produce a plurality of reduced vectors in a second dimensional space, wherein the dimension of the second dimensional space is smaller than a dimension of the first dimensional space, and wherein the plurality of reduced vectors in the second dimensional space hides information about the video dataset while preserving relational properties between the plurality of video samples.

Enabling secure video sharing by exploiting data sparsity

A method, computer-readable medium, and apparatus for modeling data of a service for providing a policy are disclosed. For example, a method may include a processor for generating a first policy for a first service by a first policy model using machine learning for processing first data of the first service, determining whether the first policy is to be applied to a second service, applying the first policy to the second service when the first policy is deemed to be applicable to the second service, wherein the applying the first policy provides the first policy to a second policy model using machine learning for processing second data of the second service, generating a second policy for the second service, and implementing the second policy in the second service, wherein the first service and the second service are provided by a single service provider.

Growing community of inventors

Dublin, CA, United States of America

Raghuraman Gopalan