Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework for performing automatic detection of surfaces in video frames resulting in the creation of a seamless in-video ad experience for viewing users. The disclosed framework operates by leveraging available surfaces in videos to show advertisements in compliance with publisher protection, compliance and policy in a fully automatic, end-to-end solution. The disclosed framework evidences a streamlined, automatic and computationally efficient process(es) that modifies digital content at the surface level within the frames of the content in compliance with the digital rights of the owners of the content being merged via the disclosed augmentation.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in computerized security and content monitoring, hosting and providing devices, systems and/or platforms. The disclosed systems and methods provide a novel framework that adaptively distinguishes between known people versus unknown people based on a dynamically applied, anonymous facial recognition methodology. The disclosed framework provides such functionality by recognizing faces within captured images without storing any information or annotations regarding or revealing the captured person's identity. The framework is configured to adaptively learn to distinguish between faces seen for the first time and faces it has previously seen by locally processing a captured image and only sending face embeddings to a network location for future comparisons of subsequently, anonymously captured images.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework for performing automatic detection of surfaces in video frames resulting in the creation of a seamless in-video ad experience for viewing users. The disclosed framework operates by leveraging available surfaces in videos to show advertisements in compliance with publisher protection, compliance and policy in a fully automatic, end-to-end solution. The disclosed framework evidences a streamlined, automatic and computationally efficient process(es) that modifies digital content at the surface level within the frames of the content in compliance with the digital rights of the owners of the content being merged via the disclosed augmentation.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, hosting and/or providing systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide an image processing framework that sub-divides computer vision techniques into three computationally efficient steps: detection, classification and matching. These steps provide an improved image processing framework that can analyze live stream data of a media file, in real-time, in order to identify and track specific digital objects depicted therein. This enables not only image processing detection results, but also the capabilities of augmenting the video stream with additional data related to the detected object.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework for performing automatic detection of surfaces in video frames resulting in the creation of a seamless in-video ad experience for viewing users. The disclosed framework operates by leveraging available surfaces in videos to show advertisements in compliance with publisher protection, compliance and policy in a fully automatic, end-to-end solution. The disclosed framework evidences a streamlined, automatic and computationally efficient process(es) that modifies digital content at the surface level within the frames of the content in compliance with the digital rights of the owners of the content being merged via the disclosed augmentation.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework for performing automatic detection of surfaces in video frames resulting in the creation of a seamless in-video ad experience for viewing users. The disclosed framework operates by leveraging available surfaces in videos to show advertisements in compliance with publisher protection, compliance and policy in a fully automatic, end-to-end solution. The disclosed framework evidences a streamlined, automatic and computationally efficient process(es) that modifies digital content at the surface level within the frames of the content in compliance with the digital rights of the owners of the content being merged via the disclosed augmentation.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework for performing automatic detection of surfaces in video frames resulting in the creation of a seamless in-video ad experience for viewing users. The disclosed framework operates by leveraging available surfaces in videos to show advertisements in compliance with publisher protection, compliance and policy in a fully automatic, end-to-end solution. The disclosed framework evidences a streamlined, automatic and computationally efficient process(es) that modifies digital content at the surface level within the frames of the content in compliance with the digital rights of the owners of the content being merged via the disclosed augmentation.

Abstract: An exemplary method includes an augmented reality system acquiring an image of an event from a viewpoint of a camera of a computing device in proximity to the event, the event including a performance area; identifying at least part of the performance area of the event within the image of the event; determining a three-dimensional (3D) pose of the performance area of the event within the image of the event; and providing, for concurrent display by a display device of the computing device, the image of the event and augmented reality content that is oriented according to the 3D pose of the performance area of the event within the image of the event.

Abstract: An exemplary method includes an augmented reality system acquiring an image of an event from a viewpoint of a camera of a computing device in proximity to the event, the event including a performance area; identifying at least part of the performance area of the event within the image of the event; determining a three-dimensional (3D) pose of the performance area of the event within the image of the event; and providing, for concurrent display by a display device of the computing device, the image of the event and augmented reality content that is oriented according to the 3D pose of the performance area of the event within the image of the event.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in computerized security and content monitoring, hosting and providing devices, systems and/or platforms. The disclosed systems and methods provide a novel framework that adaptively distinguishes between known people versus unknown people based on a dynamically applied, anonymous facial recognition methodology. The disclosed framework provides such functionality by recognizing faces within captured images without storing any information or annotations regarding or revealing the captured person's identity. The framework is configured to adaptively learn to distinguish between faces seen for the first time and faces it has previously seen by locally processing a captured image and only sending face embeddings to a network location for future comparisons of subsequently, anonymously captured images.

Abstract: One or more computing devices, systems, and/or methods for generating augmented videos are provided. First coordinates, of a first video frame of a video, may be determined for projection of a graphical object. A first plurality of keypoints on the first video frame may be determined based upon a set of objects. A second plurality of keypoints on a second video frame may be determined. A keypoint of the second plurality of keypoints may correspond to a keypoint of the first plurality of keypoints. A relationship between the first video frame and the second video frame may be determined based upon the first plurality of keypoints and the second plurality of keypoints. Second coordinates of the second video frame may be determined based upon the first coordinates and the relationship. The graphical object may be projected onto the second video frame based upon the second coordinates.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in computerized security and content monitoring, hosting and providing devices, systems and/or platforms. The disclosed systems and methods provide a novel framework that adaptively distinguishes between known people versus unknown people based on a dynamically applied, anonymous facial recognition methodology. The disclosed framework provides such functionality by recognizing faces within captured images without storing any information or annotations regarding or revealing the captured person's identity. The framework is configured to adaptively learn to distinguish between faces seen for the first time and faces it has previously seen by locally processing a captured image and only sending face embeddings to a network location for future comparisons of subsequently, anonymously captured images.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in computerized security and content monitoring, hosting and providing devices, systems and/or platforms. The disclosed systems and methods provide a novel framework that adaptively distinguishes between known people versus unknown people based on a dynamically applied, anonymous facial recognition methodology. The disclosed framework provides such functionality by recognizing faces within captured images without storing any information or annotations regarding or revealing the captured person's identity. The framework is configured to adaptively learn to distinguish between faces seen for the first time and faces it has previously seen by locally processing a captured image and only sending face embeddings to a network location for future comparisons of subsequently, anonymously captured images.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, hosting and/or providing systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide an image processing framework that sub-divides computer vision techniques into three computationally efficient steps: detection, classification and matching. These steps provide an improved image processing framework that can analyze live stream data of a media file, in real-time, in order to identify and track specific digital objects depicted therein. This enables not only image processing detection results, but also the capabilities of augmenting the video stream with additional data related to the detected object.

Abstract: One or more computing devices, systems, and/or methods for generating augmented videos are provided. First coordinates, of a first video frame of a video, may be determined for projection of a graphical object. A first plurality of keypoints on the first video frame may be determined based upon a set of objects. A second plurality of keypoints on a second video frame may be determined. A keypoint of the second plurality of keypoints may correspond to a keypoint of the first plurality of keypoints. A relationship between the first video frame and the second video frame may be determined based upon the first plurality of keypoints and the second plurality of keypoints. Second coordinates of the second video frame may be determined based upon the first coordinates and the relationship. The graphical object may be projected onto the second video frame based upon the second coordinates.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, hosting and/or providing systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide an image processing framework that sub-divides computer vision techniques into three computationally efficient steps: detection, classification and matching. These steps provide an improved image processing framework that can analyze live stream data of a media file, in real-time, in order to identify and track specific digital objects depicted therein. This enables not only image processing detection results, but also the capabilities of augmenting the video stream with additional data related to the detected object.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content searching, hosting and/or providing systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel machine-in-the-loop, image-to-video bootstrapping framework that harnesses a training set built upon an image dataset and a video dataset in order to efficiently produce an accurate training set to be applied to frames of videos. The disclosed systems and methods reduce the amount of time required to build the training dataset, and also provide mechanisms to apply the training dataset to any type of content and for any type of recognition task.

Abstract: Systems, methods, and non-transitory computer readable media configured to determine a degree of separation between a user and a connection within a social network of the user, the connection associated with an interaction from which at least topic is determined. A value of affinity between the user and the connection is determined. A weight reflecting a value of interest similarity between the user and the connection is determined. A term based on the degree of separation, the value of affinity, and the weight reflecting a value of interest similarity is calculated. Terms associated with the at least one topic are combined to generate a composite score associated with the at least one topic to determine whether to present the at least one topic to the user.

Abstract: A system of generating advertising inventory by marketers sharing content with others via a social network or other electronic communication across a network. This embodiment may include allowing one or more content providers to provide links to content items. The content items may be provided directly by the content provider or by a clearinghouse entity or other intermediary. A subscriber may then search for relevant content items from one or more content providers. The subscriber may provide ancillary content for association with the selected content item. Thus, when the subscriber shares a URL identifying the selected content item via a social network, the URL may be encoded with a unique identifier identifying the subscriber. When the URL is clicked by a user, an ad server on the publisher's side may recognize the unique identifier and display the content item with the ancillary content provided by the subscriber.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework for performing automatic detection of surfaces in video frames resulting in the creation of a seamless in-video ad experience for viewing users. The disclosed framework operates by leveraging available surfaces in videos to show advertisements in compliance with publisher protection, compliance and policy in a fully automatic, end-to-end solution. The disclosed framework evidences a streamlined, automatic and computationally efficient process(es) that modifies digital content at the surface level within the frames of the content in compliance with the digital rights of the owners of the content being merged via the disclosed augmentation.