Abstract: In various embodiments, a Data Processing System for Generating Interactive User Interfaces and Interactive Game Systems Based on Spatiotemporal Analysis of Video Content may be configured to: (1) enable a user to select one or more players participating in a substantially live (e.g., live) sporting or other event; (2) determine scoring data for each of the one or more selected players during the sporting or other event; (3) track the determined scoring data; (4) generate a custom (e.g., to the user) user interface that includes the scoring data; and (5) display the custom user interface over at least a portion of a display screen (e.g., on a mobile computing device) displaying one or more video feeds of the sporting or other event. In this way, the system may be configured to convert a video feed of a sporting event into an interactive game.

Abstract: Methods and systems for finding and ranking video sequences that contain tactical sequences (e.g., an uninterrupted portion of a sporting event) that are similar to tactical event content in a target video sequence, such as those occurring in sports, include learning and labelling (e.g., through use of metadata and the like) tactically significant sequences in a plurality of video segments, including a plurality of such tactically significant sequences in a single video segment.

Abstract: The present disclosure relates to a high precision method, model, and apparatus for calibrating the intrinsic camera parameter values of one or more intrinsic parameters of a camera. The intrinsic parameters include focal lengths, skew, optical center, and radial distortion coefficients. The practical implementation of the solution consists of a camera capturing several images of a planar calibration pattern from different viewpoints, and a computer implemented processing pipeline. The solution does not require additional human input and is robust to misdetection of the calibration pattern in some of the images.

Abstract: Data processing systems and methods are disclosed for augmenting video content with one or more augmentations to produce augmented video. Elements within video content may be identified by spatiotemporal indices and may have associated values. An advertiser can pay to have an augmentation added to an element that, for example, advertises the advertiser's goods and/or includes a link that, when activated, takes a user to the advertiser's website. Elements may have associated contexts that can be used to determine augmentations and element value, such as a position and/or current use of the element.

Abstract: Data processing systems are disclosed for determining semantic and person keypoints for an environment and an image and matching the keypoints for the image to the keypoints for the environment. A homography is generated based on the keypoint matching and decomposed into a matrix. Camera parameters are then determined from the matrix. A plurality of random camera poses can be generated and used to project keypoints for an environment using image keypoints. The projected keypoints can be compared to the actual keypoints for the environment to determine an error and weighting for each of the random camera poses.

Abstract: A location in a video may be specified and content related to the location may be accessed. A method for accessing the related content may include receiving a reference to a pixel location in a frame of a video feed of a filmed occurrence and accessing a spatio-temporal index corresponding to the filmed occurrence. The spatio-temporal index may index information relating to events or objects of the filmed occurrence and corresponding pixel locations at which the events or the objects are detected in the video feed. The method may further include querying the spatio-temporal index using the pixel location to determine particular information of an indexed event or an indexed object and receiving the particular information wherein the particular information indicates at least one of spatial and temporal alignment parameters for aligning the indexed event with a corresponding event in at least one other video feed of the filmed occurrence.

Abstract: Data processing systems and methods are disclosed for augmenting video content with one or more augmentations to produce augmented video. Elements within video content may be identified by spatiotemporal indices and may have associated values. An advertiser can pay to have an augmentation added to an element that, for example, advertises the advertiser's goods and/or includes a link that, when activated, takes a user to the advertiser's web site. Elements may have associated contexts that can be used to determine augmentations and element value, such as a position and/or current use of the element.

Abstract: Video feeds may be analyzed to identify matchups between participants. The matchups may be used to derive a competition, context, statistics, and the like. A result of the derived competition may depend, at least in part, on an ordering and outcomes of a set of matchup events. The derived competition may be presented as a collection of video clips corresponding to the set of matchup events, related commentary, and/or related statistics.

Abstract: Methods and systems for finding and ranking video sequences that contain tactical sequences (e.g., an uninterrupted portion of a sporting event) that are similar to tactical event content in a target video sequence, such as those occurring in sports, include learning and labelling (e.g., through use of metadata and the like) tactically significant sequences in a plurality of video segments, including a plurality of such tactically significant sequences in a single video segment.

Abstract: Data processing systems are disclosed for determining semantic and person keypoints for an environment and an image and matching the keypoints for the image to the keypoints for the environment. A homography is generated based on the keypoint matching and decomposed into a matrix. Camera parameters are then determined from the matrix. A plurality of random camera poses can be generated and used to project keypoints for an environment using image keypoints. The projected keypoints can be compared to the actual keypoints for the environment to determine an error and weighting for each of the random camera poses.

Abstract: Video may be edited to include collaborations by users. Collaborations may be added to the video and associated with a span of the video. The span of the collaborations may be determined according to an action that is received from a user contemporaneously with the playback of the video. In some cases, the span of the collaborations may be determined automatically by analyzing the collaboration and the video frames to which the user initial added the collaborations. Analysis of the collaborations and video frame may be used to determine span criteria for the frames of the video that should be associated with the collaborations.