Generally, a system and method for an automatic detection of referee's decisions during a ball-game match are provided. The method may include receiving a plurality of images of a ball-game field generated during the ball-game match; determining, based on predetermined ball-game rules, a first subset of images of the plurality of images representing a first event that is suspected as a specified rule-based event; determining, based on the predetermine ball-game rules, a second subset of images of the plurality of images that represents a second event, wherein the second event is subsequent to the specified rule-based event according to the predetermined ball-game rules; and analyzing, based on the predetermined ball-game rules, the images of the second subset and further determining, based on the analysis thereof, a referee's decision concerning whether the first even is the specified rule-based event.

A computing system automatically detects, in a sequence of video frames, a video frame region that depicts a scoreboard. The video frames of the sequence depict image elements including (i) scoreboard image elements that are unchanging across the video frames of the sequence and (ii) other image elements that change across the video frames of the sequence. Given this, the computing system (a) receives the sequence, (b) engages in an edge-detection process to detect, in the video frames of the sequence, a set of edges of the depicted image elements, (c) identifies a subset of the detected set of edges based on each edge of the subset being unchanging across the video frames of the sequence, and (d) detects, based on the edges of the identified subset, the video frame region that depicts the scoreboard.

A computing system retrieves ball-by-ball data for a plurality of sporting events. The computing system generates a trained neural network based on ball-by-ball data supplemented with ball-by-ball data with ball-by-ball match context features and personalized embeddings based on a batsman and a bowler for each delivery. The computing system receives a target batsman and a target bowler for a pitch to be delivered in a target event. The computing system identifies target ball-by-ball data for a window of pitches preceding the to be delivered pitch. The computing system retrieves historical ball-by-ball data for each of the target batsman and the target bowler. The computing system generates personalized embeddings for both the target batsman and the target bowler based on the historical ball-by-ball data. The computing system predicts a shot type for the pitch to be delivered based on the target ball-by-ball data and the personalized embeddings.

A method may include serially joining different video clips from videos of different historical competitions to form a composite video competition, the different video clips comprising an indeterminate subset of clips drawn from a larger pool of clips, wherein each clip from a historical competition has an associated partial result contribution to a final result of the historical competition further include presenting a result during the composite video competition, the result comprising a linked combination of the partial result contributions from the different video clips.

Methods, systems, and computer-program products used for assessing athletic ability and generating performance data. In one embodiment, athlete performance data is generated through computer-vision analysis of video of an athletic performing, e.g., during practice or gameplay. The generated performance data for the athlete may include, for example, maximum speed, maximum acceleration, time to maximum speed, transition time (e.g., time to change direction), closing speed (e.g., time to close the distance to another athlete), average separation (e.g., between the athlete and another athlete), play-making ability, athleticism (e.g., a weighted computation and/or combination of multiple metrics), and/or other performance data. This performance data may be used to generate and/or update a profile associated with the athlete, which can be utilized for recruiting, scouting, comparing, and/or assessing athletes with greater efficiency and precision.

Techniques are disclosed to add augmented reality to a sub-view of a high resolution central video feed. In various embodiments, a central video feed is received from a first camera on a first recurring basis and time-stamped position information is received from a tracking system on a second recurring basis. The central video feed is calibrated against a spatial region encompassed by the central video feed. The received time-stamped position information and a determined plurality of tiles associated with at least one frame of the central video feed are used to define a first sub-view of the central video feed. The first sub-view and a homography defining placement of augmented reality elements on the at least one frame of the central video feed are provided as output to a device configured to use the first sub-view and the homography display the first sub-view.

A method includes obtaining position information relating to an object in a sporting event, determining, based on the position information, that a start event has occurred, wherein the start event indicates a start of play of the sporting event, and generating, according to a result of the determination, an instruction to start storing position information relating to the object.

An image processing apparatus extracts a foreground image corresponding to an object included in a processing image using a background image corresponding to the processing image, and generates the background image from the processing image. The image processing apparatus determines whether it is allowed to update the background image for use in the extraction, and based on a result of the determination, updates the background image for use in the extraction using the generated background image.

Methods, devices, and systems for segmenting and annotating videos for analysis are disclosed. A user identifies specific moments of the video that provide a teachable moment. A pre-context and a post-context portion of the video surrounding the identified moment are used to create a tile video. One or more tile videos are compiled in a user-defined order to generate a weave video with a specific focus or theme. The generated weave video is shared with one or more users and can be annotated to facilitate teaching and/or discussion.

Systems and methods for generating real-time synthetic crowd responses for events, to augment the experience of event participants, remote viewers, and the like. Various sensors monitor the event in question, and various event properties are derived from their output using an event state model. These event properties, along with various event parameters such as score, time remaining, etc., are then input to a machine learning model that determines a real-time synthetic audience reaction tailored to the immediate state of the event. Reaction parameters are used to generate a corresponding crowd or audience audio signal, which may be broadcast to event participants, viewers, spectators, or anyone who may be interested. This instantaneous, realistic crowd reaction more closely simulates the experience of events with full on-site audiences, enhancing the viewing experience of both event participants and those watching.