Systems and methods for video presentation and analytics for live sporting events are disclosed. At least two cameras are used for tracking objects during a live sporting event and generate video feeds to a server processor. The server processor is operable to match the video feeds and create a 3D model of the world based on the video feeds from the at least two cameras. 2D graphics are created from different perspectives based on the 3D model. Statistical data and analytical data related to object movement are produced and displayed on the 2D graphics. The present invention also provides a standard file format for object movement in space over a timeline across multiple sports.

Metadata for one or more highlights of a video stream may be extracted from one or more card images embedded in the video stream. The highlights may be segments of the video stream, such as a broadcast of a sporting event, that are of particular interest. According to one method, video frames of the video stream are stored. One or more information cards embedded in a decoded video frame may be detected by analyzing one or more predetermined video frame regions. Image segmentation, edge detection, and/or closed contour identification may then be performed on identified video frame region(s). Further processing may include obtaining a minimum rectangular perimeter area enclosing all remaining segments, which may then be further processed to determine precise boundaries of information card(s). The card image(s) may be analyzed to obtain metadata, which may be stored in association with at least one of the video frames.

A computing system receives a plurality of game files corresponding to a plurality of games across a plurality of seasons. The computing system generates a prediction model configured to generate a possession value for an event. The computing system receives a target event, in real-time or near real-time, from a tracking system monitoring a target game. The computing system generates target features for the target event based on target event data associated with the target event. The computing system generates, via the prediction model, a target possession value for the target event based on the target event data and the target features. The target possession value represents a likelihood that a team with possession will score within a following x-seconds after the target event.

A method of generating a path of an object through a virtual environment is provided, the method comprising: receiving image data, at a first instance of time, from a plurality of image capture devices arranged in a physical environment; receiving image data, at an at least one second instance of time after the first instance of time, from a plurality of image capture devices arranged in the physical environment; detecting a location of a plurality of points associated with an object within the image data from each image capture device at the first instance of time and the at least one second instance of time; projecting the location of the plurality of points associated with the object within the image data from each image capture device at the first instance of time and the at least one second instance of time into a virtual environment to generate a location of the plurality of points associated with the object in the virtual environment at each instance of time; and generating a path of the object through the virtual environment using the location of the plurality of points associated with the object in the virtual environment, the path being indicative of the position and orientation of the object through the virtual environment.

A computer-implemented method is provided for automated detection of a moving area of interest, such as a ball, in a video stream of filed sports with a common object of interest encompassing a plurality of players and the object of interest. Images of a sports ground are captured by means of a video camera system producing a video stream which is digitally processed to continuously identify a detected concentration of action within the boundaries of the field. The concentration of action in the field is determined based on an estimated position of the object of interest in at least one frame of the video stream. Players' postures or orientations may be detected to improve the accuracy of the determination of the object of interest.

A processing system including at least one processor may obtain at least one video of a first competitor along a competition route in a physical environment, obtain data characterizing at least one condition along the competition route as experienced by the first competitor, present visual data associated with the at least one video to a second competitor via a display device, and control at least one setting of at least one device associated with the second competitor to simulate the at least one condition, wherein the at least one device is distinct from the display device.

An image classification system for tracking a net sport is illustrated. The system includes a visual device configured to capture video footage of a match. The computing device is communicatively connected to the visual device and is configured to receive the video footage of the match from the visual device, translate video footage of the match from the visual device into a data representation by logging an event with a timestamp, and display data representation to a user.

Disclosed is a method and apparatus for extracting rules-based events from a soccer match video. The method of extracting a rules-based event from a soccer match video includes setting rules for each category of events to be extracted from a sports match video; extracting ball possession and ball coordinates based on tracking coordinate data of at least one player and tracking coordinate data of a ball in the sports match video, identifying that an event of a specific category is started at a specific point in time of the sports match video when a condition for before a start of an event and a condition for after a start of an event in the rule are satisfied, and identifying that the event is ended at another specific point in time of the sports match video when a condition for an end of an event in the rule is satisfied.

A computer-implemented method according to one embodiment includes running an initial network on a plurality of images to detect actors pictured therein and body joints of the detected actors. The method further includes running fully-connected networks in parallel, one fully-connected network for each of the detected actors, to reconstruct complete three-dimensional poses of the actors. Sequential model fitting is performed on the plurality of images. The sequential model fitting is based on results of running the initial network and the fully-connected networks. The method further includes determining, based on the sequential model fitting, a locational position for a camera in which the camera has a view of a possible point of collision of two or more of the actors. The camera is instructed to be positioned in the locational position.

Method, systems and apparatuses may provide for technology that extracts one or more motion features from filtered position data associated with a projectile in a game and identifies a turning point in a trajectory of the projectile based on the one or more motion features. The technology may also automatically designate the turning point as a highlight moment if one or more of the turning point or the trajectory satisfies a proximity condition with respect to a target area in the game.