Described herein is a method and system for automated, context sensitive and non-intrusive insertion of consumer-adaptive content in video. It assesses ‘context’ in the video that a consumer is viewing through multiple modalities and metadata about the video. The method and system described herein analyzes relevance for a consumer based on multiple factors such as the profile information of the end-user, history of the content, social media and consumer interests and professional or educational background, through patterns from multiple sources. The system also implements local-context through search techniques for localizing sufficiently large, homogenous regions in the image that do not obfuscate protagonists or objects in focus but are viable candidate regions for insertion for the intended content. This makes relevant, curated content available to a user in the most effortless manner without hampering the viewing experience of the main video.

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.

Systems and methods are provided for identifying a key instrument in an event. One example method includes receiving a capture of the event and identifying, at a first computing device, the event. The key instrument is identified at the first computing device. An indicator to apply to and/or around the identified key instrument is generated for display.

A system for identifying a person approaching an access way of a sporting event. The is identified using pass-through facial recognition technology in which one or more images of the person are taken while the person is in motion. The person is identified by comparing one of the images taken while the person approaches the access way of the sporting event with a profile image of the person.

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.

One or more highlights of a video stream may be identified. The highlights may be segments of a video stream, such as a broadcast of a sporting event, that are of particular interest to one or more users. According to one method, at least a portion of the video stream may be stored. The portion of the video stream may be compared with templates of a template database to identify the one or more highlights. Each highlight may be a subset of the video stream that is deemed likely to match the one or more templates. The highlights, an identifier that identifies each of the highlights within the video stream, and/or metadata pertaining particularly to the one or more highlights may be stored to facilitate playback of the highlights for the users.

A remote engagement system for a live event occurring at a venue includes an output device located at the venue or remotely from the venue for providing audio and/or visual output to at least one recipient. A controller receives signals, such signals being representative of physical reactions of remote viewers and being transmitted from a plurality of user input devices located remotely from each other and from the venue and controls the output device located at the venue or remotely from the venue to provide an audio and/or visual output to people at the venue or located remotely from the venue.

A system and method for generating a play prediction for a team is disclosed herein. A computing system retrieves trajectory data for a plurality of plays from a data store. The computing system generates a predictive model using a variational autoencoder and a neural network by generating one or more input data sets, learning, by the variational autoencoder, to generate a plurality of variants for each play of the plurality of plays, and learning, by the neural network, a team style corresponding to each play of the plurality of plays. The computing system receives trajectory data corresponding to a target play. The predictive model generates a likelihood of a target team executing the target play by determining a number of target variants that correspond to a target team identity of the target team.

Systems, methods, and computer programming products are provided according to example embodiments to provide real-time streaming of video content, hit indicators, and hit analytics from target locations to users, spectators, and certification authorities. One embodiment is provided that at least includes a camera unit, configured to be directed at a target, to capture a stream of video content, and to transmit the stream of video content to a receiving unit. The receiving unit may be communicatively connected to a computing system configured to receive the stream of video content from the camera unit and identify hit locations of projectiles on the target through optical processing of the stream of video content. The computing system may be further configured to compute analytics pertaining to the detected hit locations on the target. Additionally, the computing system may be configured to generate enhanced video content by indicating the location of the hit and/or computed analytics within the stream of video content and transmit the enhanced video content for display on one or more display devices.

A system and method for detecting false or exaggerated responses to physical contact. Image capture devices are positioned around a monitored area for capturing still or video images of an activity that include a moment of contact. Those images are synchronized to allow for composite analysis. Then object detection is performed to identify objects of interest within the images. Structural elements of the objects are then identified. Based on the structural elements, a determination is made as to whether a contact was made, for example based on whether structural elements of two nearby objects became adjacent or overlapping with one another, a force is calculated based on a speed of movement of those elements, and then machine learning is used to determine whether a response to contact was within reasonable expectations based on the amount of force and other factors.